Course Schedule 2023
| Unige Instructors | ||
| Computational models of visual perception | Fabio Solari | 13-17 Feb 2023 |
| Theory and Practice of Virtual Reality Systems | Manuela Chessa | 27 Feb -3 Mar 2023 |
| Introduction to Type Theory: from foundations to practice | Francesco Dagnino | 6-10 Mar 2023 |
| Introduction to formal verification: an appetiser | Angelo Ferrando, Giorgio Delzanno | 13-17 Mar 2023 |
| Strategic Choices: Games and Team Optimization | Marcello Sanguineti Lucia Pusillo | 27-31 Mar 2023 |
| An Introduction to Prolog | Viviana Mascardi | 3-5 Apr 2023 |
| Ricca - Leotta school May 2023 | Filippo Ricca, Maurizio Leotta | May 2023 |
| Mobile Security | Alessio Merlo | 22-26 May 2023 |
| Introduction to High Performance Computing | Daniele D'Agostino | 29 May - 2 Jun |
| Theory and Practice of Runtime Monitoring | Davide Ancona | 5-9 Jun 2023 |
| CVCC + DL | Francesca Odone Nicoletta Noceti | 5-9 Jun 2023 |
| Machine Learning School | Lorenzo Rosasco | 19-23 Jun 2023 |
| Effective habits and skills for successful young scientists | Fabio Roli | 26-30 Jun 2023 |
| Adversarial Machine Learning | Fabio Roli, Luca Demetrio | 3-5 Jul 2023 |
| Trustworthy Artificial Intelligence | Luca Oneto | 10-14 Jul 2023 |
| External Instructors (CNR/IMT Lucca) | ||
|
An introduction to optimization over time and its application to online machine learning and reinforcement learning |
Giorgio Gnecco | 20-24 Feb 2023 |
| An Introduction to Model Predictive Control and Rolling Horizon Optimization |
Mauro Gaggero | 20-24 Mar 2023 |
| Network monitoring and inspection | Matteo Repetto | 27-31 Mar 2023 |
| Accelerated Parallel Systems: the GPU and FPGA cases | Antonella Galizia | 17-21 Apr 2023 |
| Information Hiding | Luca Caviglione | 17-21 Jul 2023 |
Detailed information
Computational models of visual perception
Duration: 20 hours (+ final project)
Instructor:
Fabio Solari – DIBRIS, University of Genoa – This email address is being protected from spambots. You need JavaScript enabled to view it.
When: 13-17 February 2023
Where: via Dodecaneso 35
Abstract
This course introduces paradigms and methods that allow students to develop computational models of visual perception, which are based on hierarchical networks of interacting neural units, mimicking biological processing stages.
Program
- Introduction to visual perception and to the cortical dorsal and ventral streams for action and recognition tasks.
- Hierarchical networks of functional neural units. Computational models of the visual features estimation for action and recognition. Comparison among computational models and computer vision algorithms. Benchmark Datasets. How to use computational models to improve virtual and augmented reality systems to allow natural perception and interaction.
- Case studies: models and algorithms of the literature.
References
- R, Hussain, M. Chessa, F. Solari, “Mitigating Cybersickness in Virtual Reality Systems through Foveated Depth-of-Field Blur”. Sensors, 21(12), p.4006, 2021
- G. Maiello, M. Chessa, P.J. Bex, F. Solari. Near-optimal combination of disparity across a log-polar scaled visual field. PLoS Computational Biology 16(4): e1007699, 2020
- W.S. Grant, J. Tanner, L. Itti. "Biologically plausible learning in neural networks with modulatory feedback." Neural Networks 88: 32-48, 2017
- F. Solari, M. Chessa, NK Medathati, P. Kornprobst. “What can we expect from a V1-MT feedforward architecture for optical flow estimation?”. Signal Processing: Image Communication. 1;39:342-54 ,2015
- G. Maiello, M. Chessa, F. Solari, P.J. Bex. The (In) Effectiveness of Simulated Blur for Depth Perception in Naturalistic Images. PLoS one, 10(10), pp. e0140230, 2015
- A.F. Russell, S. Mihalaş, R. von der Heydt, E. Niebur, R. Etienne-Cummings. "A model of proto-object based saliency." Vision research 94: 1-15, 2014
- P. Bayerl, H. Neumann. “Disambiguating visual motion by form-motion interaction—a computational model”. International Journal of Computer Vision. 72(1):27-45, 2007
- R.S. Zemel, P. Dayan, A. Pouget. “Probabilistic interpretation of population codes”. Neural Computation, 10(2), pp.403-430, 1998
An introduction to optimization over time and its application to online machine learning and reinforcement learning
Duration: 20 hours
Instructor:
Giorgio Gnecco – IMT Lucca – This email address is being protected from spambots. You need JavaScript enabled to view it.
When: 20 -24 February 2023
Where: In one of the DIBRIS buildings either in Via Dodecaneso or in Via Opera Pia. Students’ attendance on Teams is also possible.
Abstract
The course first provides an introduction to classical methods of dynamic optimization, such as the Bellman Optimality Principle and the Pontryagin Principle. Then, it introduces more recent topics, such as Approximate Dynamic Programming and Neural Networks for the approximate solution of dynamic optimization problems. The proofs are outlined; the details are presented only when they provide useful insights. Both discrete-time and continuous-time optimization are considered. Several applications and case-studies are described and discussed. MATLAB code will be presented for some examples.
Program
Discrete-time N-stage optimization: Dynamic Programming, LQ and LGQ problems, The Riccati Equations, The Kalman Filter, Approximate Dynamic Programming, Neural Networks for approximate solutions to discrete-time N-stage optimization problems. Continuous-time optimization: the Hamilton-Jacobi-Bellman Equation and the Pontryagin Principle. Connection between continuous-time optimization and differential games. Case-studies and examples.
References
- D. P. Bertsekas: “Dynamic Programming and Optimal Control”, vol.I, Athena Scientific, fourth edition, 2017.
- D. P. Bertsekas: “Dynamic Programming and Optimal Control”, vol. II, Athena Scientific, fourth edition, 2012.
- Lecture notes provided by the teacher.
Theory and Practice of Virtual Reality Systems
Duration: 20 hours
Instructor(s): Manuela Chessa - University of Genoa (DIBRIS) - This email address is being protected from spambots. You need JavaScript enabled to view it.This email address is being protected from spambots. You need JavaScript enabled to view it.">
When: 27 February - 3 March 2023
Where: via Dodecaneso 35, Valletta Puggia, DIBRIS
Abstract
The course provides a general introduction to the theory and the development of Virtual Reality Systems. The course will start from some basic aspects of Virtual Reality towards the recent achievements in Mixed Reality. The course will cover the following topics.
- Introduction to Virtual Reality.
- Applications of Virtual Reality: opportunities and issues.
- Devices for Virtual Reality.
- Interaction Techniques in Virtual Reality (hand interaction, walking, …)
- Perception and Interaction in Virtual Reality.
- Introduction to Unity.
- Unity and Unreal
- How to build a VR application
References
- Valentini, I., Ballestin, G., Bassano, C., Solari, F., & Chessa, M. (2020, March). Improving obstacle awareness to enhance interaction in virtual reality. In 2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) (pp. 44-52). IEEE.
- Girau, E., Mura, F., Bazurro, S., Casadio, M., Chirico, M., Solari, F., & Chessa, M. (2019, July). A mixed reality system for the simulation of emergency and first-aid scenarios. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 5690-5695). IEEE.
- Chessa, M., Maiello, G., Klein, L. K., Paulun, V. C., & Solari, F. (2019, March). Grasping objects in immersive Virtual Reality. In 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) (pp. 1749-1754). IEEE.
- Chessa, M., Maiello, G., Borsari, A., & Bex, P. J. (2019). The perceptual quality of the oculus rift for immersive virtual reality. Human–computer interaction, 34(1), 51-82.
- http://www.melslater.me/
- https://wp.cs.ucl.ac.uk/anthonysteed/
- https://unity.com/learn
Introduction to Type Theory: from foundations to practice
Duration: ~24 hours (about 20 hours) 20 hours for lectures + 4 hours for exercises/laboratory
Instructor(s):
Francesco Dagnino – DIBRIS, UniGe – This email address is being protected from spambots. You need JavaScript enabled to view it.
Jacopo Emmenegger – DIMA, UniGe – This email address is being protected from spambots. You need JavaScript enabled to view it.
When: 6-10 March 2023
Where: DIBRIS @ VP, Genova
Abstract
Proof assistants are tools designed to write formal proofs and automatically check their correctness. They are increasingly used in many different domains, from software verification to mathematics. They allow, for instance, to write code correct-by-construction or to formalise complicated mathematical arguments.. Most popular proof assistants, such as Agda, Coq or Lean, implement a constructive logic based on a (dependent) type theory. This means that they are strongly typed functional programming languages where types and programs are seen as logical formulas and proofs, respectively, and then correctness is just ensured by type-checking a program.
In the course, we will study fundamental notions and results on type theories, explaining their connection with logic, and we will experiment formal reasoning in a type theory, using Agda as a concrete system.
Program
The program can be adapted depending on the audience.
- The untyped lambda-calculus as a computational model: terms, reduction, confluence, normalisation
- Constructive reasoning, Intuitionistic Propositional Logic and the BHK interpretation
- Simply typed lambda-calculus, proposition-as-types, proofs-as-terms
- Strong normalisation and consistency
- Introduction to dependent types, quantifiers via dependent sums and products
- Dependent types in Agda, universes
- Inductive types in Agda
- Equality via Identity types
References
[1] J.Y. Girard, Y. Lafont, P. Taylor. Proofs and Types. Cambridge University Press, 1989.
21] M.H.B. Sorensen, P. Urzyczyn. Lectures on the Curry-Howard Isomorphism. Elsevier, 2006.
[3] B. Nordstrom, K. Petersson, J.M. Smith. Programming in Martin-löf’s type theory : an introduction. Clarendon Press, 1990.
[4] M. Hofmann. Syntax and Semantics of Dependent Types. Cambridge University Press, 1997
[5] Agda (https://agda.readthedocs.io/en/v2.6.2/)
Introduction to formal verification: an appetiser
Duration: about 20 hours
Instructor(s): Angelo Ferrando – University of Genova - This email address is being protected from spambots. You need JavaScript enabled to view it.
Giorgio Delzanno - University of Genova
When: 13-17 March 2023
Where: Via Dodecaneso 35, Valletta Puggia, DIBRIS
Abstract
The course provides a general introduction to static formal verification (such as Model Checking), and runtime verification. The course will not focus only on the theoretical foundations of the two approaches, but it will offer practical insights as well. For both methodologies, established tools will be presented and experimented (through laboratories). At the end of the course, a more general overview of recent works on runtime verification will also be reported. This will help the students to have a better understanding of the newest features and challenging applications where such formal technique has been applied.
Program
- Introduction to Formal Methods and Formal Verification
- Introduction to temporal logics (LTL and CTL)
- Introduction to Model Checking
- Practical applications of Model Checking (with tools)
- Laboratory on Model Checking tools
- Introduction to Runtime Verification
- Practical applications of Runtime Verification (with tools)
- Laboratory on Runtime Verification
- Recent study and developments on Runtime Verification (predictive runtime verification, partial monitor, robotics, and so on)
- Process mining and Petri nets
References
- E. Bartocci, Y. Falcone, A. Francalanza, G. Reger, Introduction to runtime verification, in: Lectures on Runtime Verification – Introductory and Advanced Topics, 2018, pp. 1–33.
- Clarke, E.M.: Model checking. In: International Conference on Foundations of Software Technology and Theoretical Computer Science. pp. 54–56. Springer (1997)
- Angelo Ferrando, Louise A. Dennis, Rafael C. Cardoso, Michael Fisher, Davide Ancona, Viviana Mascardi.Toward a Holistic Approach to Verification and Validation of Autonomous Cognitive Systems. ACM Trans. Softw. Eng. Methodol. 30(4): 43:1-43:43 (2021)
- Angelo Ferrando, Rafael C. Cardoso, Michael Fisher, Davide Ancona, Luca Franceschini, Viviana Mascardi. ROSMonitoring: A Runtime Verification Framework for ROS. TAROS 2020: 387-399
- Andreas Bauer, Martin Leucker, Christian Schallhart: Runtime Verification for LTL and TLTL. ACM Trans. Softw. Eng. Methodol. 20(4): 14:1-14:64 (2011)
An Introduction to Model Predictive Control
and Rolling Horizon Optimization
Duration: 20 hours
Instructor: Mauro Gaggero, National Research Council of Italy (CNR), Genova - This email address is being protected from spambots. You need JavaScript enabled to view it.
When: 20-24 Marzo 2023
Where: University of Genoa (classroom to be announced in Via Opera Pia) or Microsoft Teams platform
Abstract
Model predictive control (MPC) and rolling-horizon optimization are optimization and control paradigms that have been widely employed in the literature owing to their ability to exploit information on the future behavior of the system at hand, their capability of dealing with constraints, and the presence of many theoretical results about their properties. From various decades, MPC has been used for process control in chemical plants, and nowadays it is employed for the optimization of many other complex setups such as, for instance, power plants, mechatronic systems, logistics operations, cloud computing applications, and so on. It is still receiving on-going interest from researchers in both the industrial and academic communities. Concerning the academic world, MPC is attractive for both researchers working in the field of Control Systems and Operations Research since it combines several aspects of both disciplines. The course will start from the basic theoretic notions of MPC and rolling-horizon optimization, together with recent developments in design and implementation. Special attention will be devoted to the computational aspects of MPC and to the existing techniques to reduce the overall required effort. An overview of receding-horizon state estimation, a topic strictly related to MPC, will be given as well. Finally, recent applications of MPC and rolling-horizon optimization will be presented, together with details of their software implementation.
