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

Computer Science Workshop by DOCS

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 diversityserendipityfairness, 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. BixioGiorgio DelzannoS. ReboraMRulli
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. AnconaL. BenvenutoG. DelzannoG. Gambari:
Flow Programming: A Flexible way to bring the Internet of Things into the Lab. 
UMAP  2020: 155-158 

[4] Angelo FerrandoGiorgio Delzanno
Incrementally Predictive Runtime Verification. 
CILC 2021: 92-106

[5] S. ConchonG. DelzannoA. Ferrando:
Declarative Parameterized Verification of Distributed Protocols via the Cubicle Model Checker. 
Fundam. Informaticae 178(4): 347-378 (2021) 

[6] Sylvain ConchonGiorgio DelzannoArnaud 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

Title: Advances in Geometry Processing and Discrete Differential Geometry
Keywords: Geometry Processing, Geometric Modeling, Computer graphics
Curriculum: Computer Science
Abstract:
The research will address the computational resolution of fundamental geometric problems, with possible applications to computer graphics, geometric modeling and bio-printing. Developments may concern different ongoing projects such as: vector graphics on surfaces; support to collaborative modeling; meshing for FEM; animation; simulation of cell systems for bio-printing; etc. The candidate will be required to learn the fundamentals of geometric modeling and geometry processing, and the main concepts and computational techniques in discrete differential geometry. 
 
References
 
C. Mancinelli,  G. Nazzaro, F. Pellacini, E. Puppo, 2022,
b/Surf: interactive Bézier splines on surfaces,
IEEE Trans. on Visualization and  Computer Graphics,
DOI: 10.1109/tvcg.2022.3171179
 
G. Nazzaro, E. Puppo, F. Pellacini, 2022,
geoTangle: Interactive Design of Geodesic Tangle Patterns on Surfaces,
ACM Trans. on Graphics, 41(2), pp.12:1--12:17.
 
C. Mancinelli, M. Livesu, E. Puppo, 2021,
Practical Computation of the Cut Locus on Discrete Surfaces,
Computer Graphics Forum, 40(5):261-273.
 
F. Corda,  J. M. Thiery,  M. Livesu,  E. Puppo,  T. Boubekeur,  R. Scateni, 2020,
Real Time Deformation with Coupled Cages and Skeletons,
Computer Graphics Forum, 39(6):19-32.
 
Livesu, M., Pietroni, N., Puppo, E., Sheffer, A., Cignoni, P., 2020,
LoopyCuts: Practical Feature-Preserving Block Decomposition,
ACM Trans. on Graphics (Siggraph 2020), 4(390).


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.

 

 

 

The research areas of the Computer Science Curriculum are describe in the mission page http://phd.dibris.unige.it/csse/

Specific research projects of Dibris research groups:
Specific Research Themes 2022

The grants funded on the PNRR project D.M. 352 are related to the following specific themes
Industrial Research Themes

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. 

 

 

CSSE PhD Program, Admission Procedure July 2022

Candidates admitted to the online interviews scheduled from July 26 to July 29, 2022 
 
Systems Engineering

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:

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