ML IN PL ASSOCIATION - Key Persons
Job Titles:
- Scientific Program Coordinator
Job Titles:
- Research Scientist at Google DeepMind
Agnieszka Grabska-Barwińska is a Research Scientist at Google DeepMind, London, where she combines her knowledge in the fields of neuroscience and machine learning. Previously she was a post-doc at the UCL Gatsby Computational Neuroscience Unit and at the Ruhr-Universität Bochum. She obtained her Ph.D. from the International Graduate School of Neuroscience.
Agnieszka Grabska-Barwińska is a Research Scientist at Google DeepMind, London, where she combines her knowledge in the fields of neuroscience and machine learning. Previously she was a post-doc at the UCL Gatsby Computational Neuroscience Unit and at the Ruhr-Universität Bochum. She obtained her Ph.D. from the International Graduate School of Neuroscience.
Job Titles:
- Previous Team Member Tomasz Wąs
- Project Mentor
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- Associate Professor of AI
Agnieszka Ławrynowicz is an associate professor of AI and an experienced researcher in combining machine learning with symbolic approaches such as knowledge graphs. She is passionate about her work and continually seeks new ways to apply her knowledge to help solve real-world problems. She has led and participated in many R&D projects, including research in computational food, digital humanities, and social good. She enjoys things that are simple to use but elegant and creative.
Job Titles:
- Member of the Sponsors Team
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- Marketing Coordinator
- Previous Team Member
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- Marketing Officer
- Panel Team
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- Website / Infrastructure Team
Alina is an entrepreneur with an academic background (Ph.D. in Computer Science, Artificial Intelligence), combining the best of the two worlds to support business partners and enable analytic teams. She has helped companies across various industries leverage growing AI capabilities in order to bring competitive advantage. A scientist, highly trained in research, quantitative methods and computer science. Alina cultivates a culture of innovation, entrepreneurial spirit and focused teamwork. She has built teams and worked in international groups, including fully remote. She authored and co-authored 10+ publications in top scientific journals such as Neurocomputing, Web Intelligence, Fundamenta Informaticae as well as leading conference papers such as IJCAI, PRIMA and WI-IAT. She received a special prize for outstanding theoretical dissertation on Artificial Intelligence in 2016. At QED Software, Alina is responsible for the AI products portfolio as well as effective introduction of the products to the market. Privately, Alina enjoys life, but particularly windsurfing.
Job Titles:
- Member of the Sponsors Team
- Marketing Team
Job Titles:
- Member of the Sponsors Team
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- Student Relations Officer
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- Website / Infrastructure Team
Desmond Elliott is an Assistant Professor and a Villum Young Investigator at the University of Copenhagen. He obtained his Ph.D from the University of Edinburgh, under the supervision of Frank Keller, and he was a Postdoctoral Researcher at CWI, and the University of Amsterdam in the Netherlands. His current research interests include tokenisation-free language modelling, and multilingual and multimodal learning.
Job Titles:
- Academic Relations Manager at G - Research
- Research
Dr Charles Martinez is the Academic Relations Manager at G-Research. Charles started his studies as a physicist at University Portsmouth Physics department's MPhys programme, and later completed a PhD in Phonon interactions in Gallium Nitride nanostructures at the University of Nottingham. Charles then worked on indexing and abstract databases at the Institution for Engineering and Technology (IET) before moving -into sales in 2010. Charles' previous role was as Elsevier's Key Account Manager, managing sales and renewals for the UK Russell Group institutions, Government and Funding body accounts, including being one of the negotiators in the recent UK ScienceDirect Read and Publish agreement. Since leaving Elsevier Charles is dedicated to forming beneficial partnerships between G-Research and Europe's top institutions, and is living in Cambridge, UK.
