all candidates in alphabetical order
Candidates for ENNS President
Igor Farkaš, Slovakia
Bio: Igor Farkaš holds a PhD degree in applied informatics and MSc degree in technical cybernetics, both from the Slovak University of Technology in Bratislava. In 2000-2003 he was a postdoc with the Department of Psychology, University of Richmond, VA. Since 2003 he has been affiliated with the Department of Applied Informatics of the Faculty of Mathematics, Physics and Informatics, Comenius University Bratislava with full professorship since 2014 and serving as department chair in 2015-2022. He leads the Cognition and Neural Computation research group, and coordinates the Centre for Cognitive Science. Igor Farkaš received a Fulbright scholarship (University of Texas in Austin), and Humboldt scholarship (Saarland University, Germany). He has conducted research in ANN modeling with the focus on cognitive robotics and language learning, but also computational analyses of neural network models (deep networks, echo state networks), and reinforcement learning. He has co-authored more than 130 peer-reviewed publications. He coordinates the Middle European interdisciplinary master program in Cognitive Science in Bratislava. He has supervised 15 doctoral students. As a prominent Slovak expert on ANN he received Scientist of the Year 2023 award and ESET Science Award in 2024. Within the ENNS he is currently serving the second term as an executive committee member. He had been the main program chair of ICANN 2020 and 2021, honorary chair in 2022 and workshop organizer in last years.
Alessio Micheli, Italy
Bio: Alessio Micheli is Full Professor at the Department of Computer Science of the University of Pisa, where he is the head and scientific coordinator of the Computational Intelligence & Machine Learning Group (CIML), part of the CAIRNE.eu Research Network. His research interests include machine learning, neural networks, deep learning, learning in structured domains (sequence, tree, and graph data), recurrent and recursive neural networks, reservoir computing, and probabilistic and kernel-based learning for non-vectorial data, with a particular focus and pioneering works on efficient neural networks for learning from graphs. The applications area includes Health and Bio/ChemInformatics. In these research areas, he has authored (at 2025) over 250 articles, with an h-index of 40 and a total of over 8200 citations (Scholar, August 2025). Since 2003, he has been teaching courses on Artificial Intelligence, Machine Learning and Computational Neuroscience. Prof. Micheli is the national coordinator of the “Italian Working group on Machine Learning and Data Mining” of the Italian Association for Artificial Intelligence and he has been co-founder/chair of the IEEE CIS Task Force on Reservoir Computing. He is an elected member of the Executive committee of the European Neural Network Society – ENNS. He serves as an Associate Editor for Neural Networks and IEEE Transactions on Neural Networks and Learning Systems.
Candidates for the ENNS ExCom
Angelo Cangelosi, UK
Bio: Angelo Cangelosi is Professor of Machine Learning and Robotics at the University of Manchester (UK) and co-director of the Manchester Centre for Robotics and AI. He also is Turing Fellow at the Alan Turing Institute London, Visiting Professor at Hohai University, and Visiting Distinguished Fellow at AIST-AIRC Tokyo. His research interests are in cognitive and developmental robotics, neural networks, language grounding, human robot-interaction and trust, and robot companions for health and social care. Overall, he has secured over £35m of research grants as coordinator/PI. Cangelosi has produced more than 300 scientific publications. Cangelosi is Editor-in-Chief of the journals Interaction Studies and IET Cognitive Computation and Systems, and in 2015 was Editor-in-Chief of IEEE Transactions on Autonomous Development. He has chaired numerous international conferences, including recently ICANN2022 Bristol, and ICDL2021 Beijing. His book “Developmental Robotics: From Babies to Robots” (MIT Press) was published in January 2015, and recently translated in Chinese and Japanese. His latest book “Cognitive Robotics” (MIT Press), coedited with Minoru Asada, was recently published in 2022.
Matthias Kerzel, Germany
Bio: Matthias Kerzel received his MSc and PhD in computer science from the University of Hamburg, Germany. His research focuses on neural network architectures, developmental neurorobotics, hybrid neurosymbolic architectures, explainable AI and human-robot interaction. He is currently a postdoctoral research and teaching associate and a technical manager for neurorobotics in the Knowledge Technology Group at the University of Hamburg. He taught lectures on Knowledge Processing in Intelligent Systems, Neural Networks and Bio-inspired Artificial Intelligence and has been part of the international and interdisciplinary Transregional Collaborative Research Centre on “Crossmodal Learning” as well as many other neural networks research and industry projects. Matthias Kerzel has co-authored over 70 peer-reviewed publications and has served as the ENNS Secretary management since 2020. He has been very active on the ENNS board from 2022 to 2025, assisted with the strategic ICANN Core submission and contributed to the organising committees of numerous ICANN conferences. He is also a regular organiser of ICANN workshops.
