Rodrigo Agerri is a Ramon y Cajal Research Fellow (tenure-track) at the IXA Group, part of the HiTZ Centre of the University of the Basque Country, UPV/EHU). He has a PhD in Computer Science from City, University of London (2007) and has since been working on Natural Language Processing at several UK and Spanish institutions, including a two year stint at industry as research project director. He has been involved in over 20 research projects funded by the European Commission, UK research councils, and the Spanish Ministry of Science, among others. Currently he is Co-PI of “DeepReading”, a project funded by the Spanish Ministry of Science. His research is focused on semantic processing, information extraction and opinion mining, topics on which he has published more than 50 peer-reviewed papers at the main journals and conferences on Natural Language Processing. He is the creator and main developer of IXA pipes, a set of ready to use multilingual tools for linguistic processing used across academia, industry and administration. He is a PMC and committer in the OpenNLP project of the Apache Software Foundation and a mentor in the Google Summer of Code (GSOC).
Tim studied Chemistry at the University of Essen in Germany from 1995-2000 and obtained his PhD in 2003 from TU Berlin/MPI for Bioinorganic Chemistry. He started his independent academic career as a Lecturer in Interfacial & Analytical Science at the Department of Chemistry, Imperial College London, where he was promoted to Senior Lecturer and Reader in 2011 and 2014, respectively. In 2017, he took up a Chair of Physical Chemistry in the School of Chemistry at University of Birmingham. He is the School’s Director of Research & Knowledge Transfer since 2018. He is a Fellow of the Royal Society of Chemistry and the Secretary General of the International Society of Electrochemistry. His research interests cover a range of topics, including charge transport in single molecules and thermoelectrics; quantum tunnelling for sensing and sequencing; single-molecule sensing with nanopores and nanopipettes and the use and development of Machine Learning techniques for single-molecule science.
Dimitra is a Lecturer at the Department of Electrical and Electronic Engineering at City, University of London. Prior to her current appointment, she was a Postdoctoral Researcher in the Engineering Department and a Lecturer at Christ Church College at University of Oxford. Previously, she worked at the Smart Grid & Technology Department in Commonwealth Edison (ComEd) - a unit of Exelon Corp. (Chicago, Illinois, U.S.) that provides service to approximately 3.8 million customers. She was awarded a Ph.D. and a M.S. in Electrical and Computer Engineering from University of Illinois at Urbana-Champaign in 2014 and 2011, respectively. She received her undergraduate degree in Electrical and Computer Engineering from National Technical University of Athens, Greece in 2009. Her research lies on the interface of power and energy systems, decision and control, economics and energy policy, and machine learning for energy management applications.
I am a PhD candidate in mathematics, supervised by Mark Broom and Eduardo Alonso. My research is on the mathematical foundations of artificial intelligence and machine learning, where I focus on learning in networks of interacting agents. I approach this question from the perspectives of evolutionary game theory, dynamic systems and Markov chains, in order to obtain convergence and optimality proofs for learning algorithms. Prior to joining City, University of London, I obtained a Diplom in mathematics from the University of Konstanz, Germany, and a BA in economics from the University of St. Gallen, Switzerland.
Mark Broom obtained a BA (Hons) in Mathematics from the University of Oxford in 1989, followed by an MSc in Statistics (1990) and a PhD in Mathematics (1993) at the University of Sheffield. Mark was appointed as Professor of Mathematics at City University in January 2010. He has supervised 14 PhD/DPhil students (7 of them funded by EPSRC or NERC). He has won 19 grants to support his work, including the current EU Research and Innovation Staff Exchange (RISE) grant number 690817 where he is Project Coordinator, involving a consortium of eleven universities in the EU and North America (January 2016-December 2019). In 2017 he organised the major conference Mathematical Models in Ecology and Evolution at City. Mark is on the editorial boards of the Journal of Theoretical Biology, Dynamic Games and Applications and the Journal of Dynamics and Games. His research interests are in Mathematical Biology, in particular Evolutionary Game Theory, and he has published over 130 papers. This includes both theoretical work on general games and the modelling of specific animal behaviours. Main research areas include multiplayer game theory, models of food stealing (kleptoparasitism), the signalling behaviour of prey species, and evolutionary processes in structured populations. In 2013, together with Jan Rychtář, he completed the book Game-Theoretical Models in Biology published by Chapman and Hall. The second edition is currently being prepared.
Lucian Busoniu received his Ph.D. degree cum laude from the Delft University of Technology, the Netherlands, in 2009. He is a professor with the Department of Automation at the Technical University of Cluj-Napoca, where he leads the group on Robotics and Nonlinear Control. He has previously held research positions in the Netherlands and in France. He serves on the editorial board of the Elsevier journal Engineering Applications of Artificial Intelligence. His research interests include nonlinear optimal control using artificial intelligence and reinforcement learning techniques, robotics, and multiagent systems. His publications include among others several influential review articles and a book on reinforcement learning.
