CSW 2024

Computer Science Workshop 2024

5th Edition

September 9th and 10th, 2024

Room 505, DIBRIS (Valletta Puggia), Università di Genova
Via Dodecaneso 35, Genoa
with the contribution of the University of Genoa

Flier

Motivation and goals

The DoCS group is pleased to announce that the 5th edition of the Computer Science Workshop will be held on September 9 and 10, 2024 at the Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS) at the University of Genoa.

Computer Science is a vast field of ever-increasing complexity, with new and exciting research challenges emerging at all times. Here at the University of Genoa we are involved in active areas of research such as Virtual and Augmented Reality, Multi-Agent systems, Data Management, Geometric Modeling, Security, Machine Learning, Programming Languages, Logic, Computer Vision, Software Engineering, Artificial Intelligence and more.

Every year, the Workshop provides its attendees with a broad perspective on the state of research in Computer Science, both at our department and abroad. It is an opportunity for students to connect with the research world, and for researchers to discover unexpected connections.

Keynotes

This year’s edition will feature six keynotes by distinguished researchers from Italian and foreign Universities:

Local Companies

As every year, the Workshop gives participants the opportunity to connect with local companies doing active research in Computer Science. Company employees will present challenging problems they encountered on their job, and the solutions they developed to tackle them.

Companies will also setup informative booths during lunch of the second day of the event.

PhD Poster Session

During lunch of the first day of the event, all Computer Science PhD students will have a poster session to present their work to participants and speakers.

Additional information

Participation is free of charge and open to everyone, but registration is required. Links for registration will be provided soon.

Lunch and coffee breaks will be offered to all participants.

Speakers

Map of Elections

Abstract

An election is a pair (C,V), where C is a set of candidates and V is a collection of voters, with preferences over the candidates, typically expressed as rankings. Such elections can, naturally, describe political elections, but they are also useful in modelling various sport competitions, participatory budgeting exercises, and many other tasks. In this talk I will present the “map of elections” framework, which is a general method of visualizing relations between elections (or, for that matter, any other compound objects). The talk will include general introduction to the topic of algorithmic analysis of elections and a collection of results, ranging from complexity theory and algorithm analysis, through discrete mathematics, to empirical observations and engineering solutions.

Piotr’s bio

Piotr Faliszewski is a professor of computer science at the AGH University in Krakow, Poland. His research is focused on computational social choice, a multidisciplinary research area that spans theoretical computer science, multiagent research, economics, operations research and other areas. Main themes of Piotr’s research include algorithms for computational analysis of candidate performance in elections, multiwinner and particpatory budgeting elections, and analysis of the space of elections. Piotr has published over 110 conference papers and 50 journal ones. He has received Friedrich Wilhelm Bessel Research Award from the Alexandra von Humboldta Foundation and currently is running an ERC Consolidator project PRAGMA.

Toward Egocentric Perception Powered Wearable Artificial Assistants

Abstract

Computer Vision and Artificial Intelligence have become more and more popular in the last years thanks to important technological and algorithmic breakthroughs. However, the access to AI is still limited to few individuals and mediated through devices, such as computers and smartphones, which detach humans from the reality.

To democratize access to AI, we need to build systems which can perceive the world as humans do, able provide them feedback and assist them while they are engaged in their daily activities.

In this talk, we’ll see how egocentric vision, i.e., the analysis of images, videos and multimodal data captured from the user’s point of view, can answer this call. We’ll discuss the challenges and opportunities provided by the field, point out the scientific contributions and the technological tools which make research in this field possible, showcase the main applications, and highlight the open research questions.

Giovanni’s bio

Giovanni Maria Farinella is a Full Professor, at the University of Catania, Italy. His research interests lie in the fields of Computer Vision and Machine Learning with focus on Egocentric Perception.

He is Associate Editor of the international journals IEEE Transactions on PAMI, PR, and IJCV. He regularly serves as Area Chair for CVPR/ICCV/ECCV/BMVC/WACV/ICPR and has been Program Chair of ECCV 2022.

Giovanni is part of the EPICKITCHENS and EGO4D teams. He founded and currently directs the International Computer Vision Summer School (ICVSS). He was awarded the PAMI Mark Everingham Prize 2017 and the Intel’s 2022 Outstanding Researcher Award.

Trustworthy Autonomous Systems?

Abstract

Autonomy represents a step-change in systems development and requires new approaches to systems architectures, systems analysis, and practical regulation. In this presentation, I will describe our approach utilising the modularity and heterogeneity of (software) components to provide hybrid agent architectures for autonomous systems.

This then allows for a range of verification techniques to be utilised in the different components, from formal verification applied to the core autonomous decision-making through to varieties of testing used in other parts of the system. An important component is the use of runtime verification (or runtime monitoring) to check for anomalies and violations.

This approach provides a basis for more reliable, transparent, trustworthy and verifiable autonomous (often robotic) systems. Finally, moving beyond trustworthiness to wider issues of responsibility, I will briefly discuss both sustainability and governance issues.

Michael’s bio

Michael Fisher is a Professor of Computer Science, and Royal Academy of Engineering Chair in Emerging Technologies, at the University of Manchester.

His research concerns autonomous systems, particularly verification, engineering, self-awareness, and trustworthiness, with applications robotics and autonomous vehicles. Increasingly, his work encompasses not safety but broader ethical issues such as sustainability and across these (AI, Autonomous Systems, IoT, Robotics, etc).