Program
- Introduction to discrete-time model predictive control and rolling-horizon optimization
- Model predictive control with constraints
- Model predictive control and stability analysis
- Moving-horizon state estimation
- Real-time implementations of model predictive control
- Examples of applications of model predictive control and rolling-horizon optimization
References
- M. Morari, J.H. Lee, “Model predictive control: past, present and future”, Computers and Chemical Engineering, vol. 23 pp. 667-682, 1999.
- D. Mayne, J. Rawlings, C. Rao, and P. Scokaert, “Constrained model predictive control: stability and optimality,” Automatica, vol. 36, no. 6, pp. 789–814, 2000.
- E.F. Camacho, C. Bordons, “Model Predictive Control”, Series Advanced Textbooks in Control and Signal Processing, Springer, 2004.
- L. Wang, “Model Predictive Control System Design and Implementation Using MATLAB”, Series Advances in Industrial Control, Springer, 2009.
- A. Alessandri, M. Baglietto, G. Battistelli, M. Gaggero, "Moving-horizon state estimation for nonlinear systems using neural networks," IEEE Trans. on Neural Networks, vol. 22, no. 5, pp. 768-780, 2011.
- A. Alessandri, M. Gaggero, F. Tonelli, "Min-max and predictive control for the management of distribution in supply chains," IEEE Trans. on Control Systems Technology, vol. 19, no. 5, pp. 1075-1089, 2011.
- A. Alessandri, C. Cervellera, M. Gaggero, "Nonlinear predictive control of container flows in maritime intermodal terminals," IEEE Trans. on Control Systems Technology, vol. 21, no. 4, pp. 1423-1431, 2013.
- M. Gaggero, L. Caviglione, "Predictive control for energy-aware consolidation in cloud datacenters", IEEE Trans. on Control Systems Technology, vol. 24, no. 2, pp. 461-474, 2016.
- A. Alessandri, M. Gaggero, "Fast moving horizon state estimation for discrete-time systems using single and multi iteration descent methods", IEEE Trans. on Automatic Control, vol. 62, no. 9, pp. 4499-4511, 2017.
- M. Gaggero, L. Caviglione, "Model predictive control for energy-efficient, quality-aware, and secure virtual machine placement", IEEE Trans. on Automation Science and Engineering, vol. 16, no. 1, pp. 420-432, 2019, DOI:10.1109/TASE.2018.2826723.
- M. Gaggero, D. Di Paola, A. Petitti, L. Caviglione, "When time matters: predictive mission planning in cyber-physical scenarios", IEEE Access, vol. 7, no. 1, pp. 11246-11257, 2019, DOI:10.1109/ACCESS.2019.2892310.
Strategic Choices: Games and Team Optimization
Duration: 20 hours
Instructors: Lucia Pusillo - University of Genoa (DIMA) - This email address is being protected from spambots. You need JavaScript enabled to view it.
Marcello Sanguineti - University of Genoa (DIBRIS) - This email address is being protected from spambots. You need JavaScript enabled to view it.
When: 27-31 March 2023
Where: Via Dodecaneso 35
Abstract: Game and Team Theory study strategic interactions among two or more agents, which have to take decisions in order to optimize their objectives. They have various links to disciplines such as Economics, Engineering, Computer Science, Political and Social Sciences, Biology, and Medicine. These links provide incentives for interdisciplinary research and make the role of Game and Team Theory invaluable in a variety of applications. The main goal of this course consists in providing students with the basic mathematical tools to deal with interactive problems and illustrating them via case-studies.
Program
- Non-cooperative games
- Strategic games and extended-form games
- Incomplete-information games
- Well-posedness problems for Nash equilibria
- Repeated games
- Evolutionary stable strategies
- Multiobjective games and solution concepts
- Cooperative TU-games
- Solutions for cooperative games
- Partial cooperative games
- Team optimization with stochastic information structure.
- Examples of applications in contexts such as:
- environment models;
- nonverbal communication & social interactions;
- medicine and biology;
- optimal production;
- telecommunication networks;
- transportation networks.
References
- Course notes/slides.
- A. Dontchev, T. Zolezzi. ''Well-Posed Optimization Problems''. Lecture Notes in Math., vol. 1543. Springer, 1993.
- D. Fudenberg, J. Tirole. ''Game Theory'', MIT Press, 1991
- G. Gnecco, M. Sanguineti. “Team Optimization Problems with Lipschitz Continuous Strategies”, Optimization Letters, vol. 5, pp. 333-346, 2011.
- G. Gnecco, M. Sanguineti. “New Insights into Witsenhausen’s Counterexample”, Optim. Let. 6:1425-1446, 2012.
- G. Gnecco, Y. Hadas, M. Sanguineti, “Some Properties of Transportation Network Cooperative Games". Networks 74:161–173, 2019.
- G. Gnecco, M. Sanguineti, G. Gaggero. “Suboptimal Solutions to Team Optimization Problems with Stochastic Information Structure”. SIAM J. on Optimization 22:212-243, 2012.
- Y. Hadas, G. Gnecco, M. Sanguineti. "An Approach to Transportation Network Analysis ViaTransferable Utility Games". Transportation Res. Part B: Methodological, vol. 105, pp. 120-143, 2017.
- K. Kolykhalova, G. Gnecco, M. Sanguineti, G. Volpe, A. Camurri, “Automated Analysis of the Origin of Movement: An Approach Based on Cooperative Games on Graphs". IEEE Trans. on Human-Machine Systems 50:550-560, 2020.
- H. Peters. ''Game Theory- A Multileveled Approach''. Springer, 2008.
- L. Pusillo. "Evolutionary Stable Strategies and Well Posedness Property", Appl. Math. Sc. 7:363-376, 2013.
- L. Pusillo, S. Tijs. ''E-equilibria for Multicriteria Games ''. In: R. Cressman and P. Cardaliaguet. The Annals of the Int. Society of Dynamic Games (ISDG). vol. 12, pp. 217-228, Birkhauser, 2012.
- R. Zoppoli, M. Sanguineti, G. Gnecco, T. Parisini. “Neural Approximations for Optimal Control and Decision". Springer, Communications and Control Engineering Series. London, 2020.
Network monitoring and inspection
Duration: 20 hours
Instructor(s):
Matteo Repetto
Institute for Applied Mathematics and Information Technologies
National Research Council of Italy (CNR)
This email address is being protected from spambots. You need JavaScript enabled to view it.
When: 27-31 March 2023
Where: Online (Teams) or on site (as requested by students)
Abstract
The Internet is the main carrier for cyber-attacks, so it is not surprising that most detection techniques build on network flow monitoring and packet inspection. There is a huge amount of information that potentially can be gathered from the network, but deep packet inspection at line rate is extremely challenging even in hardware, especially in case of high-speed links (1 Gbps and upward). This course will give a basic understanding of common tools for flow monitoring and packet inspection, with specific emphasis on how to extract custom information that is ever more needed to detect modern attacks. Besides, the eBPF framework provided by the Linux kernel will be introduced as a power mechanism to build efficient, custom and portable inspection and enforcement processes.
Program
- Introduction to network monitoring
- Overview of common network cyber-attacks
- Network protocols for flow monitoring
- Interactive inspection tools: wireshark, tshark, tcpdump for wired/wireless network monitoring
- Passive network monitoring and deep packet inspection: nProbe, PacketBeat, Zeek
- Programmable monitoring: Zeek scripting and eBPF
References
- L. Caviglione, W. Mazurczyk, M. Repetto, A. Schaffhauser, M. Zuppelli. Kernel-level tracing for detecting stegomalware and covert channels in Linux environments. Computer Networks, Volume 191, May 2021. DOI: 10.1016/j.comnet.2021.108010
- M. Repetto, A. Carrega, R. Rapuzzi. An architecture to manage security operations for digital service chains. Future Generation Computer Systems. Volume 115, February 2021, Pages 251-266. DOI: 10.1016/j.future.2020.08.044
- M. Repetto, G. Bruno, J. Yusupov, G. Lamanna, B. Ertl, and A. Carrega. Automating Mitigation of Amplification Attacks in NFV Services. IEEE Transactions on Network and Service Management. Early access. DOI: 10.1109/TNSM.2022.3172880
- M. Zuppelli, M. Repetto, A. Schaffhauser, W. Mazurczyk, L. Caviglione. Code Layering for the Detection of Network Covert Channels in Agentless Systems. IEEE Transactions on Network and Service Management. Early access. DOI: 10.1109/TNSM.2022.3176752
An Introduction to Prolog
Duration: 12 hours
Instructor: Mascardi Viviana, This email address is being protected from spambots. You need JavaScript enabled to view it.
When: April, 3, 4, 5, 2023 (4 hours per day, given in presence and online via Teams)
Where: DIBRIS, Via Dodecaneso 35
Abstract: "In the summer of 1972, Alain Colmerauer and his team in Marseille developed and implemented the first version of the logic programming language Prolog. Together with both earlier and later collaborations with Robert Kowalski and his colleagues in Edinburgh, this work laid the practical and theoretical foundations for the Prolog and logic programming of today. Prolog and its related technologies soon became key tools of symbolic programming and Artificial Intelligence."
This statement is taken from the "The Year of Prolog" web page, http://prologyear.logicprogramming.org/: the 50th anniversary of Prolog has been celebrated in 2022 with scientific and dissemination initiatives all over the world. Keeping the momentum going, we offer a compact introductory course on Prolog, with practical exercises and an overview of the existing and future Prolog applications. In particular, we highlight the potential of Prolog for implementing cognitive intelligent agents and for supporting eXplainable Artificial Intelligence (XAI) thanks to its declarative flavor.
Program:
Prolog syntax
Prolog operational semantics
Extra-logical and meta-logical predicates
Examples
Applications
Future perspectives
References:
The Art of Prolog, second edition
Advanced Programming Techniques
by Leon S. Sterling and Ehud Y. Shapiro
1994
Accelerated Parallel Systems: the GPU and FPGA cases
Duration: 20 hours (five half-days)
Instructors: Antonella Galizia - IMATI-CNR This email address is being protected from spambots. You need JavaScript enabled to view it., Christian Pilato - Politecnico di Milano This email address is being protected from spambots. You need JavaScript enabled to view it.This email address is being protected from spambots. You need JavaScript enabled to view it.">
When: 17-21 April 2023
Where: DIBRIS-UNIGE Via Dodecaneso 35, Genova (online attendance will be possible)
Abstract
With the end of Moore law for sequential computing architectures and the advents of multi and many cores era, managing parallelism is no longer the goal of a restricted community but becomes a need for everybody who is interested in exploiting an adequate fraction of available performance provided by widespread modern computing architectures, including desktop and mobile devices. A computer is nowadays a complex system with heterogeneous computational units including multi cores CPU and many cores accelerators such as Graphic Processing Unit (GPU), Field-Programmable Gate Array (FPGA), or others. The aim of the course is to present the state-of-the-practice on computing systems equipped with accelerated technology; the main focus is on high efficiency, which is of utmost importance but can have different meanings: as for high-performance computing and data center domains, high efficiency mostly relates to performance while in the mobile and IoT space, research communities think about accelerators more from a power/energy perspective. The course considers programming of Complex Heterogeneous Parallel Systems (CHPS) and in particular accelerators as GPU and FPGA, the overall goal and challenge is the portability and performances of software to ensure effectiveness and efficiency of target applications. This edition of the course will discuss two different approaches: the GPGPU based solutions and the hardware specialization of the application on FPGA. In particular, it will be shown, with practical cases, how to design and implement applications able to exploit available computational resources through a suitable selection of programming tools, communications and domain-oriented libraries, and design and implementation strategies. At this regards the course will include a hands-on part that the student may dedicate to a general case study or to a personalized case depending on specific interests.
Program
- Introduction to complex heterogeneous parallel systems (CHPS): from personal computer to High Performance clusters and GPUs
- A coarse grain analysis of performances and programming issues for CHPS, including memory hierarchies and data movement; computational units and different levels-types of parallelism; communications issues
- Overview of GPGPU oriented parallel processing libraries, languages and tools. This will include CUDA, OpenACC and OpenCL insights, GPU-accelerated libraries
- Overview of CUDA advanced programming features will be provided as well as examples of high software ecosystem such HPC solutions for Python, accelerated libraries, tools for profiling and debugging, and high-level synthesis tools for automatic hardware customization.