Alessandra Lintas, Switzerland
Bio: Alessandra Lintas received the M.S. degree in Chemical and Pharmaceutical Technology from the University of Sassari, Italy, in 2004, and the Ph.D. degree by the University of Cagliari in 2007, with a dissertation on reward systems and dynamics. She was awarded postdoctoral fellowships with the Geneva University Neurocenter, Switzerland, the Schulich School of Medicine at Western University, Canada and the Department of Medicine at the University of Fribourg. She is currently a Principal Investigator at the NeuroHeuristic Research Group, University of Lausanne, Switzerland. Her main research activity is focused on studying the brain networks involved in decision-making processes in experimental and simulated models. She served as secretary of ENNS for two years (2018-2019) and as deputy Treasurer of ENNS for the term 2017-2019.
Kristína Malinovská, Slovakia
Bio: Kristína Malinovská is an assistant professor at the Comenius University in Bratislava. She acquired her Ph.D. in computer science in 2014 at the CU and did her postdoc at CIIRC CTU in Prague with the Robotics and machine perception department. Her research interests are in foundations artificial neural networks (bio-inspired learning, novel neural network architectures, advances and explainability in deep learning, etc.), and in cognitive robotics and human-robot interaction. She teaches programming, computational intelligence, computational neuroscience and other courses in the MEi:CogSci master’s program in cognitive science in Bratislava. Kristína Malinovská was involved in the organization of the ICANN conference from 2020 on. She was the head of the local organizing committee of ICANN 2021 and one of the main program chairs of ICANN 2024. She has been very active on the ENNS board from 2022 to 2025, helping in ENNS communication duties, conference awards, as well as with the strategic ICANN Core submission. She is also a regular organizer of ICANN workshops.
Nicolò Navarin, Italy
Bio: Nicolò Navarin is an associate professor in Computer Science at the Department of Mathematics, University of Padova, Italy. He got his Ph.D. in computer science from the University of Bologna, Italy, in 2014. His research experience includes visiting positions at the University of Freiburg, Germany, the Università della Svizzera Italiana, Lugano, Switzerland, and 3IA Côte d’Azur, Sophia Antipolis, France. He has been a research fellow at the University of Nottingham, UK, and assistant professor at the University of Padua. Prof. Navarin’s research interests are in the field of machine learning, including kernel methods and neural networks for structured data, and applications to bioinformatics, business process mining, computer vision, and computational psychology. Prof. Navarin has been actively involved in the organization of several conferences (INNS Big Data and Deep Learning 2019, International Conference on Process Mining 2020, IEEE Symposium Series in Computational Intelligence 2021, IEEE World Congress on Computational Intelligence 2022, International Joint Conference on Neural Networks 2025). He is a member of the International Neural Network Society and a senior member of the IEEE, Computational Intelligence Society.
Sebastian Otte, Germany
Bio: Sebastian Otte is professor at the Institute for Robotics and Cognitive Systems at the University of Lübeck, Germany, and the head of the Research Group for Adaptive Artificial Intelligence. From 2013 to 2017, Sebastian was a PhD student in AI and robotics at the Eberhard Karls University of Tübingen. From 2017 to 2023, he conducted postdoctoral research in the Neuro-Cognitive Modeling Group at the University of Tübingen. In 2020, he served as a substite professor for the W3 chair of Distributed Intelligence at the University of Tübingen. From 2022 to 2023, supported by a Feodor Lynen Research Fellowship from the Alexander von Humboldt Foundation, he worked as a visiting scientist at the Centrum Wiskunde & Informatica (CWI) in Amsterdam, Netherlands. In 2023, Sebastian assumed his current position as a professor at the University of Lübeck. Since 2019, Sebastian has been ENNS executive board member and was part of the organization team of the virtual ICANN 2021. Since 2023, has serves a communication chair for the ENNS.
Marcello Sanguineti, Italy
Bio: Marcello Sanguineti (Chiavari, Italy, 1968) is Full Professor of Operations Research at the University of Genova, Italy. He holds a Ph.D. degree in Electronic Engineering and Computer Science from the University of Genova. He is affiliated with CNR – National Research Council of Italy, Guest Scholar at IMT – School for Advanced Studies, Lucca, and has been Research Associate with IIT – Italian Institute of Technology. He has co-authored over 200 research papers in archival journals, book chapters, and international conference proceedings. His research operates at the meeting point between machine learning and optimisation. His main interests are: mathematical foundations of neurocomputing, neural networks for optimisation, infinite-dimensional programming, game-theoretical models, and affective computing. He has coordinated several national and international research projects on the approximate solution of optimisation problems via machine-learning-based approaches. Since thirty years he is member of the Program Committees of some of the main conferences in his research areas and has been member of the PC of ICANN 2025. He is Area Editor of the journal Soft Computing and has been Guest Editor of the IEEE Transactions on Neural Networks and Learning Systems, Computers and Operations Research, and Computational Management Science. He is member of the Editorial Boards of Neural Networks, IEEE Transactions on Neural Networks and Learning Systems, Neurocomputing, and Neural Processing Letters.