Fisher chairs the British Standards Institution Committee on Sustainable Robotics, co-chairs the IEEE Technical Committee on the Verification of Autonomous Systems, and is a member of both the IEEE P7009 Standards committee on ““Fail-Safe Design of Autonomous Systems”” and the Strategy Group of the UK’s Responsible AI programme.

He is currently on secondment (for 2 days per week) to the UK Government’s Department for Science, Innovation and Technology [https://www.gov.uk/dsit] advising on issues around AI and Robotics.”

From Research to Reality: Innovation in Educational Extended Reality

Abstract

In this talk, I will share my experience of research, development, and innovation in the area of educational extended reality. Improving human learning with educational software provides plenty of research challenges for academia in computer science, human-computer interaction, and educational sciences. Transferring the results of design-based research from academic to practice presents a different societal challenge. In this talk, I will present examples of my work in this field with examples from two international projects which both started with research and overtime transformed into software products that are developed and maintained by small open-source communities. The topics and questions I will touch upon are different in nature, including technical (virtual and augmented reality, cooperation technology, virtual humans, and artificial intelligence), human (user experience, learning, inclusion), organizational (software distribution, maintenance, approval), and business (technology transfer, sustainability, business models).

Mikhail’s bio

Dr. Mikhail Fominykh is a researcher at the Norwegian University of Science and Technology (NTNU), specializing in Augmented and Virtual Reality applications for learning. His research interests include advancing the multidisciplinary field of technology-enhanced learning, augmented and virtual reality application development for learning, educational authoring tools, management of research and development teams, innovation and product development in education, and technology transfer.

Mikhail is a member of the Innovative Immersive Technologies for Learning (IMTEL) research group at NTNU, mostly working on project coordination and managing technical software development activities. Mikhail has (co-)led several research-and-development projects, including several funded by the European Union. Mikhail is currently a project coordinator of two EU-funded projects Virtual Reality for Vocational Education and Training - VR4VET (2022-2024) and Augmented Reality Instructional Design for Language Learning - ARIDLL (2022-2025).

The Value of Studying Computer Graphics and Geometry Processing

Abstract

Is it worth studying and researching Computer Graphics and Geometry Processing in today’s world? The answer is a resounding yes. These disciplines are essential for creating and interacting with the stunning visual content that permeates our lives, from movies and video games to extended reality experiences. However, the significance of Computer Graphics and Geometry Processing extends far beyond entertainment. They play a crucial role in scientific visualization, enabling professionals to interpret complex data and structures in fields such as biology, environmental monitoring, and cultural heritage. Additionally, they enhance design and fabrication processes, from small-scale objects up to architectural projects. This talk will explore real-world problems in these fields, and discuss how addressing them requires a blend of concepts from computer science, geometry, optimization, numerical simulation, and artificial intelligence. We will examine the evolving landscape, particularly the increasing influence of AI, and discuss the open challenges and opportunities that lie ahead.

Daniela’s bio

Daniela Giorgi is a Senior Researcher at the Visual Computing Lab at CNR-ISTI (National Research Council of Italy, Institute of Information Science and Technologies). Her research interests include Computer Graphics; 3D Shape Analysis; Computational Topology; Artificial Intelligence; Geometric and 3D Deep Learning. She has authored more than 70 peer-reviewed papers published in international journals and conferences.

Currently, she is a Principal Investigator in the PNRR Extended Partnership FAIR - Future Artificial Intelligence Research, and a WP Leader for the Horizon Europe Project SUN (Social and hUman ceNtered XR). In 2022, she was elected President of the Italian Chapter of the European Association for Computer Graphics (Eurographics).

Large Language Models: The Italian Perspective

Abstract

As the field of Natural Language Processing (NLP) continues to evolve, the advent of large language models has revolutionized the way we approach language understanding and generation. With a growing focus on multilingual and cross-lingual applications, it is essential to explore the performance of these models in less-resourced languages, such as Italian. In this talk, I will provide an overview of the current state of large language models in the Italian context, discussing the challenges, opportunities, and future directions in this area. I will present our team’s research on the adaptation of pre-trained models to the Italian language and the results of their evaluation on a range of NLP tasks. The talk will also touch upon the potential applications of these models in analyzing gender biases in generated text. By sharing our experience and insights, we aim to contribute to a deeper understanding of the capabilities and limitations of large language models in the Italian language and to inspire further research in this exciting and rapidly evolving field.

Marco’s bio

Marco Polignano is an Assistant Professor in the computer science department at the University of Bari Aldo Moro, Italy, and a key member of the SWAP research group. He constantly contributes to cutting-edge AI, NLP, and Recommender Systems advancements. In 2018, he obtained a Ph.D. with a doctoral thesis titled “An affect-aware computational model for supporting decision-making through recommender systems”.

He served as a program committee member for several international conferences, including IJCAI, IUI, RecSys, and WWW. He served as an organizer for many workshops and has been among the chairs for the ACL 2021, EACL, and EMNLP 2024. He was part of the prestigious Marie Skłodowska-Curie (MSCA-RISE) fellowship program in 2016 and 2018. Recently, he actively worked on the FAIR (Future AI Research) national project. Within this context, he worked on LLaMAntino, an LLM for the Italian language. He is responsible for the “User Preferences and Personalization” task of the FAIR Transversal Project TP2 - Vision, Language, and Multimodal Challenges.