- Designing parallel and/or heterogeneous applications and practical experiences: hands on case studies selected from linear algebra, computational geometry, Monte Carlo simulation, and data science applications. Individual case study on topics proposed by students will be encouraged (8hours)
References
Slides of the course will be provided to students
Ricca - Leotta school May 2023
Mobile Security
Duration: 20 hours (5 half-days)
Instructors(s): Alessio Merlo – University of Genova This email address is being protected from spambots. You need JavaScript enabled to view it. Luca Verderame – University of Genova This email address is being protected from spambots. You need JavaScript enabled to view it.This email address is being protected from spambots. You need JavaScript enabled to view it.">
When: 22-26 May 2023
Where: online via Teams or in presence at DIBRIS – Valletta Puggia, Via Dodecaneso 35
Abstract: The course provides an overview of the main topics related to the security of mobile devices and applications. The course offers an insight into the leading mobile operating systems (i.e., Android and iOS) and their security issues. Moreover, the course provides a discussion on emerging mobile security technologies (e.g., Host-Based Card Emulation, and Trusted Execution Environment), security threats, and possible countermeasures. The second part of the course will cover the security of Mobile Applications, with a particular focus of state-of-the-art frameworks and methodologies for the vulnerability assessment of Android applications. Finally, the course will provide specific hands-on sessions with tools and techniques for the vulnerability assessment of Android applications.
Program:
- Introduction to mobile devices: history, features, and evolution;
- Architecture and security features of the principal mobile OSes (Android, iOS);
- Emerging mobile security technologies, security threats, and countermeasures;
- OWASP for Mobile Application Security Analysis;
- Reverse Engineering of Android Apps and Reversing Countermeasures;
- Static and Dynamic analysis of Android Apps.
During the hands-on sessions, students will get acquainted with a number of static and dynamic analysis tools, including
- ObfuscAPK - https://github.com/ClaudiuGeorgiu/Obfuscapk
- Apktool - https://ibotpeaches.github.io/Apktool/
- Jadx - https://github.com/skylot/jadx
- Inspeckage - https://github.com/ac-pm/Inspeckage
- Approver - https://approver.talos-sec.com
- Charles Proxy - https://www.charlesproxy.com
References:
- Romdhana, A., Merlo, A., Ceccato, M., & Tonella, P. (2022). Deep reinforcement learning for black-box testing of android apps. ACM Transactions on Software Engineering and Methodology.
- Merlo, A., Ruggia, A., Sciolla, L., & Verderame, L. (2021). ARMAND: Anti-repackaging through multi-pattern anti-tampering based on native detection. Pervasive and Mobile Computing, 76, 101443.
- Mayrhofer, R., Stoep, J. V., Brubaker, C., & Kralevich, N. (2021). The android platform security model. ACM Transactions on Privacy and Security (TOPS), 24(3), 1-35.
- OWASP Mobile Security Project. Mobile Security Testing Guide (MSTG) and Mobile Application Security Verification Standard (MASVS) https://owasp.org/www-project-mobile-app-security/;
Introduction to High Performance Computing
Duration: 20 hours
Instructor: Daniele D’Agostino – DIBRIS Unige
When: 29 May - 2 June 2023
Where: Via Dodecaneso
Abstract For most scientists the abstract fact of the existence of an algorithm solving a problem is enough, while its efficient implementation in terms of exploitation of the available computational capabilities is mostly disregarded. But with the end of Moore law for sequential computing architectures and the advents of multi and many cores era, managing parallelism is no longer the goal of a restricted ICT community, it becomes a need for everybody who is interested in exploiting an adequate fraction of available performance provided by widespread modern computing architectures. The aim of the course is to provide a glance of the different aspects involved in efficient and effective programming of current heterogeneous computing systems equipped with manycore x86 architectures and accelerators, in particular graphics cards (GPUs). Therefore, it conveys the required knowledge to develop a thorough understanding of the interactions between software and hardware at the core, socket, node and cluster level. In particular it will be presented, with practical cases, how the design and implementation of programs can exploit available computational resources through a suitable selection of programming paradigms, compiling and profiling tools. The course includes a hands-on part that the student may dedicate to a general case study or to a personalized case depending on specific interests.
The programming language will be C/C++. The translation in Fortran is straightforward.
Program
- Introduction to complex heterogeneous parallel systems: from workstations to High Performance clusters and supercomputers.
- The von Neumann architecture then versus now, features and bottlenecks.
- Introduction to parallel architectures.
- Single Instruction Multiple Data (SIMD)
- Single Program Multiple Data (SPMD)
- The roofline performance model.
- Profiling and performance analysis
- The compiler, one of the most important software tools for HPC.
- Intel oneAPI
- Nvidia HPC SDK
- Optimal use of parallel resources – on the basis of students’ interests
- Parallel programming for x86 nodes: OpenMP and MPI
- Parallel programming for GPUs: openACC and CUDA
- Parallel programming for HPC systems: MPI+X
- Designing parallel applications and practical experiences.
References
- Slides and references will be provided to students
Theory and Practice of Runtime Monitoring
Duration: about 20 hours
Instructor(s): Davide Ancona - University of Genoa (DIBRIS) - This email address is being protected from spambots. You need JavaScript enabled to view it.,
Angelo Ferrando - University of Genoa (DIBRIS) - This email address is being protected from spambots. You need JavaScript enabled to view it.
When: 5 - 9 June 2023
Where: via Dodecaneso 35, Valletta Puggia, DIBRIS
Abstract
The course provides a general introduction to Runtime Monitoring and Verification (RM&V), and the theoretical and practical aspects of RML (Runtime Monitoring Language), a system agnostic domain specific language for RM&V. Use cases will be considered in the context of distributed and Internet of Things systems with Node.js/Jalangi2 and Node-RED and robotic systems based on ROS.
- An introduction to RM&V.
- Theory and practice of RML, a domain specific language for RM&V.
- RM&V of Node.js applications with RML and Jalangi2.
- RM&V of IoT systems with RML and Node-RED.
- RM&V of Robotic systems based on ROS.
- Hands-on labs with RML, Jalangi2, Node.js and Node-RED.
References
- Davide Ancona, Luca Franceschini, Angelo Ferrando, Viviana Mascardi. RML: Theory and practice of a domain specific language for runtime verification. Science of Computer Programming, 205:102610 (2021).
- Angelo Ferrando, Louise A. Dennis, Rafael C. Cardoso, Michael Fisher, Davide Ancona, Viviana Mascardi.Toward a Holistic Approach to Verification and Validation of Autonomous Cognitive Systems. ACM Trans. Softw. Eng. Methodol. 30(4): 43:1-43:43 (2021)
- Angelo Ferrando, Rafael C. Cardoso, Michael Fisher, Davide Ancona, Luca Franceschini, Viviana Mascardi. ROSMonitoring: A Runtime Verification Framework for ROS. TAROS 2020: 387-399
- Luca Franceschini, RML: Runtime Monitoring Language, Ph.D. thesis, DIBRIS - University of Genova, URL http://hdl.handle.net/11567/1001856, March 2020.
- Davide Ancona, Francesco Dagnino, Luca Franceschini. A formalism for specification of Java API interfaces. ISSTA/ECOOP Workshops 2018: 24-26
- Davide Ancona, Luca Franceschini, Giorgio Delzanno, Maurizio Leotta, Marina Ribaudo, Filippo Ricca. Towards Runtime Monitoring of Node.js and Its Application to the Internet of Things. ALP4IoT@iFM 2017: 27-42
- Davide Ancona, Angelo Ferrando, Viviana Mascardi. Comparing Trace Expressions and Linear Temporal Logic for Runtime Verification. Theory and Practice of Formal Methods 2016: 47-64
- Angelo Ferrando, Davide Ancona, Viviana Mascardi. Decentralizing MAS Monitoring with DecAMon. AAMAS 2017: 239-248
- Davide Ancona, Angelo Ferrando, Viviana Mascardi. Parametric Runtime Verification of Multiagent Systems. AAMAS 2017: 1457-1459
- Y. Falcone, S. Krstic, G. Reger, D. Traytel, A taxonomy for classifying runtime verification tools, in: Runtime Verification – 18th International Conference, Proceedings, RV 2018, pp. 241–262.
- E. Bartocci, Y. Falcone, A. Francalanza, G. Reger, Introduction to runtime verification, in: Lectures on Runtime Verification – Introductory and Advanced Topics, 2018, pp. 1–33.
- Yliès Falcone, Klaus Havelund, Giles Reger. A Tutorial on Runtime Verification. Engineering Dependable Software Systems 2013: 141-175
- Martin Leucker, Christian Schallhart. A brief account of runtime verification. J. Log. Algebr. Program. 78(5): 293-303 (2009)
- RML: https://rmlatdibris.github.io
- Node.js: https://nodejs.org/en
- Node-RED: https://nodered.org
- Jalangi2: https://github.com/Samsung/jalangi2
Computer Vision Crash Course
Duration: 20 hours
Instructor(s):
Francesca Odone and Nicoletta Noceti
MaLGa DIBRIS, Università degli Studi di Genova
{francesca.odone, nicoletta.noceti,}@unige.it
When: 5 -9 June 2023
Where: DIBRIS-UNIGE Via Dodecaneso 35, Genova
Abstract
Visual perception, as a key element of Artificial Intelligence, allows us to build smart systems sensitive to surrounding environments, interactive robots, video-cameras with real time algorithms running on board. With similar algorithms, our smart phones can log us in by recognizing our face, read text automatically, improve the quality of the photos we shoot. At the core of these applications are computer vision models, often boosted by machine learning algorithms.
This crash course is conceived as a complement to the “Deep Learning: Hands on introduction” course (henceforth DL) although it can be taken independently.
It covers the basic principles of computer vision and visual perception in artificial agents, including theoretical classes, application examples, hand-on activities.
Within CVCC, we present elements of classical computer vision (introduction to image processing, feature detection, depth estimation, motion analysis).
At the same time, by borrowing from DL, we also present deep learning approaches to computer vision problems such as image classification, detection, and semantic segmentation.
Core CVCC Program (for those attending the CVCC course only)
Integrated DL and CVCC program
References
Slides and readings will be provided.
Some reference books:
- E. Trucco, A. Verri Introductory Techniques for 3-D Computer Vision Prenctice Hall 1998
- R. Szeliski Computer Vision: Algorithms and Applications https://szeliski.org/Book/
- I. Goodfellow, Y. Bengio, A. Courville Deep Learning https://www.deeplearningbook.org/
Topics in Modern Machine Learning (ModML)
Duration
20 hours
Instructor(s)
Lorenzo Rosasco – DIBRIS – This email address is being protected from spambots. You need JavaScript enabled to view it.This email address is being protected from spambots. You need JavaScript enabled to view it.">
Giovanni Alberti – DIMA – This email address is being protected from spambots. You need JavaScript enabled to view it.
Simone Di Marino – DMA - This email address is being protected from spambots. You need JavaScript enabled to view it.
When: 19-23 June 2023
Where DIBRIS, Via Dodecaneso 35
Abstract
This is an advanced machine learning course covering some of the topics of interest in modern machine learning. After a 6-hour boot camp on the first day (on statistical learning, machine learning models and optimization for machine learning), the rest of the week will be dedicated to introducing modern topics including, for example, interpolation and overparameterization, implicit regularization, optimal transport for machine learning, machine learning for inverse problems, fairness in machine learning and reinforcement learning. Each presentation, held in the morning, will be introductory and self-contained, with an associated practical session in the afternoon. The last day will be dedicated to a workshop with invited speakers.
Program The detailed program will be provided later.
References Ad hoc references will be given for each topic.
Effective habits and skills for successful young scientists
Teacher: Fabio Roli
Duration: 20 hours (5 half-days)
When: June 26-30 2023
Where: online on MS Teams
Curriculum: Cross-curricula course
Exam: written assessments with open-ended questions
Abstract:
Although tons of books on effective habits and soft skills have been published, they have not been thought for scientists, and, therefore, issues that are relevant for them are not easily available. This short course aims to collect spread ideas and place them in a coherent framework useful for young scientists and provide a small tactical guide for scientists at the first stages of their career. First, I review the main concepts of Steve Covey's personal and time management paradigm, the inspirational speeches of the late Professor Randy Pausch, and the paradigm of atomic habits of James Clear, and discuss their utility for daily activity of a young scientist. Then, I focus on a few practical skills, namely, on how to write a great paper and give a great talk. I try to convey the message that succeeding in science and technology requires skills and habits beyond the pure intelligence and intellectual abilities, and that good habits and skills of personal and time management are extremely important for young scientists.
Program:
- Basic concepts of theory of habits. Effective habits for young scientists.
- Basis concepts of personal and time management. Effective personal and time management for young scientists.
- Survival skills in the game of science. Know yourself: match your goals to your character and talents.
- How to write a great paper.
- How to give a great talk.
References:
- S. Covey, The 7 Habits of Highly Effective People, 2020
- J. Clear, Atomic habits, 2018
- F. Rosei, T. Johnston, Survival skills for scientists, 2006
- F. Roli, Personal and time management for young scientists, tutorial at the International Conference on Machine Learning and Cybernetics, 2013
- R. Hamming, You and your research, 1986
- U. Alon, How to choose a good scientific problem, Molecular Cell, 2009.