Ausra Saudargiene, Lithuania
Bio: Ausra Saudargiene is Professor at Neuroscience Institute, Lithuanian University of Health Sciences, Lithuania, and Professor at the Department of Informatics, Vytautas Magnus University, Kaunas, Lithuania. She received PhD in artificial neural networks from the Institute of Mathematics and Informatics, Vilnius University, Lithuania, and later got extensive training in neuroinformatics and neuroscience in Europe, Israel, Japan, USA and Canada. Her research interests are deep learning in neuroscience and medicine, brain-inspired artificial intelligence algorithms, and she leads international scientific projects on computational models of learning and memory in the brain. She is a member of the International Neuroinformatics Facility (INCF) Training and Education Committee since 2016. She has a long-lasting experience in organizing scientific events in Europe, and initiated and organized a series of Baltic-Nordic Schools on Neuroinformatics and Neuroscience BNNI 2013-2022 in Lithuania, Finland, Sweden, Estonia, Latvia, Poland, Germany promoting multidisciplinary research in neuroscience.
Igor Tetko, Germany
Bio: Igor Tetko received MSc degree from Moscow Institute of Physics and Technology in physics computer sciences and PhD from the Ukrainian Academy of Sciences. He did postdoc in neuroinformatics at the University of Lausanne and received habilitation in cheminformatics from the University of Strasbourg. He is Chemoinformatics group leader at Helmholtz Munich, CEO of BigChem GmbH. He coordinates Horizon Europe Marie Skłodowska-Curie Doctoral Network “Explainable AI for molecules “AiChemist” and was General Chair of ICANN2019 & ICANN2024 in Munich and in Lugano, respectively as well as Program Chair of ICANN2025. His research interests are in development and application of machine learning in chemistry. His Google Scholar H-index is 66.
Michael Wand, Switzerland
Bio: Michael Wand is Senior Researcher at IDSIA USI-SUPSI (Dalle Molle Institute for Artificial Intelligence, affiliated with both the University (USI) and the University of Applied Sciences and Arts (SUPSI) of Southern Switzerland) in Lugano, Switzerland. He received his Diploma Degree in Mathematics and his PhD an Computer Science from Karlsruhe Institute of Technology in Germany, where he worked with Prof. Tanja Schultz on an innovative speech prosthesis based on facial muscular activity. He joined the IDSIA in 2014 as Marie Curie postdoctoral fellow; in 2019 he was named Senior Researcher, since 2021 he is also affiliated with the SUPSI Institute for Digital Technologies for Personalized Healthcare. His research interests lie in the application of Machine Learning and Artificial Intelligence to challenging real-world problems, specifically tasks involving continuous or real-time interaction with users. A major area where such methods are utilized is biosignal processing, both in medicine and rehabilitation and for advanced user interfaces. Michael Wand has acquired several national and international projects and has co-authored more than 60 peer-reviewed publications (h-index: 24); in addition to his research he teaches topics in Machine Learning both at SUPSI and USI, where he also supervises his PhD students. He was the main organizer and Program Chair of the ICANN 2024 conference, which was held on the USI-SUPSI premises in Lugano in September 2024.
Roseli Wedemann, Brazil
Bio: Roseli S. Wedemann has accomplished undergraduate and masters studies in physics and doctoral research in computer science (area of distributed algorithms), at the Federal University of Rio de Janeiro. She is currently a professor of the Institute of Mathematics of the University of the State of Rio de Janeiro. Her research and publications have recently focused on theoretical and computational models of complex systems, with emphasis on computational neuroscience and artificial neural networks, applying theoretical tools from statistical mechanics. She teaches undergraduate courses and participates in the Computational Science post-graduate program of her university, where she teaches and supervises young researchers. She coordinated the development of the project for the creation of this Computational Science program and has headed the program from 2014 to 2017. Roseli has participated regularly in the ICANN conferences, frequently as a member of the program committee, and has organized a workshop entitled “Workshop on Conscious and Unconscious Mental Functions” at ICANN 2012. She served as guest editor of the Special Issue “Selected Papers from the 26th International Conference on Artificial Neural Networks – ICANN 2017”, MDPI Publishers – Journal Entropy, 2018. She is currently an elected member of the Executive Committee of the European Neural Network Society (ENNS). She is also a reviewer for various renowned scientific journals, for various Brazilian science funding agencies, and participated in the program committee of various conferences.