Edoardo M. Ponti is a Lecturer (≈ Assistant Professor) in Natural Language Processing at the University of Edinburgh, where he is part of the "Institute for Language, Cognition, and Computation" (ILCC), and an Affiliated Lecturer at the University of Cambridge. Previously, he was a visiting postdoctoral scholar at Stanford University and a postdoctoral fellow at Mila and McGill University in Montreal. In 2021, he obtained a PhD in computational linguistics from the University of Cambridge, St John's College. His main research foci are modular deep learning, sample-efficient learning, faithful text generation, computational typology and multilingual NLP. His research earned him a Google Research Faculty Award and 2 Best Paper Awards at EMNLP 2021 and RepL4NLP 2019. He is a board member and co-founder of SIGTYP, the ACL special interest group for computational typology, and a scholar of the European Lab for Learning and Intelligent Systems (ELLIS). He is a (terrible) violinist, football player, and an aspiring practitioner of heroic viticulture.
Job Titles:
- Associate Professor at the University of a Coruña
Eduardo Mosqueira-Rey is a tenured Associate Professor at the University of A Coruña (Spain) and member of the research group LIDIA (Laboratory for Research and Development in Artificial Intelligence). His research focuses on the development of Machine Learning and Quantum Computing algorithms applied usually to health problems. His recent work is centred on the definition of new types of interaction between humans and machine learning algorithms known as "Human-in-the-Loop Machine Learning''. Within this line, he is the principal investigator of the project "Analysis of human-in-the-loop machine learning strategies and its application to pancreatic cancer research (HITL-ML)" funded by the Spanish State Research Agency (AEI). He is also a research member of the NEASQC (NExt ApplicationS of Quantum Computing) European project developing the use case "Quantum Rule-Based Systems (QRBS) for breast cancer detection.
Job Titles:
- Assistant Professor at the Faculty of Mathematics
Ewa Szczurek is an assistant professor at the Faculty of Mathematics, Informatics and Mechanics at the University of Warsaw. She holds two Master degrees, one from the Uppsala University, Sweden and one from the University of Warsaw, Poland. She finished PhD studies at the Max Planck Institute for Molecular Genetics in Berlin, Germany and conducted postdoctoral research at ETH Zurich, Switzerland. She now leads a research group focusing on machine learning and molecular biology, with most applications in computational oncology. Her group works mainly with probabilistic graphical models and deep learning, with a recent focus on variational autoencoders.
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- Member of the Speakers Team
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- Call for Contributions Coordinator
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- Research Scientist at OpenAI
Filip Wolski is a Research Scientist at OpenAI, where he is working on reinforcement learning systems such as the OpenAI Five for DOTA 2. Before he got involved in machine learning, he was an accomplished competitive programmer having won both International Collegiate Programming Contest and the International Olympiad in Informatics, and has worked for top American companies involved in high-frequency trading.
Filip Wolski is a Research Scientist at OpenAI, where he is working on reinforcement learning systems such as the OpenAI Five for DOTA 2. Before he got involved in machine learning, he was an accomplished competitive programmer having won both International Collegiate Programming Contest and the International Olympiad in Informatics, and has worked for top American companies involved in high-frequency trading.
Job Titles:
- Speakers Team Coordinator
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- Associate Professor at Delft University of Technology
Frans A. Oliehoek is Associate Professor at Delft University of Technology, where he leads a group on interactive learning and decision making, is one of the scientific directors of the Mercury machine learning lab, and is director and co-founder of the ELLIS Unit Delft. He received his Ph.D. in Computer Science (2010) from the University of Amsterdam (UvA), and held positions at various universities including MIT, Maastricht University and the University of Liverpool. Frans' research interests revolve around intelligent systems that learn about their environment via interaction, building on techniques from machine learning, AI and game theory. He has served as PC/SPC/AC at top-tier venues in AI and machine learning, and currently serves as associate editor for JAIR and AIJ. He is a Senior Member of AAAI, and was awarded a number of personal research grants, including a prestigious ERC Starting Grant.