- D. A. Patterson, How to have a bad career in research, Talks at Google, 2016
Adversarial Machine Learning
Teachers: Fabio Roli and Luca Demetrio
Duration: 12 hours (3 half-days)
When: July 3-5 2023
Where: online on MS Teams
Curriculum: Cybersecurity and Reliable AI
Exam: 2 written assessments (one with multiple choice questions, one hands-on assessment using the SecML software library, https://secml.readthedocs.io/en/v0.15/ )
Abstract:
Today machine-learning algorithms are used for many real-world applications, including image recognition, spam filtering, malware detection, biometric recognition. In these applications, the learning algorithm can have to face intelligent and adaptive attackers who can carefully manipulate data to purposely subvert the learning process. As machine learning algorithms have not been originally designed under such premises, they have been shown to be vulnerable to well-crafted attacks, including test-time evasion and training-time poisoning attacks (also known as adversarial examples). In particular, the security of cloud-based machine-learning services has been questioned through the careful construction of adversarial queries that can reveal confidential information on the machine-learning service and its users. This course aims to introduce the fundamentals of the security of machine learning, the related field of adversarial machine learning, and some techniques to assess the vulnerability of machine-learning algorithms and to protect them from adversarial attacks. We report application examples including object recognition in images, biometric identity recognition, spam and malware detection, with hands-on on attacks against machine learning and defences of machine-learning algorithms using the SecML software library, https://secml.readthedocs.io/en/v0.15/.
Program:
- Introduction to adversarial machine learning: introduction by practical examples from computer vision, biometrics, spam, malware detection.
- Design of learning-based pattern classifiers in adversarial environments. Modelling adversarial tasks. The two-player model (the attacker and the classifier). Levels of reciprocal knowledge of the two players (perfect knowledge, limited knowledge, knowledge by queries and feedback). The concepts of security by design and security by obscurity
- System design: vulnerability assessment and defense strategies. Attack models against machine learning. Vulnerability assessment by performance evaluation. Taxonomy of possible defense strategies.
- Hands-on classes on attacks and defences of machine-learning algorithms using the SecML open-source Python library for the security evaluation of machine learning algorithms (https://secml.readthedocs.io/en/v0.15/ ).
- Summary and outlook. Current state of this research field and future perspectives
References:
- B., Battista, F. Roli. "Wild patterns: Ten years after the rise of adversarial machine learning." Pattern Recognition 84 (2018): 317-331.
- B. Biggio, F.Roli, Wild Patterns, Half-day Tutorial on Adversarial Machine Learning: https://www.pluribus-one.it/research/sec-ml/wild-patterns
- Biggio, B., Corona, I., Maiorca, D., Nelson, B., Srndic, N., Laskov, P., Giacinto, G., Roli, F. Evasion attacks against machine learning at test time. ECML-PKDD, 2013.
- Biggio, B., Fumera, G., Roli, F. Security evaluation of pattern classifiers under attack. IEEE Trans. Knowl. Data Eng., 26 (4):984–996, 2014.
Trustworthy Artificial Intelligence
Duration: 20 hours
Instructor(s): Luca Oneto – UNIGE – This email address is being protected from spambots. You need JavaScript enabled to view it.
When: from Monday 10th of July 2023 to Friday 14th of July 2023 from 8:00 to 12:00 CEST
Where: TBD
Abstract: It has been argued that Artificial Intelligence (AI) is experiencing a fast process of commodification. This characterization is of interest for big IT companies, but it correctly reflects the current industrialization of AI. This phenomenon means that AI systems and products are reaching the society at large and, therefore, that societal issues related to the use of AI and Machine Learning (ML) cannot be ignored any longer. Designing ML models from this human-centered perspective means incorporating human-relevant requirements such as reliability, fairness, privacy, and interpretability, but also considering broad societal issues such as ethics and legislation. These are essential aspects to foster the acceptance of ML-based technologies, as well as to be able to comply with an evolving legislation concerning the impact of digital technologies on ethically and privacy sensitive matters.
Program
- Trustworthy AI;
- Reliable AI: Sensitivity Analysis, Robustness, Non-Regressivity, and Adversarial Machine Learning;
- Fair AI: from Pre-, In-, and Post-Processing Models to Learn Fair Representations;
- Private AI: Anonymization, Federated Learning, Differential Privacy, Homomorphic Encryption;
- Interpretable/Explainable AI: making models more understandable.
References
- L. Oneto, et al. Towards learning trustworthily, automatically, and with guarantees on graphs: an overview. Neurocomputing, 2022
- Winfield, A. F. et al. "Machine ethics: the design and governance of ethical AI and autonomous systems." Proceedings of the IEEE 107.3 (2019): 509-517.
- Floridi, L. "Establishing the rules for building trustworthy AI." Nature Machine Intelligence 1.6 (2019): 261-262.
- L. Oneto and S. Chiappa. Fairness in machine learning. Recent Trends in Learning From Data. Springer, 2020
- Biggio, B. and Roli F. "Wild patterns: Ten years after the rise of adversarial machine learning." Pattern Recognition 84 (2018): 317-331.
- Guidotti, R. et al. "A survey of methods for explaining black box models." ACM computing surveys (CSUR) 51.5 (2018): 1-42.
- Liu, B. et al. "When machine learning meets privacy: A survey and outlook." ACM Computing Surveys (CSUR) 54.2 (2021): 1-36.
Information Hiding
Duration: 20 hours (5 half-days)
Instructor:
Luca Caviglione
Institute for Applied Mathematics and Information Technologies
National Research Council of Italy (CNR)
This email address is being protected from spambots. You need JavaScript enabled to view it.
When: 17-21 Jul 2023
Where: preferred venue is via Skype or Microsoft Teams to reach a wide audience. Otherwise, Via Dodecaneso (according to post-pandemic rules).
Abstract:
Information hiding techniques are increasingly used in investigative journalism to protect the identity of sources or by malware to hide its existence and communication attempts. Therefore, understanding how information hiding can be used to empower privacy of users or endow malicious software with the ability of staying "under the radar" are essential to fully assess the modern cybersecurity panorama.
In this perspective, the course introduces the use of information hiding in modern threats and privacy-enhancing architectures with emphasis on two different research areas, specifically: i) techniques for creating network covert channels for communicating with a remote command & control facility, exfiltrate sensitive information and or enforce privacy ii) how to create and detect a covert channel implementing an abusive local path between two colluding applications to bypass the security framework of mobile devices.
To give a comprehensive overview on information hiding and steganography, the course will also cover the use of information hiding and steganographic techniques for watermarking purposes. For instance, it will showcase the main mechanisms for watermarking images, sounds and network flows for management, retrieval, metadating, authentication and copyright enforcement. The course will also discuss possible countermeasures or mitigation methodologies for facing the risks of the increasing amount of steganographic threats observed in the wild.
Program:
Module 1: Course introduction and a general view on information hiding.
Module 2: Information hiding as a cybersecurity threat: malware and colluding applications.
Module 3: Network covert channels (including air-gapped covert channels).
Module 4: Information hiding for watermarking, privacy enhancing, and metadating.
Module 5: Countermeasures (e.g., detecting obfuscated malware or removing ambiguities in protocols).
References:
[1] W. Mazurczyk, L. Caviglione, “Steganography in Modern Smartphones and Mitigation Techniques”, IEEE Communications Surveys & Tutorials, IEEE, Vol. 17, No.1, First Quarter 2015, pp. 334 - 357.
[2] W. Mazurczyk, L. Caviglione, Information Hiding as a Challenge for Malware Detection, IEEE Security & Privacy, Vol. 13, No. 2, pp. 89-93, Mar.-Apr. 2015.
[3] L. Caviglione, M. Podolski, W. Mazurczyk, M. Ianigro, “Covert Channels in Personal Cloud Storage Services: the case of Dropbox”, IEEE Transactions on Industrial Informatics, IEEE, Vol. 13, No. 4, pp. 1921 - 1931, August 2017.
[4] L. Caviglione, M. Gaggero, J.-F. Lalande, W. Mazurczyk, M. Urbanski, “Seeing the Unseen: Revealing Mobile Malware Hidden Communications via Energy Consumption and Artificial Intelligence”, IEEE Transactions on Information Forensics & Security, IEEE, Vol. 11, No. 4, pp. 799 – 810, April 2016.
[5] W. Mazurczyk, L. Caviglione, “Cyber Reconnaissance Techniques”, Communications of the ACM, Vol. 64, No. 3, pp. 86-95, March 2021.
[6] L. Caviglione, W. Mazurczyk, “Never Mind the Malware, Here’s the Stegomalware”, IEEE Security & Privacy, Vol. 20, No. 5, pp. 101-106, Sept.-Oct. 2022.
[7] Steg-in-the-wild (https://github.com/lucacav/steg-in-the-wild): a curated list of attacks observed in the wild taking advantage of steganographic or information-hiding-capable techniques.
Candidates admitted to the online interviews scheduled from July 26 to July 29, 2022
Admitted candidates will be contacted by email for instructions on the next step of the admission procedure.
Open Positions in the PhD Program in Computer Science and Systems Engineering (CSSE)
Application deadline: extended to July 6, 2022 at 12:00 (CET)
Deadline for obtaining the master degree: extended to October 21, 2022
For more details visit the Phd website of our University
Computer Science
(*) 4 grants funded by Università degli Studi di Genova, the annual gross amount of the grant, including social security expenses to be paid by the recipient, is € 16.500,00.
(*) 1 grant funded within D.M. 351/2022 (Azione Dottorati per la Pubblica Amministrazione), under condition to the approval of Ministerial funding; the annual gross amount of the grant, including social security expenses to be paid by the recipient, is € 16.500,00.
(*) 8 grants funded within D.M. 352/2022 (cofunded by 1) Esaote, 2) Aitek, 3) Gter, 4) M3S Srl, 5) PSA Genoa Investments, 6) Teec). 7-8) Leonardo, under condition to the approval of Ministerial funding; the annual gross amount of the grant, including social security expenses to be paid by the recipient, is € 16.500,00.
Systems Engineeering
(*) 2 grants funded by Università degli Studi di Genova, the annual gross amount of the grant, including social security expenses to be paid by the recipient, is € 16.500,00.
(*) 6 grants funded within D.M. 352/2022 (cofunded by 1) Aitek, 2) Decathlon, 3) PSA Genoa Investments, 4) Rulex Innovation Lab, 5) MyPass, 6) Tema srl, Territorio, Mobilità e Ambiente), under condition to the approval of Ministerial funding; the annual gross amount of the grant, including social security expenses to be paid by the recipient, is € 16.500,00.
Prospective applicants are encouraged to contact the reference person for the theme (see the Themes page) they are interested in.
The complete list of Open PhD position is available here positions@Unige:
Application Form
A necessary requirement for admission is that you have a University degree at Master level, or you expect to obtain it by
September 19, 2022 ***Extended to October 21, 2022***
If you have a foreign degree (ie you did not graduate in Italy) your application your follow an ad hoc procedure to have your degree recognised as equivalent toan Italian degree.
General Information and application forms are available at the URL:
- https://unige.it/usg/it/dottorati-di-ricerca (Italian)
- https://unige.it/en/students/phd-programmes (English)
See on-line help for instructions (you will need to fill the form with your personal data and to specify the PhD program
you are applying for (Computer Science and Systems Engineering) and the curriculum).
You will need to upload a number of documents (in pdf format):
- A valid photo ID (both sides and all pages).
- A CV that clearly indicates your prior research experience (this includes e.g. project work, publications, teaching experience, title and short summary of your Master’s thesis).
- A research project consistent with the research theme that you selected (5/6 pages). Guidelines to write a research project proposal are available here.
- The transcript of exams with grades.
Each canditate should provide 1 to 3 reference letters to support the application.
You must not upload reference letters. They must be sent directly by the writer to the PhD coordinator (see below).
Important notice for non local candidates
For non-local candidates (i.e., not known to faculty members at DIBRIS) it is particularly important to secure reference letters from well-established researchers that can provide a reliable assessment of the candidate's abilities.
Reference Letters
The reference letters must be sent by the writer of the letter to the following email addresses, before the submission deadline
- Computer Science: phd.compsci at dibris.unige.it (replace at with @)
- Systems Engineering: phd.syseng at dibris.unige.it (replace at with @)
A template may be found in the Template for reference letters.
Selection process
A Selection Committee (COMMISSIONE) evaluates background knowledge and research potential of the candidates, based on the information submitted with their application (TITOLI) and based on a technical/motivational INTERVIEW. At the end the Committee produces a ranked list (GRADUATORIA) of candidates sufficiently qualified and trained to have a reasonable expectation of successfully completing the graduate program.
The ranking is primarily based on a combination of the following criteria:
- Quality of previous undergraduate/graduate workStrength of reference letter
- Statements in the applicant's research proposal
- Other evidence of graduate potential
- Availability of an advisor in the research area selected by the applicant
- Availability of positions in the PhD program
CONCORSO PER TITOLI E COLLOQUIO
CORSO DI DOTTORATO INFORMATICA E INGEGNERIA DEI SISTEMI / COMPUTER SCIENCE AND SYSTEMS ENGINEERING
UNIVERSITÀ DEGLI STUDI DI GENOVA
CURRICULUM INGEGNERIA DEI SISTEMI/SYSTEMS ENGINEERING (CODICE 9271)
List of candidates admitted to the PhD Program in Systems Engineering (July 30, 2022)
CASELLA VIRGINIA
HOXHA REXHINA
ZAHMOUN SAID
JAFARI MOHAMMAD JAVAD
IMPORTANT NOTICE FOR THE ADMITTED CANDIDATES
The official list of candidates who have been admitted to the doctoral courses will be published before September 12, 2022
in the PhD site of the University of Genova: https://unige.it/en/usg/en/phd-programmes
The enrollment will stay open from September 13 to September 19, 2022 in the website
https://servizionline.unige.it/studenti/post-laurea/confermaPL
The deadline to acquire the Master Degree is October 21, 2022
The President of the Committee
Prof. Roberto Sacile
List of candidates admitted to the second round (interview)
|
ABBASI |
BURHAN UD DIN |
|
AKKARY |
NABIL |
|
BENAHMED |
OSSAMA |
|
CASELLA |
VIRGINIA |
|
HOXHA |
REXHINA |
|
JAFARI |
MOHAMMAD JAVAD |
|
TUCKER |
SWATARA KAY |
|
ZAHMOUN |
SAID |
Selected candidates will be contacted by email to fix a (skype/in person) appointment for the interview (on July 26, starting at 14.00 CET).