Erkan Buzbas is an associate professor of Statistics at the University of Idaho. He is a statistician and mathematical modeler. His background is in stochastic modeling of population-level phenomena, and development of computational statistical methods to perform inference under uncertainty. He has a broad interest in stochastic modeling of complex systems and statistical theory. Erkan's current work is focused on mathematical and statistical aspects of metascience. He uses statistical theory, mathematical modeling, and simulations to investigate:
Berna Devezer is an associate professor of Marketing at the College of Business and Economics, and an affiliate faculty of Statistics at the Department of Mathematics and Statistical Science at University of Idaho. She holds a PhD in Marketing and MS in Statistics from Washington State University. She is a metascience theorist and modeler, with background in behavioral experimentation and statistics.She has a broad interest in scientific theory, philosophy of science, and interdisciplinary metaresearch, with a particular focus on using stochastic and agent-based modeling approaches to study complexities of the scientific process.
Hugo Caselles-Dupré is a post-doctoral researacher in Machine Learning at ISIR (Sorbonne University). He did his PhD at the Flowers Laboratory (ENSTA Paris & INRIA) and Softbank Robotics Europe, studying perception and representation learning for embodied agents. He's also artist & co-founder at Obvious. One of their work, "Edmond de Belamy", made an historic sale at Christie's in October 2018.
Hugo Caselles-Dupré and his collegues at Obvious, Pierre Fautrel and Gauthier Vernier, were selected among The Top Young Entrepreneurs of The Forbes 30 Under 30 2020 in the category of Art and Culture.
Peter Dayan is a Director at the Max Planck Institute for Biological Cybernetics in Tübingen. He is a theoretical neuroscientist, studying neural reinforcement learning and representational inference and plasticity. He has particular interests in the role of neuromodulators (dopamine, serotonin, norepinephrine and acetylcholine), meta-learning and computational psychiatry. He uses computational methods, fMRI and MEG, and collaborates with a wide variety of experimental groups.
David Filliat graduated from the Ecole Polytechnique in 1997 and obtained a PhD on bio-inspired robotics navigation from Paris VI university in 2001. After 4 years as an expert for the robotic programs in the French armament procurement agency, he is now professor at Ecole Nationale Superieure de Techniques Avancees Paris. Head of the Computer Science and System Engineering laboratory team since 2018, he obtained the 'Habilitation a Diriger des Recherches' en 2011 and is a member of the joint ENSTA Paris - INRIA FLOWERS research team on developmental robotics. His main research interests are perception, navigation and machine learning in the frame of the developmental approach for autonomous and mobile robotics.
Website : perso.ensta-paris.fr/~filliat/
Raquel Fuentetaja is an associate professor of computer science at the Universidad Carlos III de Madrid (UC3M), Spain and member of the Planning and Learning research Group (PLG). Her research interests include representation change and online selection of configurations in Automated Planning, planning execution architectures for controlling autonomous systems, machine learning for problem solving, and generalized planning. She has published about 35 papers in journals, conferences and workshops. She has been involved in over 25 research projects funded by the Spanish Government and the European Commission. Currently she is Co-PI of GoalHub (Optimized planning software for the efficient exploitation of train traffic capacity in high congestion stations), and participates in the projects Arpía (Activity Recognition and Planning for Intelligent Assistants) and Clarc Echord++ (Automated Planning for Comprehensive Geriatric Assessment Using an Autonomous Social Robot. She has been program committee at several international conferences on AI (IJCAI, ICAPS, ECAI, etc.), and organising committee of WAF18 (19th Workshop of Physical Agents) and GENPLAN'20 (AAAI'20 Workshop on generalization in planning).
Xingang Fu received his Ph.D. degree in electrical engineering from the University of Alabama (UA), Tuscaloosa, AL, USA, in 2015. He is currently a Visiting Assistant Professor with the Department of Electrical Engineering and Computer Science, Texas A&M University-Kingsville (TAMUK), Kingsville, TX, USA. His current research interests include Neural Network, Deep Learning, Neural Dynamics, Approximate Dynamic Programming, Smart Inverter, Smart Grid, Wide-Bandgap Semiconductors (GaN &SiC), DSP/Microcontroller Embedded Systems, and so on.
He is a member of the IEEE Computational Intelligence Society, IEEE Control Systems Society, IEEE Power & Energy Society, IEEE Young Professionals, etc.
Website: Xingang Fu