Invited Speakers

Prof. Sotirios Tsaftaris is currently Chair (Full Professor) in Machine Learning and Computer Vision at the University of Edinburgh. He also holds the Canon Medical/Royal Academy of Engineering Research Chair in Healthcare AI. He is an ELLIS Fellow of the European Lab for Learning and Intelligent Systems (ELLIS) of Edinburgh’s ELLIS Unit. Since 2023 he is a visiting researcher with Archimedes RC a research centre of excellence in AI in Athens, Greece. Between 2016 and 2023 he was a Turing Fellow with the Alan Turing Institute. Prof. Tsaftaris is also a Murphy Fellow and a Fellow of the Alexander S. Onassis Public Benefit Foundation. He received the M.Sc. and Ph.D degrees in Electrical and Computer Engineering from Northwestern University, Evanston, IL, in 2003 and 2006, respectively, and the Diploma degree in Electrical and Computer Engineering from the Aristotle University of Thessaloniki, Thessaloniki, Greece, in 2000.

He has published extensively, particularly in interdisciplinary fields, with more than 180 journal and conference papers in his active record, with a variety of co-authors and collaborators. His work has received several accolades, such as Best Paper Award (STACOM 2017), twice a Magna Cum Laude Award (ISMRM), a finalist for the Early Career Award (SCMR, 2011; SCMR, 2019 (Chartsias as PhD student)), and has had his work appear in journal covers and attract significant media coverage. While he has served in many technical program committees of international conferences, and he actively reviews papers for several prestigious international journals, most notably he currently is an Associate Editor (AE) for the IEEE Transactions on Medical Imaging. He served as an AE for IEEE Journal of Biomedical and Health Informatics (2011-2021) and Elsevier DSP (2014-2018). He was tutorial chair for ECCV 2020. He was Doctoral Symposium Chair for IEEE ICIP 2018 (Athens). He has served as area chair for CVPR 2021, MICCAI 2018 (Granada), ICME 2018 (San Diego), ICCV 2017 (Venice), MMSP 2016 (Montreal), VCIP 2015 (Singapore). He has also coorganized workshops and tutorials for ECCV (2020, 2014), CVPR (2019), ICCV (2017), BMVC (2015), and MICCAI (2016, 2017, 2021).

Dr Julien Le Kernec is currently a Senior Lecturer with the School of Engineering in the Autonomous Systems and Connectivity Group, University of Glasgow. He is also an adjunct Associate Professor at the University Cergy-Pontoise, France, in the ETIS (Information and Signal Processing group). Previous to this, he held a post-doctoral position with the Kuang-Chi Institute of Advanced Technology, Shenzhen, China, from 2011 to 2012 and he was a Lecturer at the Department of Electrical and Electronic Engineering at the University of Nottingham Ningbo China, from 2012 to 2016.  Dr Le Kernec received his B.Eng. and M.Eng. degrees in Electronic Engineering from the Cork Institute of Technology, Ireland, in 2004 and 2006, respectively, and his Ph.D. degree in Electronic Engineering from the University Pierre and Marie Curie, France, in 2011. In 2022, he received "Habilitation a Diriger des Recherches" from University Cergy-Pontoise, France. 

His research interests include radar system design, software-defined radio/radar, signal processing, and health applications. Dr Le Kernec has over 130 publications in journals (IEEE sensors, IEEE Signal processing Magazine, IEEE Journal of Biomedical and Health Informatics, Nature Scientific Reports), Conferences (such as IET International Radar Conferences, IEEE Radar Conferences), book chapters, patents and databases.

Dr. Yves-Alexandre de Montjoye is an Associate Professor of Applied Mathematics and Computer Science at Imperial College London where he heads the Computational Privacy Group. He is currently a Special Adviser on AI and Data Protection to EC Justice Commissioner Reynders and a Parliament-appointed expert to the Belgian Data Protection Agency. In 2018-2019, he was a Special Adviser to EC Commissioner Vestager for who he co-authored the Competition policy for the digital era report. He is affiliated with the Data Science Institute and Department of Computing. He is previously a postdoctoral researcher at Harvard working with Latanya Sweeney and Gary King and he received his PhD from MIT under the supervision of Alex "Sandy" Pentland.

His research aims at understanding how the unicity of human behavior impacts the privacy of individuals in large-scale metadata datasets. His work has been covered in The New York Times, BBC News, CNN, Wall Street Journal, Harvard Business Review, Le Monde, Die Spiegel, Die Zeit, El Pais, and in reports of the World Economic Forum, United Nations, OECD, FTC, and the European Commission, as well as in my talks at TEDxLLN and TEDxULg. He recently wrote a white paper for Brookings on the use and privacy metadata as well as op-eds for the World Economic Forum, Christian Science Monitor, and Le Monde. He worked for the Boston Consulting Group and acted as an expert for the Bill and Melinda Gates Foundation and the United Nations. He was recently named an Innovator under 35 for Belgium (TR35). He was a fellow of the ID³ Foundation, the B.A.E.F. Foundation, and a research associate at Data-Pop. 

Dr. Borja de Balle Pigem, Borja Balle is a Staff Research Scientist at Google DeepMind. His current research focuses on differentially private training for large-scale models, privacy auditing to identify implementation bugs in differentially private mechanisms, distributed differential privacy mechanisms, and inference-time privacy in LLM-based systems. Before joining DeepMind in 2019, Borja was Applied Scientist at Amazon Research Cambridge, Lecturer in Data Science at Lancaster University, and post-doctoral fellow at McGill University. Borja served as workshops chair for NeurIPS 2015, and has co-organized multiple international workshops on privacy in machine learning (NeurIPS 2021, 2020, 2019, CCS 2019, ICML 2018, DALI 2017, NeurIPS 2016) and spectral learning techniques (ICML 2014, NeurIPS 2013, ICML 2013). His research has been recognized with several awards, including distinguished paper awards at USENIX 2023 and CCS 2023.

Dr. Jindong Gu is a Senior Research Fellow at the University of Oxford and a member of the Torr Vision Group. He also works partially at Google DeepMind as a faculty researcher on the Gemini Safety team. Prior to this, he received his Ph.D. degree from the University of Munich in 2022. He has experience working at Google Brain, Microsoft Research, and Tencent AI Lab.

His research goal is to build responsible AI. Specifically, he is interested in the interpretability, robustness, privacy, and safety of visual perception, foundation model-based understanding and reasoning, robotic policy and planning, and their fusion towards general intelligence systems. In this research area, he has published 42 papers in top AI conferences, including NeurIPS, ICLR, ICML, CVPR, ICCV, ECCV, ACL, and others. He also regularly serves as a program committee member and area chair at these conferences.