The President of the Committee
Prof. Roberto Sacile
CONCORSO PER TITOLI E COLLOQUIO
CORSO DI DOTTORATO INFORMATICA E INGEGNERIA DEI SISTEMI / COMPUTER SCIENCE AND SYSTEMS ENGINEERING
CURRICULUM INFORMATICA/COMPUTER SCIENCE (CODICE 9270)
XXXVIII CICLO, AVENTE SEDE AMMINISTRATIVA PRESSO L’UNIVERSITÀ DEGLI STUDI DI GENOVA, INDETTO CON DECRETO RETTORALE N. 2421 DEL 1 GIUGNO 2022 E SS.MM.II.
CANDIDATES ADMITTED TO THE PHD PROGRAM IN COMPUTER SCIENCE 2022-25
IMPORTANT NOTICE FOR THE ADMITTED CANDIDATES:
The official list of candidates who have been admitted to the doctoral courses will be published on September 5, 2022
in the PhD site of the University of Genova: https://unige.it/en/usg/en/phd-programmes
Enrollment will stay open from September 13 to September 19, 2022 in the website
https://servizionline.unige.it/studenti/post-laurea/confermaPL
The deadline to acquire the Master Degree is October 21, 2022.
4 BORSE MUR (4 SCHOLARSHIPS FUNDED BY M.U.R.)
|
4333528 |
Dott.ssa |
PIZZO |
MARIANNA |
|
4345255 |
Dott. |
DAPUETO |
JACOPO |
|
4474867 |
Dott. |
SICHETTI |
FEDERICO |
|
4851321 |
Dott. |
JANPIH |
ZIAD |
|
4496922 |
Dott. |
GATTI |
ANDREA |
Gatti is eligible only in case of renunciation of Pizzo, Dapueto, Sichetti and Janpih.
1 BORSA PNRR 351 su tema legato a Pubblica Amministrazione
(1 PNRR 351 SCHOLARSHIP on topics related to Public Administration)
|
4493864 |
Dott. |
CARUSO |
SIMONE |
|
4229348 |
Dott.ssa |
FERRANDO |
SILVIA |
|
5499979 |
Dott. |
NAHEED |
SAQIB |
Eerrando is eligible only in case of renunciation of Caruso.
Naheed is eligible only in case of renunciation of Caruso and Ferrando.
1 BORSA 352 su tema AITEK (1 PNRR 352 SCHOLARSHIP cofunded by AITEK)
|
5180550 |
Dott. |
KHAN |
DADAN |
1 BORSA 352 su tema ESAOTE (1 PNRR 352 SCHOLARSHIP cofunded by ESAOTE)
|
5555563 |
Dott.ssa |
SALEEM |
MARVA |
1 BORSA 352 su tema GTER (1 PNRR 352 SCHOLARSHIP cofunded by GTER)
|
5059661 |
Dott. |
KURSHAKOV |
GEORGII |
1 BORSA 352 su tema Leonardo “BigData and High Performance Computing”
(1 PNRR 352 SCHOLARSHIP cofunded by Leonardo Company)
|
5567157 |
Dott. |
DHAR |
JOY |
1 BORSA 352 su tema M3S (1 PNRR 352 SCHOLARSHIP cofunded by M3S)
|
4342472 |
Dott. |
AVOLA |
STEFANO |
1 BORSA 352 su tema TEEC (1 PNRR 352 SCHOLARSHIP cofunded by TEEC)
|
4496922 |
Dott. |
GATTI |
ANDREA |
The Admission Committee
CONCORSO PER TITOLI E COLLOQUIO
CORSO DI DOTTORATO INFORMATICA E INGEGNERIA DEI SISTEMI / COMPUTER SCIENCE AND SYSTEMS ENGINEERING
CURRICULUM INFORMATICA/COMPUTER SCIENCE (CODICE 9270)
XXXVIII CICLO, AVENTE SEDE AMMINISTRATIVA PRESSO L’UNIVERSITÀ DEGLI STUDI DI GENOVA, INDETTO CON DECRETO RETTORALE N. 2421 DEL 1 GIUGNO 2022 E SS.MM.II.
List of candidates admitted to the second round (interview)
| 5495546 | AHMED | AWAIS |
| 5496680 | ALI | WARIS |
| 4342472 | AVOLA | STEFANO |
| 4493864 | CARUSO | SIMONE |
| 4240062 | CASELLA | VIRGINIA |
| 4345255 | DAPUETO | JACOPO |
| 5567157 | DHAR | JOY |
| 5513181 | FAIZAN | RAO |
| 4229348 | FERRANDO | SILVIA |
| 4496922 | GATTI | ANDREA |
| 5167702 | HASSANNATAJJOLOUDARI | JAVAD |
| 5540789 | HOSSEINALIBEIKI | HOSSEIN |
| 4851321 | JANPIH | ZIAD |
| 5180550 | KHAN | DADAN |
| 5059661 | KURSHAKOV | GEORGII |
| 5386921 | NADIM | MUHAMMAD AMIN |
| 5499979 | NAHEED | SAQIB |
| 5544673 | NOORUDDIN | NOORUDDIN |
| 4333528 | PIZZO | MARIANNA |
| 5543759 | QAMAR UN NISA | QAMAR UN NISA |
| 5383104 | RANA | TANZEEL SULTAN |
| 5555882 | REZA | TAHERI |
| 5549272 | REZAEI | HADIS |
| 5555563 | SALEEM | MARVA |
| 5361380 | SHAH | SAHAR |
| 4474867 | SICHETTI | FEDERICO |
| 5191307 | SIDDEEQ | SHAHBAZ |
Selected candidates will be contacted by email to fix a (skype/in person) appointment for the interview (from July 26 to July 29)
The President of the Committee
Prof. Giorgio Delzanno
PhD Program in Computer Science and Systems Engineering
Research Projects Proposals 2022 (XXXVIII Cycle)
Title: Ethic-by-Design Query Processing / Responsible Query Processing
Proposer: Barbara Catania
Research area: Data Science and Engineering
Curriculum: Computer Science
Description: Nowadays, large-scale technologies for the management and the analysis of big data have a relevant and positive impact: they can improve people’s lives, accelerate scientific discovery and innovation, and bring about positive societal change. At the same time, it becomes increasingly important to understand the nature of these impacts at the social level and to take responsibility for them, especially when they deal with human-related data.
Properties like diversity, serendipity, fairness, or coverage have been recently studied at the level of some specific data processing systems, like recommendation systems, as additional dimensions that complement basic accuracy measures with the goal of improving user satisfaction [2].
Due to the above-mentioned social relevance and to the fact that ethical need to take responsibility is also made mandatory by the recent General Data Protection Regulation of the European Union [GDPR16], nowadays the development of solutions satisfying - by design - non-discriminating requirements is currently one of the main challenges in data processing and is becoming increasingly crucial when dealing with any data processing stage, including data management stages [1, 3, 4].
Based on our past experience in advanced query processing for both stored and streaming data, the aim of the proposed research is to design, implement, and evaluate ad hoc query processing techniques for stored and stream data to automatically enforce specific beyond-accuracy properties, with a special reference to fairness-related constraints. The focus will be on rewriting approaches, to guarantee the transparency of the process.
Link to the group or personal webpage: dama.dibris.unige.it
References:
[1] S Abiteboul et Al. Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151). Dagstuhl Manifestos 7(1): 1-29 (2018)
[2] M Kaminskas, D Bridge. Diversity, Serendipity, Novelty, and Coverage: A Survey and Empirical Analysis of Beyond-Accuracy Objectives in Recommender Systems. TiiS 7(1): 2:1-2:42 (2017)
[3] J Stoyanovich, B Howe, H.V. Jagadish. Special Session: A Technical Research Agenda in Data Ethics and Responsible Data Management. SIGMOD Conf. 2018: 1635-1636 (2018)
[4] J Stoyanovich, K Yang, H.V. Jagadish. Online Set Selection with Fairness and Diversity Constraints. EDBT 2018: 241-252 (2018)
Title: Interactive environments in extended reality (XR)
Supervisor(s): Manuela Chessa and Fabio Solari
Keywords: human-computer interaction HCI, virtual reality VR, extended reality XR
Curriculum: Computer Science
Abstract: Extended Reality (XR) and Mixed Reality (MR) are the new frontiers of human-computer interaction (HCI), combining the potentiality of immersive Virtual Reality (VR) with the real physical world. Several fields of application may benefit from such systems, from industrial contexts, for training and maintenance, to medical ones, for rehabilitation and daycare. Also, entertainment, e.g., videogames or museum applications, is an area where XR technologies are becoming prominent. Technology is now advanced enough to provide us with many devices to visualize XR worlds and track the users. Nevertheless, available systems are still preliminary from the computational point of view. This PhD research theme aims to grow a new researcher able to develop and combine algorithms from Computer Vision, to build a dynamic 3D representation of the real world, with HCI and VR techniques. The final goal should be a coherent XR environment where a user should be able to interact with both real and virtual elements. The user in the XR should show natural, i.e., similar to the corresponding real situations, cognitive and physical behaviors and super-natural experiences must be allowed to overcome the limits of the real world.
References:
Ballestin, G., Chessa, M., & Solari, F. (2021). A registration framework for the comparison of video and optical see-through devices in interactive augmented reality. IEEE Access, 9, 64828-64843.
Chessa, M., & Solari, F. (2021). The sense of being there during online classes: analysis of usability and presence in web-conferencing systems and virtual reality social platforms. Behaviour & Information Technology, 40(12), 1237-1249.
Viola, E., Solari, F., & Chessa, M. (2021). Self Representation and Interaction in Immersive Virtual Reality. In VISIGRAPP (2: HUCAPP) (pp. 237-244).
Valentini, I., Ballestin, G., Bassano, C., Solari, F., & Chessa, M. (2020). Improving obstacle awareness to enhance interaction in virtual reality. In 2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) (pp. 44-52). IEEE.
Supervisor: Daniele D'Agostino
Title: Virtual research environments for astrophysical data
Keywords: Science gateways, research infrastructures
Curriculum: Computer Science
Abstract:
Modern telescopes can yield unique insights into the universe. But a huge amount of information remains stored and largely un exploited in the data archives. From an ICT point of view the key issues are represented by the fact that these archives have been developed with rather old technologies, have a limited implementation of the FAIR principles and they lack an effective integration with computational infrastructures.
Starting from the experience gained in previous European project, the goal of the thesis is two-fold. At first an existing archive will be redesigned to provide a state-of-the-art support to scientists in finding, analysing and post-processing the available data. This involves a heterogeneous set of technologies, including big data analysis and management, machine learning and web programming. Then the integration of European research infrastructures, like the ones provided by Fenix and EGI.
References:
D’Agostino, Daniele, et al. "A citizen science exploration of the X-ray transient sky using the EXTraS science gateway." Future Generation Computer Systems 111 (2020): 806-818.
External collaborations: INAF
Supervisor(s): Daniele D'Agostino, Giorgio Delzanno
Title: A Web IDE for high performance and distributed programs
Keywords: HPC, Distributed computing, Web apps
Curriculum: Computer Science
Abstract:
An online integrated development environment (Web IDE) is a browser-based application to write, run, analyse and share simple programs using one or more programming languages. An increasing number of open source tools exists, with specific goals. For example the Compiler Explorer web app is widely used to analyse the assembly code produced by different compilers on a large set of architectures, including Risc-V and Arm ones. However none of them supports the development and execution of parallel and distributed programs except in the case of Jupiter notebooks on the Google Colab platform.
The goal of this research activity is to extend one of the available tools in order to support reserachers and students in developing better software by providing the possibility to share their implementations and possibly compare the performance by exploiting available computational infrastructures.
References:
Calegari, Patrice, Marc Levrier, and Paweł Balczyński. "Web portals for high-performance computing: a survey." ACM Transactions on the Web (TWEB) 13.1 (2019): 1-36.
Godbolt, M. (2020). Optimizations in C++ compilers. Communications of the ACM, 63(2), 41-49.
Title: Image enhancement and denoising in the deep learning era
Proposer: Francesca Odone, Nicoletta Noceti
Curriculum: Computer Science
Research line: Data Science and Engineering
Topics: Image Processing, Computer Vision, Machine Learning, Deep Learning
Description:
As the quality of acquisition devices improves, image denoising is a crucial task in a variety of application domains, either because the acquisition process is still a challenge (e.g., the medical, biological or astronomic domains) or because of errors caused by transmission or compression.
The project focuses on image denoising with the objective of exploring possible combinations between classical approaches based on harmonic analysis tools (such as wavelets or their variants) and the most recent deep learning approaches. The effectiveness of the latter is out of question, with the price of requiring large amount of data and thorough and costly supervisions. Disentangled representations are a possible way to address imaging tasks with a limited amount of supervision.