Job Titles:
- Professor at the Pompeu Fabra University
Gergely Neu is a research assistant professor at the Pompeu Fabra University, Barcelona, Spain. He has previously worked with the SequeL team of INRIA Lille, France and the RLAI group at the University of Alberta, Edmonton, Canada. He obtained his PhD degree in 2013 from the Budapest University of Technology and Economics, where his advisors were András György, Csaba Szepesvári and László Györfi. His main research interests are in machine learning theory, with a strong focus on sequential decision making problems. Dr. Neu was the recipient of a Google Faculty Research award in 2018, the Bosch Young AI Researcher Award in 2019, and an ERC Starting Grant in 2020.
Job Titles:
- Senior Research Scientist at Google DeepMind
Gintare Karolina Dziugaite is a senior research scientist at Google DeepMind, an adjunct professor in the McGill University School of Computer Science, and an associate industry member of Mila, the Quebec AI Institute. Prior to joining Google, she led the Trustworthy AI program at Element AI / ServiceNow, and was named a Rising Star in Machine Learning in 2019. Her research combines theoretical and empirical approaches to understanding deep learning. Since her PhD, one of her main focuses has been on generalization, memorization, and, more recently, on unlearning. She has published a number of papers on network and data pruning, investigating how pruning interacts with other properties of deep learning systems, the training dynamics and the loss landscape.
Currently a Data Scientist at Amazon, Grzegorz Jacenków specialises in multimodal learning research and large language models (LLMs). Prior to joining Amazon, he was a PhD student in Healthcare AI at The University of Edinburgh, where he also earned an MSc in Artificial Intelligence. His academic foundation was laid with a BSc in Computer Science with Business and Management from The University of Manchester. Notably, Grzegorz contributed to CERN as a technical student, addressing author disambiguation at Inspire-HEP. His research interests encompass multimodal alignment, low-resource learning, and leveraging knowledge graphs.
Job Titles:
- Researcher in Computer Vision at the University of Oxford
Gül Varol is a postdoctoral researcher in computer vision at the University of Oxford, working with Andrew Zisserman. She obtained a PhD from the WILLOW team of INRIA Paris and Ecole Normale Supérieure (ENS) under the supervision of Ivan Laptev and Cordelia Schmid. Before that, she received her BS and MS degrees from Bogazici University. Her research is focused on human understanding in videos, with a particular emphasis on action recognition and body shape analysis.
Gül Varol is a postdoctoral researcher in computer vision at the University of Oxford, working with Andrew Zisserman. She obtained a PhD from the WILLOW team of INRIA Paris and Ecole Normale Supérieure (ENS) under the supervision of Ivan Laptev and Cordelia Schmid. Before that, she received her BS and MS degrees from Bogazici University. Her research is focused on human understanding in videos, with a particular emphasis on action recognition and body shape analysis.
Henryk Michalewski obtained his Ph.D. in Mathematics and Habilitation in Computer Science from the University of Warsaw. Henryk spent a semester in the Fields Institute, was a postdoc at the Ben Gurion University in Beer-Sheva and a visiting professor in the École normale supérieure de Lyon.
Job Titles:
- Head of the Department of Linguistic Engineering and Text Analysis at the NASK National Research Institute
Inez Okulska is the Head of the Department of Linguistic Engineering and Text Analysis at the NASK National Research Institute and Director of Innovaition & Tech Department at the Ministry of Digital Affairs Republic of Poland. After completing a colorful humanistic path (which included, among others, linguistics, comparative literary studies, cultural studies, philosophy), culminating in a doctorate in translation studies and a postdoctoral fellowship at Harvard University, she completed master's studies in automation and robotics at the WEiTI faculty of the Warsaw University of Technology. Scientifically interested in the semantic and pragmalinguistic potential of grammar, explores proprietary vector representations of text and their algebraic potential. She implements projects related to cybersecurity, primarily at the level of detection and classification of undesirable content. She was selected as one of Perspectywy Top100 WomenInAI in Poland.
