Lecturers

Biography

My research interests are in the areas of autonomous agents, multi-agent interaction, reinforcement learning, and game theory, with a focus on sequential decision making under uncertainty. The long-term goal of my research is to create intelligent autonomous agents capable of robust interaction with other agents to accomplish tasks in complex environments.

Previously, I was a postdoctoral fellow at the University of Texas at Austin in Peter Stone’s group. I obtained PhD and MSc degrees in Artificial Intelligence from the University of Edinburgh, and a BSc degree in Computer Science from Technical University of Darmstadt. I received personal fellowships from the Royal Academy of Engineering, the Royal Society, the Alexander von Humboldt Foundation, and the German Academic Scholarship Foundation (Studienstiftung). In 2022, I was honoured to be nominated for the IJCAI Computers and Thought Award.

Google Scholar | Google Patents

I am co-author of the MIT Press textbook Multi-Agent Reinforcement Learning: Foundations and Modern Approaches with Filippos Christianos and Lukas Schäfer.

Biography

Mikhail Belkin received his Ph.D. in 2003 from the Department of Mathematics at the University of Chicago. His research interests are in theory and applications of machine learning and data analysis. Some of his well-known work includes widely used Laplacian Eigenmaps, Graph Regularization and Manifold Regularization algorithms, which brought ideas from classical differential geometry and spectral analysis to data science. His recent work has been concerned with understanding remarkable mathematical and statistical phenomena observed in deep learning. This empirical evidence necessitated revisiting some of the basic concepts in statistics and optimization. One of his key recent findings is the “double descent” risk curve that extends the textbook U-shaped bias-variance trade-off curve beyond the point of interpolation.

Mikhail Belkin is a recipient of a NSF Career Award and a number of best paper and other awards. He has served on the editorial boards of the Journal of Machine Learning Research, IEEE Pattern Analysis and Machine Intelligence and SIAM Journal on Mathematics of Data Science.

Biography

Giuseppe De Giacomo is a Professor of Computer Science in the Department of Computer Science at the University of Oxford. He has previously been a Professor at the Department of Computer, Control, and Management Engineering of the University of Rome “La Sapienza”. His research spans theoretical, methodological, and practical aspects of Artificial Intelligence and Computer Science, with major contributions to Knowledge Representation, Reasoning about Actions, Generalized Planning, Autonomous Agents, Temporal Synthesis and Verification, Service Composition, Business Process Modeling, and Data Management and Integration. He is a Fellow of AAAI, ACM, and EurAI. He was awarded an ERC Advanced Grant for the project WhiteMech: White-box Self-Programming Mechanisms. He served as Program Chair of ECAI 2020 and KR 2014. He is a member of the Board of EurAI and chairs the steering committee of EurAI’s annual summer school ESSAI.

Biography

Director, Research Scientist Meta Superintelligence Labs.Prior to joining Facebook in Spring 2018, he received the PhD degree in computer science from TU Graz, and spent time as a visiting researcher at the York University Toronto and the University of Oxford. He is the recipient of a DOC Fellowship of the Austrian Academy of Sciences and his PhD thesis was awarded with the Award of Excellence for outstanding doctoral thesis in Austria. His main areas of research include the development of effective representations for video understanding. He aims to find solutions for problems that are grounded in applications such as recognition and detection from video.

https://scholar.google.com/citations?user=UxuqG1EAAAAJ&hl=de

Biography

Hi, I am a staff research scientist at Google DeepMind. I am the research lead for a team of 10+ technical staff working on Gemini’s adversarial security and privacy evaluations and post-training. My research interests lie at the intersection of AI, Security and Privacy. See my Google Scholar profile for a list of recent publications, my CV, or feel free to reach out to me.

Biography

Abdelsalam Helal (aka: Sumi Helal) is a full Professor in the Computer Science and Engineering Department at the University of Bologna. Prior to joining UNIBO, he spent 26 years as associate and then full processor in the Computer & Information Science and Engineering Department at the University of Florida. At UF, he directed the Mobile and Pervasive Computing Laboratory and co-founded and directed the Gator Tech Smart House –a real-world deployment project. His active areas of research focus on architectural and programmability aspects of the Internet of Things (IoT), service-oriented IoT architectures, IoT edge intelligence, and pervasive/ubiquitous systems and their human-centric applications, especially in the Digital Health area. Helal is also a technologist at heart who founded several successful ventures in the areas of IoT and Digital Health. His research was licensed by the top multinational tech industry including Google, Apple, Samsung, Bosch, Siemens, Nokia, Ericsson, AMAZON, T-Mobile, Verizon, others. Prof. Helal is a Fellow of the ACM, IEEE, AAAS, AAIA, and IET. He is member of Academia Europaea, and the US National Academy of Inventors NAI. Go to the Curriculum vitae

Biography

Since June 2023,  Albert Q. Jiang has been a Research Scientist at Mistral AI, where his team focuses on the science and infrastructure of reasoning. His long-term research objective is the development of a mathematical superintelligence that is safe and aligned by construction. In pursuit of this goal, Albert has contributed to several frontier projects in large language models and reasoning systems, including pretraining data initiatives such as Mixtral of Experts and Mistral 7B in 2023, mid- and post-training research with Mathstral in 2024, and large-scale reinforcement learning efforts through Magistral in 2025.

Albert completed his PhD at the University of Cambridge Computer Laboratory under the supervision of Mateja Jamnik and Wenda Li. His thesis was examined by Jeremy Avigad and Ferenc Huszár in October 2024, and he successfully passed with no corrections required.