Supervisor(s):
Angelo Ferrando, PhD [University of Genova]
Rafael C. Cardoso, PhD [University of Aberdeen]
Title: Explainable and Reliable Autonomous Agents in the age of Robotics
Keywords: Multi-Agent Systems, Artificial Intelligence, Formal
Verification, Robotics, Machine Learning
Curriculum: Computer Science
Abstract:
The demand for the use of autonomous systems has been increasing in
the past years, especially in applications domains that contain
hazardous environments, require timely decisions/reactions, or are
simply too expensive or too mundane to operationalise (such as robotic
applications). With this increase in demand, autonomous systems are
also facing higher scrutiny in terms of trust that the autonomous
behaviour works as intended and does not violate any safety
constraints. Thus, it is important to provide assurances that can
increase the confidence we (regulators, public, developers,
stakeholders, etc) have about autonomous systems. Recent autonomous
systems (e.g., robots) have a high degree of modularity due to the
assortment of different components that interact with each other. Last
but not least, along with the need of higher reliability, such
autonomous systems are also required to be explainable; that is, they
must be capable of explaining their choices.This aspect is crucial for
the deployment of autonomous systems in real-world scenarios, which
are frequently safety-critical (i.e., scenarios where a failure can be
costly).
The aim of this PhD project is to study and develop new techniques to
increase confidence in autonomous systems, especially when deployed
for robotic applications. This requires working both on the artificial
intelligence side (i.e., how the autonomous system reasons), as well
as its engineering (i.e., how to make the autonomous system more
reliable in its decisions).
For what concerns the development of prototypes to support the
research project, we foresee – but we do not limit to – the use of
Agent-Based frameworks, such as JaCaMo [1], for the development of
explainable autonomous components, ROS [2], for the development of
robotic components, and TensorFlow [3], for training and deploying
machine learning models . To improve the reliability of such
solutions, techniques based upon formal verification will be studied,
and deployed. In particular, more dynamic and flexible techniques,
such as Runtime Verification [4], that can be used to analyse the
runtime behaviour of the running system (the autonomous/robotic
component in this case). Some related work can be found in [5-7].
References:
[1] Boissier, O., Bordini, R. H., Hübner, J. F., Ricci, A., & Santi,
A. (2013). Multi-agent oriented programming with JaCaMo. Science of
Computer Programming, 78(6), 747-761.
[2] Robot Operating System: www.ros.org
[3] TensorFlow: https://www.tensorflow.org/
[4] Bartocci, E., Falcone, Y., Francalanza, A., & Reger, G. (2018).
Introduction to runtime verification. In Lectures on Runtime
Verification (pp. 1-33). Springer, Cham.
[5] Fisher, M., Ferrando, A., & Cardoso, R. C. (2021, July).
Increasing confidence in autonomous systems. In Proceedings of the 5th
ACM International Workshop on Verification and mOnitoring at Runtime
EXecution (pp. 1-4).
[6] Ferrando, A., Dennis, L. A., Cardoso, R. C., Fisher, M., Ancona,
D., & Mascardi, V. (2021). Toward a holistic approach to verification
and validation of autonomous cognitive systems. ACM Transactions on
Software Engineering and Methodology (TOSEM), 30(4), 1-43.
[7] Ferrando, A., Cardoso, R. C., Fisher, M., Ancona, D.,
Franceschini, L., & Mascardi, V. (2020, September). ROSMonitoring: a
runtime verification framework for ROS. In Annual Conference Towards
Autonomous Robotic Systems (pp. 387-399). Springer, Cham.
External collaborations: University of Aberdeen, United Kingdom
Title: Design and Validation of IoT/Big Data Applications
Proposer: Giorgio Delzanno
Curriculum: Computer Science
Description: Multithreaded, parallel and distributed applications are at the core of modern software architectures and applications. For instance, reference architectures for the Internet of Things are typically based on scalable distributed engines mixing the use of local, low-power system on chips (i.e. Edge and Fog computing) together with remote computing infrastructures (e.g. the Cloud) for data ingestion, real time and batch processing and data visualisation. We can find here multiple open challenges ranging from new architectures for data processing (e.g. Spark), to seamlessly provide data integration and code migration, to enable high performance/efficient computing as services (HPCaaS), exploiting the computational power of edge computing resources at their best (e.g. neural accelerators).
In this general setting we are interested in the more specific research lines in the context of the PNRR Ecosystem "RAISE" project:
- IoT/Big data applications for smart cities/ports/building combining edge and cloud computing [1,2]
- Validation of IoT applications using run time verification in combination with process mining [3] and parameterized verification [4,5,6]
Link to the group or personal webpage: Giorgio-Delzanno's-webpage DBLP
References:
[1] L. Bixio, Giorgio Delzanno, S. Rebora, M. Rulli:
A Flexible IoT Stream Processing Architecture Based on Microservices. Inf. 11(12): 565 (2020)
[2] A Solution for Improving Robustness of GNSS Positioning from Android Devices,
Lorenzo Benvenuto's Phd Thesis in Computer Science and Systems Engineering, University of Genoa, May 2022
Supervisors: Giorgio Delzanno (Dibris) and Tiziano Cosso (Gter)
[3] D. Ancona, L. Benvenuto, G. Delzanno, G. Gambari:
Flow Programming: A Flexible way to bring the Internet of Things into the Lab.
UMAP 2020: 155-158
[4] Angelo Ferrando, Giorgio Delzanno:
Incrementally Predictive Runtime Verification.
CILC 2021: 92-106
[5] S. Conchon, G. Delzanno, A. Ferrando:
Declarative Parameterized Verification of Distributed Protocols via the Cubicle Model Checker.
Fundam. Informaticae 178(4): 347-378 (2021)
[6] Sylvain Conchon, Giorgio Delzanno, Arnaud Sangnier:
Verification of Contact Tracing Protocols via SMT-based Model Checking and Counting Abstraction.
CILC 2021: 77-91
Supervisor(s):Maurizio Leotta, Filippo Ricca
Title: Developing Novel Test Automation Solutions for Web and Mobile Applications
Keywords: End-to-end Testing, Test Automation, Software Engineering
Curriculum: Computer Science
Abstract:
Testing web and smartphone apps can take a long time, both for the complexity of these products and for the variety of environments through which end users can use them. On the other hand, the need to reduce the distribution times of new versions and the progressive adoption of Agile methodologies in software development lead to ever smaller margins to guarantee the effective quality of the final product. In this context, the creation of automated tests becomes an essential requirement to increase efficiency and quality while at the same time reducing the overall costs.
The objectives/steps of the PhD are:
1) Selecting one of the possible interesting topics in the context of web or mobile testing, for example: automated test suite generation, test suite fragility reduction, test suite execution optimization, test suite flakiness reduction etc.
2) Studying the state of the art in this specific topic
3) Devising one or more solutions/algorithms advancing the state of the art, and implementing them.
4) Executing empirical studies comparing existing solutions with the novel proposals.
https://www.disi.unige.it/person/LeottaM/
https://www.disi.unige.it/person/RiccaF/
References
- Maurizio Leotta, Filippo Ricca, Paolo Tonella. SIDEREAL: Statistical Adaptive Generation of Robust Locators for Web Testing. Journal of Software: Testing, Verification and Reliability (STVR), Volume 31, Issue 3, pp.e1767, Editors: Tao Xie, Robert M. Hierons. John Wiley & Sons, 2021.
- Dario Olianas, Maurizio Leotta, Filippo Ricca, Matteo Biagiola, Paolo Tonella. STILE: a Tool for Parallel Execution of E2E WebTest Scripts. Proceedings of 14th IEEE International Conference on Software Testing, Verification and Validation (ICST 2021), IEEE, 2021.
- Maurizio Leotta, Diego Clerissi, Filippo Ricca, Paolo Tonella. Approaches and Tools for Automated End-to-End Web Testing. Advances in Computers, Volume 101, pp.193-237, Editor: Atif Memon. Elsevier, 2016.
External collaborations:
Both from Academia (e.g., University of Lugano, Blekinge Institute of Technology, University of Madrid) and local Industries.
Supervisor: Enrico Puppo
Supervisor(s): Massimo Paolucci
Title: Optimization approaches for Green Scheduling in manufacturing
Keywords: Parallel machine scheduling, Time-of-Use energy prices, multi-objective optimization, mixed integer programming formulations, metaheuristic algorithms, matheuristic algorithms
Curriculum: System Engineering
Abstract:
In recent years energy-efficient scheduling has become an important topic in the scientific literature, as it has taken a key role in ensuring sustainability of manufacturing industry through the reduction of energy consumption and carbon emissions. Rethinking the production processes under a sustainable lens, and simultaneously fostering environment-aware consumption practices in customers, appear to be more and more necessary. To this end, one of the first actions undertaken by energy suppliers consisted of flattening the peaks of demand in power plants by means of strategies aimed at reducing the high economic burdens related to the generation of high energy loads in short periods of time and, consequently, the environmental impact related to energy production. A possible strategy consists of the Time-of-Use (TOU) pricing policy, that spur electricity usage at off-peak hours by means of low prices, while penalizing peak hours with higher prices. In manufacturing, TOU-based energy tariffs can be taken into account by carefully rescheduling the production processes during periods characterized by low energy supply costs.
In such a context, the proposed research aims at developing both exact and heuristic approaches for scheduling problems that require the simultaneous optimization of multiple objectives, in particular including the minimization of the energy cost/consumption and the optimization of performance indexes related to the effectiveness of production and customer satisfaction (e.g., the makespan or tardiness minimization). This research should focus on the class of parallel machine scheduling, progressively including qualifying features to be able to model actual industrial requirements. The heuristic approaches to be designed and experimented can consist in both matheuristic, in particular based on mixed integer programming formulations, and metaheuristic algorithm
References:
- Anghinolfi, M. Paolucci, R. Ronco. A bi-objective heuristic approach for green identical parallel machine scheduling. European Journal of Operational Research, Volume 289, Issue 2, 2021, 416-434, ISSN 0377-2217. doi: 10.1016/j.ejor.2020.07.02
- Catanzaro, R. Pesenti, R. Ronco. Job Scheduling under Time-of-Use Energy Tariffs for Sustainable Manufacturing: A Survey. Submitted to European Journal of Operational Research, January 2022.
Title: Optimization and control of sustainable districts and active prosumers.
Proposer: Michela Robba
Curriculum: Systems Engineering
Research area(s): Optimization, optimal control, model predictive control, energy communities, sustainable districts, aggregator, energy market.
Abstract:
Significant effort has been expended of late, across the globe, to reduce greenhouse gas emissions and to achieve sustainability which in turn has led to a fundamental change in the management of resources and cities. In the case of the energy sector, the increase in the use of renewable resources and distributed generation, as well as the growing presence of electric vehicles, prosumers, microgrids, and other small-scale distributed resources, have enabled and accelerated restructuring of the electrical grid. In order to carry out optimal management of these distributed resources and address associated control problems, new models, methods, and technologies are necessary [1]. Concomitantly, new legislation, actors, and market mechanisms that support such an emerging grid structure are needed [2]. A novel concept that has been recently introduced in the context of smart energy management in cities is that of an Energy Community (EC), i.e., a set of residential or small commercial agents, each acting as prosumer and generally including generation (electric and thermal), storage units such as batteries, and flexible loads. Another new market entity is the aggregator, i.e. a market actor in charge of interacting with the Transmission System Operator (TSO) to reduce a load of a portion of territory through the coordination of different prosumers and users.
The proposed PhD research activity will fall within this framework. In particular, the following main objectives/activities can be listed:
- Definition and development of a general EMS for energy communities and sustainable energy districts.
- Models and methods for the coordination of local prosumers (that include renewables, storage systems, electrical vehicles, etc.) for demand response in the energy market.
- Optimal control of smart charging parks for electric vehicles.
- Models and methods for the integration of electric vehicles in energy communities, sustainable districts, and the energy market.
Link to personal homepage
http://www.dibris.unige.it/robba-michela
References:
[1] M. Garcia, H. Nagarajan, and R. Baldick, “Generalized convex hull pricing for the ac optimal power flow problem,” IEEE Transactions on Control of Network Systems, vol. 7, no. 3, pp. 1500–1510, 2020.
[2] G Ferro, M Robba, R Haider, AM Annaswamy, “A distributed optimization based architecture for management of interconnected energy hubs,” IEEE Transactions on Control of Network Systems, 2022.
Title: Detection of the origin of movement: Data processing and developments software libraries
Supervisors: Antonio Camurri, Giorgio Gnecco (IMT Lucca), Marcello Sanguineti, Gualtiero Volpe
Keywords: Origin of movement, Human-Computer Interaction, Affective computing, Motion capture, Multimodal interfaces and systems.
