Organization

Mykola Pechenizkiy

TU Eindhoven, The Netherlands

Mykola Pechenizkiy is Professor at the Department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e). He is Director of the Center for Safe AI, where he leads research on addressing technical and socio-technical challenges of AI reliability, AI fairness, AI compliance. He holds the Data Mining chair that is part of the Data and AI cluster.

Stiven Schwanz Dias

Embraer S.A., Brazil

Stiven is a Senior Data Fusion Research Engineer at Embraer S.A. and a Visiting Fellow at the department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e). His main research interests include distributed Bayesian estimation techniques and lifelong learning. His main focus in the industry is on multi-object, multi-sensor tracking systems for coastal surveillance applications and multi-sensor navigation systems for autonomous vehicles.

André Carlos Ponce de Leon Ferreira de Carvalho

University of São Paulo, Brazil

André is a Full Professor at the University of São Paulo, USP. He is an ad hoc reviewer for several national and international research support foundations. He has experience in Computer Science, with an emphasis on Machine Learning, Data Mining and Data Science, working mainly on the following topics: novelty detection, meta-learning, data preprocessing and metaheuristics, with applications in Bioinformatics, Engineering, Finance, Medicine and Environment. He is the director of the Center for Machine Learning in Data Analysis at USP.

Fabio Gagliardi Cozman

University of São Paulo, Brazil

Fabio is a Full Professor at Escola Politécnica (Poli), Universidade de São Paulo (USP), Director of the Center for Artificial Intelligence at USP, and researcher (level 1C-CNPq/Pq) with an interest in machine learning and knowledge/uncertainty representation. He has served, amongst other duties, as Program and General Chair of the Conference on Uncertainty in Artificial Intelligence, Area Chair of the International Joint Conference on Artificial Intelligence, and Associate Editor of the Artificial Intelligence Journal, the Journal of Artificial Intelligence Research, and the Journal of Approximate Reasoning. He chaired the Special Committee on Artificial Intelligence of the Brazilian Computer Society, and received the Prize for Scientific Merit in Artificial Intelligence by that society.

João Vinagre

European Centre for Algorithmic Transparency, Spain

João Vinagre is a researcher at the Joint Research Centre (JRC) of the European Commission, where he integrates the team of the European Centre for Algorithmic Transparency (ECAT). His research is focused on recommender systems, under perspectives relevant for the European Strategy for the Digital Economy, with emphasis on the Digital Services Act.

Thiago D. Simão

TU Eindhoven, The Netherlands

Thiago is an Assistant Professor in the Department of Mathematics and Computer Science at TU/e. The main motivation for his research revolves around making AI techniques more reliable, to enable their deployment in real-world applications. He is currently interested in safe reinforcement learning, a research topic concerned with problems where a minimum performance must be guaranteed and catastrophic events must be avoided.

Albert Bifet

University of Waikato, New Zealand

Albert is a Professor of AI, Director of the Te Ipu o te Mahara AI Institute at the University of Waikato and Co-chair of the Artificial Intelligence Researchers Association (AIRA). His research focuses on Artificial Intelligence, Big Data Science, and Machine Learning for Data Streams. He is leading the TAIAO Environmental Data Science project and co-leading the open source project MOA Massive On-line Analysis. He is the co-author of a book on Machine Learning from Data Streams published at MIT Press. He is one of the winners of the best paper award at the ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT) 2023, and he is the general co-chair of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 2024.

Deepak Padmanabhan

Queen's University Belfast, United Kingdom

Deepak is a Senior Lecturer in Computer Science at School of EEECS. His background is in Artificial Intelligence, Machine Learning and Data Analytics. His current research interests are in the ethics of AI, and understanding how AI relates to extant inequalities within society, and places emphasis on embedding such considerations within AI algorithm development. He has a particular interest in exploring pathways for radically reimagining AI for responsible usage within public sector contexts, and understanding the ways in which AI can be reformed for the gig sector to place workers’ interests as the focal point. He has published 100+ papers, authored/edited three books, and is a Senior Member of the IEEE and ACM. He has a keen interest in public communication and is an adjunct faculty member at IIT Madras, India. 

Yali Du

King's College London, United Kingdom

Dr Yali Du is a Senior Lecturer (Associate Professor) in AI at King’s College London, and a Turing Fellow at The Alan Turing Institute. She leads the Cooperative AI Lab. Her research aims to enable machines to exhibit cooperative and safe behaviour in intelligent decision making tasks. Her work focuses on reinforcement learning and multi-agent cooperation, with topics such as generalization, zero-shot coordination, evaluation of human and AI players, and social agency (e.g., human-involved learning, safety, and ethics). She was chosen for the AAAI New Faculty Highlights award (2023), Rising Star in AI 2023. She has given tutorials on cooperative multi-agent learning at ACML 2022 and AAAI 2023. She serves as the editors for Journal of AAMAS and IEEE Transactions on AI, Area Chair for NeurIPS 2024. She also serves in organising committee for AAMAS 2023 and NeurIPS 2024. Her research is also supported by the Engineering and Physical Sciences Research Council(EPSRC) and AI Safety Insitute (AISI).

Carlos Mougan

AI Office at the European Commission, Spain

Carlos is a Technical Staff of the AI Office (A3 AI Safety) at the European Commission. He has worked around the different steps of the ML pipeline: data collection, data quality, preprocessing, modeling, and monitoring. At the moment, his main research focus is on model monitoring and AI alignment.