His doctoral research focused on learning abstract mathematical reasoning with language models. His work explored the autoformalization of theorems and proofs, including the development of large parallel datasets for statement autoformalization such as Multilingual Mathematical Autoformalization (MMA). Albert also worked on integrating and improving premise selection tools using language models, studied human–AI interaction in mathematical problem-solving, and investigated mathematical conjecturing as a step toward more advanced forms of machine reasoning.

https://albertqjiang.github.io/

https://scholar.google.com/citations?user=Fe_RBHMAAAAJ&hl=en

Biography

I am a Research Scientist (Chargée de Recherche) in Machine Learning at INRIA, within the SODA team. My research lies at the intersection of statistical learning and trustworthy AI, with a focus on:

• Tabular foundation models, which unlock new possibilities through large-scale pretraining.
• Model auditing, to enhance the trustworthiness and reliability of machine learning systems.
• Learning from incomplete data, a challenge pervasive in fields like healthcare and social sciences.

I am passionate about using AI to tackle complex scientific and healthcare problems, ensuring that machine learning models are both powerful and reliable.

Biography

Bruno Lepri is a senior researcher at Fondazione Bruno Kessler, where he leads the Mobile and Social Computing (MobS) Lab within the Augmented Intelligence Center. He is also Chief Scientific Officer of Ipazia Spa, a startup focused on generative AI. He currently serves as co-director of the ELLIS Unit Trento—a joint research unit between FBK and the University of Trento dedicated to machine learning—and of the Center for Computational Social Sciences, also in collaboration with the University of Trento.
Since May 2024, he has been a member of the Scientific Committee of the National Tourism Observatory.
Previously, he was Chief AI Scientist at ManpowerGroup and a senior researcher affiliated with Data-Pop Alliance, a think tank on big data and sustainable development founded by the MIT Media Lab and the Harvard Humanitarian Initiative. In 2010, he received a Marie Curie Fellowship, which enabled him to work as a postdoctoral researcher at the MIT Media Lab for three years.
He holds a PhD in Computer Science from the University of Trento.
He also founded Profilio, a startup specializing in computational personality analysis with applications in marketing, human resources, and related fields.
His research interests include computational social sciences, cooperative AI and generative social agents, machine learning, urban computing, and new models for personal data sharing.

Biography

I am an Artificial Intelligence researcher that aims to make machines more adaptive and creative. My research is focused on computational evolution, deep learning, and crowdsourcing, with applications in robotics, video games, design, and art. I have recently been awarded an ERC Consolidator grant for my project GROW-AI: Growing Machines Capable of Rapid Learning in Unknown Environments.

My research asks questions such as: Can we create lifelong learning machines that continuously acquire new knowledge and skills? Can we grow machines that learn from and work together with humans to solve tasks that neither humans nor machines can solve by themselves?

I am a Professor at the IT University of Copenhagen and a Research Scientist at Sakana AI. I am also a co-founder of modl.ai, a company that develops AI techniques for game development. Our research has been covered in different news outlets such as Science, New Scientist, Wired, Popular Mechanics, The Register, and Popular Science.

https://scholar.google.com/citations?user=Tf8winBIYUsC&hl=en

Biography

Acting director of the Institute of Informatics and Telecommunications, NCSR Demokritos in Athens, Greece.
Voluntary chairman of the board of the Duchenne Data Foundation. Board member & Machine Learning advisor of Langaware Inc. Action editor of the Machine Learning journal.
Area Chair of ECAI 2025.

Biography

Panos Pardalos was born in Drosato (Mezilo) Argitheas  in 1954 and graduated from Athens University (Department of Mathematics).  He received  his  PhD  (Computer and Information Sciences) from the University of Minnesota.  He  is a Distinguished Emeritus Professor  in the Department of Industrial and Systems Engineering at the University of Florida, and an affiliated faculty of Biomedical Engineering and Computer Science & Information & Engineering departments.

Panos  Pardalos is a world-renowned leader in Global Optimization, Mathematical Modeling, Energy Systems, Financial applications, and Data Sciences. He is a Fellow of AAAS, AAIA, AIMBE, EUROPT, and INFORMS and was awarded the 2013 Constantin Caratheodory Prize of the International Society of Global Optimization. In addition, Panos  Pardalos has been awarded the 2013 EURO Gold Medal prize bestowed by the Association for European Operational Research Societies. This medal is the preeminent European award given to Operations Research (OR) professionals for “scientific contributions that stand the test of time.”

Panos Pardalos has been awarded a prestigious Humboldt Research Award (2018-2019). The Humboldt Research Award is granted in recognition of a researcher’s entire achievements to date – fundamental discoveries, new theories, insights that have had significant impact on their discipline.

Panos Pardalos is also a Member of several  Academies of Sciences, and he holds several honorary PhD degrees and affiliations. He is the Founding Editor of Optimization Letters, Energy Systems, and Co-Founder of the International Journal of Global Optimization, Computational Management Science, and Springer Nature Operations Research Forum. He has published over 600 journal papers, and edited/authored over 200 books. He is one of the most cited authors and has graduated 71 PhD students so far. Details can be found in www.ise.ufl.edu/pardalos

Panos Pardalos has lectured and given invited keynote addresses worldwide in countries including Austria, Australia, Azerbaijan, Belgium, Brazil,  Canada, Chile, China, Czech Republic, Denmark, Egypt, England, France, Finland, Germany, Greece, Holland,  Hong Kong, Hungary, Iceland, Ireland, Italy, Japan, Lithuania, Mexico, Mongolia, Montenegro, New Zealand, Norway, Peru, Portugal, Russia, South Korea, Singapore, Serbia, South Africa, Spain, Sweden, Switzerland, Taiwan, Turkey, Ukraine, United Arab Emirates, and the USA.