Curriculum: Computer Science
Abstract. In the thesis, the approach proposed in [1,2] for the analysis of the origin of human movement will be developed in from the points of its exploitation in real-time contexts, with particular emphasis on data processing and production of software libraries to allow its real-time application. The perceived origin of movement is the point at which a movement appears to originate from the point of view of an observer. The importance of full-body movements in conveying affective expressions and social signals is widely recognized by the scientific community [3,4], and a growing number of applications exploiting full-body expressive movement and non-verbal social signals are available. The possibility to automatically measure movement qualities such as its origin demonstrated to be very important in many different interactive applications, including therapy and rehabilitation in autism, and in cognitive and motor disabilities [5]. In [1,2], an approach based on a mathematical model called cooperative game is developed to study the origin of movement. A mathematical game is built over a graph structure representing the human body and a utility function related with movement features was defined. The games of the players are the joints of the human body. An attribute of the players, called “Shapley value” is evaluated and used to study movement. The targets of the proposed thesis are two. The first one consists in refining the methodology developed in [1,2] by considering a larger set of movement features, namely speed, tangential acceleration, and angular momentum. It will be investigated which feature is best at predicting the origin of movement. The method will be applied to a data set of Motion Capture data of subjects performing expressive movements, also by applying suitable filtering techniques to such data. The second target is the development of software libraries for the analysis of the origin of movement. The departure point is a software, written in Matlab, which extracts movement features (speed, tangential acceleration, kinetic energy, angular momentum) for two skeleton models of the human body, which refer to two different spatial scales. Such features are filtered and combined to compute a dissimilarity measure for the joints, from which a transferable utility game on an auxiliary graph is constructed. Finally, the vector of Shapley values for that game is computed (for the case in which the Shapley value coincides with the weighted degree centrality), and normalized with respect to the maximum Shapley value. The software allows for the possibility of computing the Kendall correlation between different rankings of joints. This software should be re-written in a suitable language and optimized from the point of view of efficiency and runtime, in such a way to make it exploitable for real-time analysis of the origin of movement.
External collaborations. This thesis will benefit from the ongoing activities of the European-funded FET PROACTIVE EnTimeMent 4-year project (entimement.dibris.unige.it). EnTimeMent aims at the foundation and consolidation of radically new models and motion analysis technologies for automated prediction and analysis of human movement qualities, entrainment, and non-verbal full-body social emotions. The approach is grounded on novel neuroscientific, biomechanical, psychological, and computational evidence dynamically suited to the human time, towards time-adaptive technologies operating at multiple time scales in a multi-layered approach. The research will benefit also from the motion capture and multimodal technology infrastructure available at Casa Paganini-InfoMus of Dibris (www.casapaganini.org). Specific application testbeds to validate and evaluate research results will be identified in one of the EnTimeMent scenarios (cognitive-motor rehabilitation, performing arts, sport). The thesis will also benefit from the ongoing activities of the Università Italo-Francese project GALILEO 2021 no. G21 89, “Automatic movement analysis techniques for applications in cognitive/motor rehabilitation”, between Università di Genova, IMT - Scuola Alti Studi Lucca, and Université de Montpellier.
Research activities will include collaborations and short residencies at the premises of one or more partners of the EnTimeMent project, including Qualisys (motion capture industry), Euromov – University of Montpellier (Prof Benoit Bardy), UCL University College London (Prof Nadia Berthouze), with IMT - School for Advanced Studies, Lucca (Prof. Giorgio Gnecco), and with the incubators of startups GDI Hub (London) and Wylab (Chiavari).
Link to the group/personal webpage:
www.casapaganini.org
entimement.dibris.unige.it
References
[1] K. Kolykhalova, G. Gnecco, M. Sanguineti, G. Volpe, A. Camurri: Automated Analysis of the Origin of Movement: An Approach Based on Cooperative Games on Graphs. IEEE Trans. on Human-Machine Systems, Vol. 50, pp. 550-560, 2020.
[2] O. Matthiopoulou, B. Bardy, G. Gnecco, D. Mottet, M. Sanguineti, A. Camurri: A computational method to automatically detect the perceived origin of full-body human movement and its propagation. Proc. Multi-Scale Movement Technologies ACM-ICMI 2020 Int. Workshop. 25-29 Oct. 2020, pp. 449-453.
[3] B. De Gelder, “Why bodies? Twelve reasons for including bodily expressions in affective neuroscience,” Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 364, no. 1535, pp. 3475–3484, 2009.
[4] A. Kleinsmith, N. Bianchi-Berthouze: Affective body expression perception and recognition: A survey,” IEEE Transactions on Affective Computing, vol. 4, no. 1, pp. 15–33, 2013.
[5] S. Piana, A. Staglianò, F. Odone, A. Camurri: Adaptive Body Gesture Representation for Automatic Emotion Recognition. New York, NY, USA: ACM, Mar 2016, vol. 6, no. 1, pp. 6:1–6:31. Available: http://doi.acm.org/10.1145/2818740
Title: Automated analysis of expressive qualities of full-body human movement
Supervisors: Antonio Camurri, Giorgio Gnecco (IMT Lucca), Marcello Sanguineti, Gualtiero Volpe
Curriculum: Computer Science
Keywords: Affective computing, Human-Computer Interaction, Motion capture, Multimodal interfaces and systems, Operation research, Games.
Abstract. The role played by full-body movements in conveying affective expressions and social signals is widely recognized by the scientific community [1], and a growing number of applications exploiting full-body expressive movement and non-verbal social signals is available. The possibility to automatically measure movement qualities is very valuable in many different interactive applications, including therapy and rehabilitation in autism, and in cognitive and motor disabilities. In [2,3], the automated analysis of the origin of movement (i.e., where in the body the movement initiates), which is an important component in understanding and modelling expressive movement, was investigated.
In the thesis, the approach proposed in [2,3,4,5] will be developed in several directions by using the same approach, based on a mathematical model called cooperative game. In general, mathematical games [6] study interactions among subjects, by modelling conflict or cooperation between intelligent entities called players. In the analysis of full-body human movement, the game model is built over a suitably-defined three-dimensional structure representing the human body. The players represent a subset of body joints. Each group of players has an associated utility, which represents their joint contribution to a common task. Using a utility constructed starting from a movement-related feature such as speed, a cooperative game index called Shapley value [6] can be exploited to analyse expressive qualities (e.g., to identify the movement origin, as done in [2,3,4,5] using the feature speed). Targets of the proposed thesis include, e.g:
- Considering different formulations of the cooperative game and/or different cooperative indices.
- Extracting and embedding into the model other features and/or sets of features calculated from movements, such as position, acceleration, speed, jerks, and angular acceleration.
- Investigating the time series of the Shapley values to capture the dynamics of movement in finer details (e.g., the importance of different timescales in recognizing a specific movement).
- Modelling biomechanical constraints, which determine the way we move as well as the way we perceive movements.
- Analysing the automatic detection of movement qualities different from the origin of movement.
- Conceiving novel experiments, in order to build up the movement repertoire and enlarge the available motion-capture data set.
As an outcome of the thesis, a larger set of computational methods and software tools will be available for the automatic analysis of expressive qualities associated with full-body human movement.
External collaborations. This thesis will benefit from the ongoing activities of the European-funded FET PROACTIVE EnTimeMent 4-year project (entimement.dibris.unige.it). EnTimeMent aims at the foundation and consolidation of radically new models and motion analysis technologies for automated prediction and analysis of human movement qualities, entrainment, and non-verbal full-body social emotions. The approach is grounded on novel neuroscientific, biomechanical, psychological, and computational evidence dynamically suited to the human time, towards time-adaptive technologies operating at multiple time scales in a multi-layered approach. The research will benefit also from the motion capture and multimodal technology infrastructure available at Casa Paganini-InfoMus of Dibris (www.casapaganini.org). Specific application testbeds to validate and evaluate research results will be identified in one of the EnTimeMent scenarios (cognitive-motor rehabilitation, performing arts, sport). The thesis will also benefit from the ongoing activities of the of the Università Italo-Francese project GALILEO 2021 no. G21 89, “Automatic movement analysis techniques for applications in cognitive/motor rehabilitation”, between Università di Genova, IMT - Scuola Alti Studi Lucca, and Université de Montpellier.
Research activities will include collaborations and short residencies at the premises of one or more partners of the EnTimeMent project, including Qualisys (motion capture industry), Euromov – University of Montpellier (Prof Benoit Bardy), UCL University College London (Prof Nadia Berthouze), with IMT - School for Advanced Studies, Lucca (Prof. Giorgio Gnecco), and with the incubators of startups GDI Hub (London) and Wylab (Chiavari).
Link to the group/personal webpage:
www.casapaganini.org
entimement.dibris.unige.it
References
[1] A. Kleinsmith and N. Bianchi-Berthouze, “Affective body expression perception and recognition: A survey,” IEEE Transactions on Affective Computing, vol. 4, no. 1, pp. 15–33, 2013.
[2] K. Kolykhalova, G. Gnecco, M. Sanguineti, A. Camurri, and G. Volpe: Graph-restricted game approach for investigating human movement qualities”. Proc. 4th Int. Conf. on Movement Computing (MOCO ’17). London, UK: ACM, 2017, article no. 30, 4 pages.
[3] K. Kolykhalova, G. Gnecco, M. Sanguineti, G. Volpe, A. Camurri: Automated Analysis of the Origin of Movement: An Approach Based on Cooperative Games on Graphs. IEEE Trans. on Human-Machine Systems,. Vol. 50, pp. 550-560, 2020.
[4] O. Matthiopoulou, B. Bardy, G. Gnecco, D. Mottet, M. Sanguineti, and A. Camurri: A computational method to automatically detect the perceived origin of full-body human movement and its propagation. Proc. Multi-Scale Movement Technologies ACM-ICMI 2020 Int. Workshop. 25-29 Oct. 2020, pp. 449-453.
[5] O. Matthiopoulou, B. Bardy, A. Camurri, G. Gnecco, D. Mottet, and M. Sanguineti: Detection of the Origin of Movement: Graph-Theoretical Model and Data Processing. Int. Conf. on Optimization a nd Decision Science. Firenze, 30 Aug.-2 Setp 2022.
[6] M. Maschler, E. Solan, and S. Zamir, Game Theory. Cambridge, UK: Cambridge University Press, 2013.
Computer Science Workshop by DOCS
PhD Program in Computer Science and Systems Engineering
Industrial Research Projects Proposals 2022 (XXXVIII Cycle), PNRR/DIBRIS
Computer Science
Machine Learning for Ultrasound Imaging (Dibris/Esaote)
The focus of this 3 years position is the application of machine learning algorithms, libraries and tool for the analysis of ultrasound images. The research activity will be carried out in collaboration with the Esaote company (https://www.esaote.com) and the MaLGa and Computer Vision research groups of Dibris (Prof. Francesca Odone). Candidates will carry out a doctoral program in close collaboration between university and industry and they will be supported by an academic supervisor and a supervisor from the company's R&D department. Candidates are required to have a solid background in computer science. The PhD program includes training activities on advanced topics, research and technology transfer activities on themes of interest for the company R&D department and for the academic supervisor. During the PhD program, candidates will have the opportunity to attend PhD seminars, workshops, and schools organized by the CSSE PhD board and national and international workshops and conferences.
More details on the company research activity:
https://vimeo.com/473605488
- MRI R&D https://vimeo.com/533432792
- Ultrasounds R&D https://vimeo.com/512512187
- Ultrasounds Probe R&D https://vimeo.com/512511923
- Medical IT https://vimeo.com/512510149
Virtual images for learning and testing of neural networks (Dibris/Aitek)
The goal of this 3 years position is the use of virtual images, computer-graphics generated images representing a close approximation to reality, for learning and testing of neural networks. The research activity will be carried out in collaboration with the Aitek company (https://www.aitek.it/) and the Computer Vision research group (Prof. Francesca Odone). Candidates will carry out a doctoral program in close collaboration between university and industry and they will be supported by an academic supervisor and a supervisor from the company's R&D department. Candidates are required to have a solid background in computer science. The PhD program includes training activities on advanced topics, research and technology transfer activities on themes of interest for the company R&D department and for the academic supervisor. During the PhD program, candidates will have the opportunity to attend PhD seminars, workshops, and schools organized by the CSSE PhD board and national and international workshops and conferences.
GNSS Positioning with smartphones and low cost devices (Dibris/Gter)
The focus of this 3 years position is the use of study of algorithms and heuristics for improving GNSS positioning on smartphone and low cost device. The research activity will be carried out in collaboration with the Gter company (https://www.gter.it/) and Dibris researchers working on IoT applications (Prof. Giorgio Delzanno). Candidates will carry out a doctoral program in close collaboration between university and industry. In this respect they will be supported by an academic supervisor and a supervisor from the company's R&D department. Candidates are required to have a solid background in computer science and engineering. The PhD program includes training activities on advanced topics, research and technology transfer activities on themes of interest for the company R&D department and for the academic supervisor. During the PhD program, candidates will have the opportunity to attend PhD seminars, workshops, and schools organized by the CSSE PhD board and national and international workshops and conferences.
Additional material:
A Glance on GNSS (presentation of GNSS positioning and related research topics)
A Solution for Improving Robustness of GNSS Positioning from Android Devices
Lorenzo Benvenuto's Phd Thesis in Computer Science and Systems Engineering, University of Genoa, May 2022
Supervisors: Giorgio Delzanno (Dibris) and Tiziano Cosso (Gter)
Cybersecurity and information management in maritime terminals (Dibris/PSA Genoa Investments)
The focus of this 3 years position is the design of innovative methods and tools for cybersecurity and information management in maritime terminals. The research activity will be carried out in collaboration with the PSA Genoa Investment company (https://www.globalpsa.com/), and computer science and engineering researchers working in cybersecurity at Dibris (CSec Lab https://www.csec.it/). Candidates will carry out a doctoral program in close collaboration between university and industry and they will be supported by an academic supervisor and a supervisor from the company's R&D department. Candidates are required to have a solid background in computer science and engineering. The PhD program includes training activities on advanced topics, research and technology transfer activities on themes of interest for the company R&D department and for the academic supervisor. During the PhD program, candidates will have the opportunity to attend PhD seminars, workshops, and schools organized by the CSSE PhD board and national and international workshops and conferences.
Resilience, integration and efficiency of ICT systems in the rail transport domain (Dibris/M3S)
The focus of this 3 years position is the application of innovative methods for improving resilience, integration and efficiency of ICT systems in the rail transport domain. The research activity will be carried out in collaboration with the M3S company (https://www.m3s.it/), and Computer Engineering researchers at Dibris (Prof. Massimo Maresca and Prof. Pierpaolo Baglietto). Candidates will carry out a doctoral program in close collaboration between university and industry and they will be supported by an academic supervisor and a supervisor from the company's R&D department. Candidates are required to have a solid background in computer engineering. The PhD program includes training activities on advanced topics, research and technology transfer activities on themes of interest for the company R&D department and for the academic supervisor. During the PhD program, candidates will have the opportunity to attend PhD seminars, workshops, and schools organized by the CSSE PhD board and national and international workshops and conferences.
Digital transformation of process management in the insurance appraisals domain (Dibris/Teec)
The focus of this 3 years position is the study of innovative models, methods and tools for supporting the digital transformation of process management in the insurance appraisals domain (e.g image and text processing and ad hoc edge computing tools). The research activity will be carried out in collaboration with the TEEC company (https://www.queirolo.eu/work/teec/), and computer science researchers at Dibris (Prof. Giovanna Guerrini, Prof. Giorgio Delzanno). Candidates will carry out a doctoral program in close collaboration between university and industry and they will be supported by an academic supervisor and a supervisor from the company's R&D department. Candidates are required to have a solid background in computer science. The PhD program includes training activities on advanced topics, research and technology transfer activities on themes of interest for the company R&D department and for the academic supervisor. During the PhD program, candidates will have the opportunity to attend PhD seminars, workshops, and schools organized by the CSSE PhD board and national and international workshops and conferences.
BigData and High Performance Computing Solutions in the Computing Continuum, Cloud-Edge, and Digital Twin applications (Leonardo Labs)
The focus of this 3 years position is the study of innovative methods and tools for BigData and High Performance Computing Solutions in the Computing Continuum, Cloud-Edge, and Digital Twin applications. The research activity will be carried out in collaboration with the Leonardo Labs company , and computer science researchers at Dibris. Candidates will carry out a doctoral program in close collaboration between university and industry and they will be supported by an academic supervisor and a supervisor from the company's R&D department. Candidates are required to have a solid background in computer science. The PhD program includes training activities on advanced topics, research and technology transfer activities on themes of interest for the company R&D department and for the academic supervisor. During the PhD program, candidates will have the opportunity to attend PhD seminars, workshops, and schools organized by the CSSE PhD board and national and international workshops and conferences.
Detailed description: The research will focus on the performance efficiency of container technologies for BigData and HPC Digital Twin distributed applications, deployed on heterogeneous Cloud-Edge architectures. The student will have the possibility of performing his/her research using the davinci-1 supercomputer: Supercomputer Davinci -1 | Leonardo and collaborating with the leonardo lab researchers. The research will be co-supervised by Carlo Cavazzoni responsible for the HPC, BigData and Cloud Computing Leonardo Lab. Before joining Leonardo in May 2020, Carlo Cavazzoni spent more than 20 years in Cineca (Italian supercomputing centre). He is a member of the EuroHPC-JU Research and Innovation Advisory Board., and he contributed to many EC infrastructure and research HPC projects.
Carlo Cavazzoni is author and co-author of 100+ peer review publications, including Science, Physical Review Letters, Nature Materials, and many others. See also https://www.researchgate.net/profile/Carlo-Cavazzoni-2/publications. Finally, he was a pioneer in HPC architecture designs with two successful HPC prototypes cofounded by PRACE (prace-ri.eu): Eurora and DAVIDE, build in partnership with Eurotech (Eurora) and E4 (DAVIDE). In particular Eurora was ranked first in the Green500 lists in June 2013.
Digital twins are software applications built with the aim of replicating, in a synthetically generated environment, the response of a real system to a change in its environment, and then used to make predictions about the behaviour of the real system (e.g. perform prediction about a failure of a component, aka predictive maintenance). Digital twin can be data driven, model driven or a combination of the two. Data driven digital twins take their predictive power from an implicit model of a real system built using AI and Data Analytics and are boosted by the use of BigData technologies. Model driven Digital twins takes their predictive power from an explicit model built using a set of equations describing the physics of the system, and are boosted by the use of High Performance Computing technologies. The combination of the two requires both BigData and HPC technologies. Digital Twins evolve and improve the predictive power also assimilating data collected from the real system being monitored. Whereas from the point of view of the infrastructure we can assume that today and in future digital twin run on a cloud service, but requiring the monitoring functionalities for data collection being run close to the real system in an edge device or server. Digital twins have then a software component running at the core and one running on the edge in the so called digital continuum.
Security and Resilience of Orchestration and Software Defined Networking and Computing (SDN / SDC) technologies for certified applications in the Cloud and 5G areas (Leonardo)
The focus of this 3 years position is the study of innovative methods and tools for security and resilience of orchestration and software defined networking and computing (SDN / SDC) technologies for certified applications in the cloud and 5G areas. The research activity will be carried out in collaboration with the Leonardo Labs company , and computer science researchers at Dibris. Candidates will carry out a doctoral program in close collaboration between university and industry and they will be supported by an academic supervisor and a supervisor from the company's R&D department. Candidates are required to have a solid background in computer science. The PhD program includes training activities on advanced topics, research and technology transfer activities on themes of interest for the company R&D department and for the academic supervisor. During the PhD program, candidates will have the opportunity to attend PhD seminars, workshops, and schools organized by the CSSE PhD board and national and international workshops and conferences.
Systems Engineering
Transport Optimization in the Decathlon logistics network and supply chain (Dibris/Decathlon)
The focus of this 3 years position is the application of innovative methods for transport optimizations in logistic networks, supply chain (see detailed description). The research activity will be carried out in collaboration with the Decathlon company (Decathlon Italia https://www.decathlon.it/), the Stamtech company (/https://www.stamtech.com/), and Systems Engineering researchers at Dibris (Prof. Michela Robba). Candidates will carry out a doctoral program in close collaboration between university and industry and they will be supported by an academic supervisor and a supervisor from the company's R&D department. Candidates are required to have a solid background in systems engineering. The PhD program includes training activities on advanced topics, research and technology transfer activities on themes of interest for the company R&D department and for the academic supervisor. During the PhD program, candidates will have the opportunity to attend PhD seminars, workshops, and schools organized by the CSSE PhD board and national and international workshops and conferences.
Decathlon is a French multinational created in 1976, dedicated to design, manufacturing and distribution of sport goods with a strong development based on their own brands and a very large offer related on more than 110 different sport activities. Decathlon’s supply chain mainly outsources the production of main products such as: sportswear, equipment, and sports equipment. Manufacturing is the only stage in which Decathlon cooperates with subcontractors located mainly in Asia (most in China and Vietnam) and Europe (Portugal and Italy). The supply chain today is very complex because of siloed steps from the production to the final customer. Indeed, the products have to pass through Decathlon's logistics network made up of 69 warehouses and logistics platforms distributed all over the world. Indeed, the product passes from the manufacturing country to the warehouse called Continental Network Warehouse (EDC) and distributed to the other local warehouses called Regional Network Warehouse (DC). The latter delivers the product to the Decathlon stores or, for the e-commerce, directly to the customer.
The digitalization process that Decathlon is following aims to bring down these barriers transforming the supply chain in an integrated and fully transparent ecosystem.
The main aim of the activities which will be done during the thesis will be focused on:
- Traceability of the goods during all shipment phases from supplier to customer. Today, there is a list of internal initiative to map each shipment, for instance from DC to regional shop. The digital transformation will bring the implementation of a unique platform able to map the position of a singular BAC/product form the production to the end of life. An intensive Data layering and data extraction from different internal and external tools will be performed. The chain visibility depends on the creation of an effective “Track and Trace” (T&T) system that allows players to determine the status of any given shipment of goods at any point in its travels, by any transport mode. Transport data and status information will be captured from enterprise resource planning systems as well as from carriers, either through direct connections or via third-party portals. GPS technology will enable companies to check exact shipment locations.
- Optimization of shipments Suppliers-EDC and DC-Customer. It will be based on timeline, costs, routes and other constraints. The result will enable companies to react to disruptions in the supply chain, and even anticipate them, by fully modeling the network, creating “what-if” scenarios, and adjusting the supply chain in real time as conditions change.
- Reduction of measurable environmental impact. In a product's life cycle, transport is not the most polluting stage, but this has not prevented Decathlon from taking measures relating to the transport part. Decathlon teams are currently in the midst of analyzing the environmental impact of this phase. The purpose of this activities is to perform a worldwide assessment, allowing Decathlon to precisely identify the areas for improvements and set goals for the years to come.
Mobility data analysis of TPS and MaaS users (Dibris/Aitek)
The focus of this 3 years position is the application of innovative methods for the analysis of mobility data dor TPS and MaaS (Mobility as a Service) users. The research activity will be carried out in collaboration with the Aitek company (https://www.esaote.com) and Systems Engineering researchers at Dibris (Prof. Simona Sacone). Candidates will carry out a doctoral program in close collaboration between university and industry and they will be supported by an academic supervisor and a supervisor from the company's R&D department. Candidates are required to have a solid background in systems engineering. The PhD program includes training activities on advanced topics, research and technology transfer activities on themes of interest for the company R&D department and for the academic supervisor. During the PhD program, candidates will have the opportunity to attend PhD seminars, workshops, and schools organized by the CSSE PhD board and national and international workshops and conferences.
Design of methods and tools for the optimal planning of maritime terminals processes (Dibris/PSA Genoa Investment)
The focus of this 3 years position is the design of innovative methods and tools for the optimal planning of maritime terminals processes. The research activity will be carried out in collaboration with the PSA Genoa Investment company (https://www.globalpsa.com/ and https://www.psagp.it/), and Systems Engineering researchers at Dibris (Prof. Simona Sacone). Candidates will carry out a doctoral program in close collaboration between university and industry and they will be supported by an academic supervisor and a supervisor from the company's R&D department. Candidates are required to have a solid background in systems engineering. The PhD program includes training activities on advanced topics, research and technology transfer activities on themes of interest for the company R&D department and for the academic supervisor. During the PhD program, candidates will have the opportunity to attend PhD seminars, workshops, and schools organized by the CSSE PhD board and national and international workshops and conferences.
Optimization of multi-agent systems through Reinforcement Learning (Dibris/Rulex Innovation Lab)
The focus of this 3 years position is the application of reinforcement learning methods, a special class of artificial intelligence methods, in the design of multi agent systems for industrial control systems. The research activity will be carried out in collaboration with the Rulex company (https://www.rulex.ai/), and artificial intelligence researchers at Dibris (Prof. Armando Tacchella, Prof. Viviana Mascardi, AIMS group). Candidates will carry out a doctoral program in close collaboration between university and industry and they will be supported by an academic supervisor and a supervisor from the company's R&D department. Candidates are required to have a solid background in artifical intelligence. The PhD program includes training activities on advanced topics, research and technology transfer activities on themes of interest for the company R&D department and for the academic supervisor. During the PhD program, candidates will have the opportunity to attend PhD seminars, workshops, and schools organized by the CSSE PhD board and national and international workshops and conferences.
Digital and smart ticketing (Dibris/MyPass)
The focus of this 3 years position is the study of innovative models, methods and tools for the smart ticketing with applications in different domains (transportation, turism, etc). The research activity will be carried out in collaboration with the MyPass company (https://www.mypass.cc/), and systems engineering researchers at Dibris (Prof. Roberto Sacile). Candidates will carry out a doctoral program in close collaboration between university and industry and they will be supported by an academic supervisor and a supervisor from the company's R&D department. Candidates are required to have a solid background in systems engineering. The PhD program includes training activities on advanced topics, research and technology transfer activities on themes of interest for the company R&D department and for the academic supervisor. During the PhD program, candidates will have the opportunity to attend PhD seminars, workshops, and schools organized by the CSSE PhD board and national and international workshops and conferences.
Analysis, planning, integration and monitoring of mobility services: innovative models, methods and tools for the mobility of the future (Dibris/Tema srl)
The focus of this 3 years position is the study of innovative models, methods and tools for the analysis, planning, integration and monitoring of mobility services. The research activity will be carried out in collaboration with the TeMa company (https://temasrl.net/), and systems engineering researchers at Dibris (Prof. Simona Sacone). Candidates will carry out a doctoral program in close collaboration between university and industry and they will be supported by an academic supervisor and a supervisor from the company's R&D department. Candidates are required to have a solid background in systems engineering. The PhD program includes training activities on advanced topics, research and technology transfer activities on themes of interest for the company R&D department and for the academic supervisor. During the PhD program, candidates will have the opportunity to attend PhD seminars, workshops, and schools organized by the CSSE PhD board and national and international workshops and conferences.
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