Jacek Tabor in his scientific work deals with broadly understood machine learning, in particular with deep generative models. He is also a member of the GMUM group (gmum.net) aimed at popularization and development of machine learning methods in Cracow. Tomasz Trzciński Warsaw University of Technology / Tooploox / Jagiellonian University Tomasz Trzciński (DSc, WUT'20; PhD, EPFL'14; MSc, UPC/PoliTo'10) is an Associate Professor at Warsaw University of Technology, where he leads a Computer Vision Lab, and at Jagiellonian University of Cracow (GMUM). He is also a Computer Vision Group Leader at IDEAS NCBR, a publicly-funded Polish Center for AI. He was a Visiting Scholar at Stanford University in 2017 and at Nanyang Technological University in 2019. Previously, he worked at Google in 2013, Qualcomm in 2012 and Telefónica in 2010. He is an Associate Editor of IEEE Access and MDPI Electronics and frequently serves as a reviewer in major computer science conferences (CVPR, ICCV, ECCV, NeurIPS, ICML) and journals (TPAMI, IJCV, CVIU). He is a Senior Member of IEEE, member of ELLIS Society, member of the ALICE Collaboration at CERN and an expert of National Science Centre and Foundation for Polish Science. He is a Chief Scientist at Tooploox and a co-founder of Comixify, a technology startup focused on using machine learning algorithms for video editing.
Job Titles:
- Visual Identity Coordinator
Job Titles:
- Assistant Professor of Artificial Intelligence in the Computational Intelligence
Jakub Tomczak is an assistant professor of Artificial Intelligence in the Computational Intelligence group at the Vrije Universiteit Amsterdam and a deep learning researcher in Qualcomm AI Research in Amsterdam. From October 2016 to September 2018 he was a Marie Sklodowska-Curie Individual Fellow in Prof. Max Welling's group at the University of Amsterdam. He obtained his Ph.D. in machine learning from the Wroclaw University of Technology. His research interests include probabilistic modeling, deep learning, approximate Bayesian modeling, and deep generative modeling (with special focus on Variational Auto-Encoders and Flow-based model).
Jakub Tomczak is an assistant professor of Artificial Intelligence in the Computational Intelligence group at the Vrije Universiteit Amsterdam and a deep learning researcher in Qualcomm AI Research in Amsterdam. From October 2016 to September 2018 he was a Marie Sklodowska-Curie Individual Fellow in Prof. Max Welling's group at the University of Amsterdam. He obtained his Ph.D. in machine learning from the Wroclaw University of Technology. His research interests include probabilistic modeling, deep learning, approximate Bayesian modeling, and deep generative modeling (with special focus on Variational Auto-Encoders and Flow-based model).
Job Titles:
- Website / Infrastructure Team
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- Associate Professor at Faculty of Mathematics
Jan Chorowski is an associate professor at Faculty of Mathematics and Computer Science at University of Wrocław. He received his M.Sc. degree in electrical engineering from Wrocław University of Technology and Ph.D. from University of Louisville. He has visited several research teams, including Google Brain, Microsoft Research and Yoshua Bengio's lab. His research interests are applications of neural networks to problems which are intuitive and easy for humans and difficult for machines, such as speech and natural language processing.
Job Titles:
- Full Professor of Computer Science at the Faculty of Mathematics, Informatics and Mechanics of the University of Warsaw, a past Vice - Rector at the University
Jane Dwivedi-Yu is a researcher at Meta AI. Her current research focuses on enhancing capabilities of language models along several dimensions, including tool usage, editing, and evaluating representation harms and notions of morality and norms internalized by these models. She is also interested in building large-scale personalized recommender systems by leveraging principles from affective computing, work which was cited among the top 15 AI papers to read in 2022. Before joining Meta, she completed her PhD in Computer Science at University of California, Berkeley and Bachelors at Cornell University.
Jiri Matas is a full professor and the head of the Visual Recognition Group, Department of Cybernetics, Czech Technical University in Prague. He holds a PhD degree from the University of Surrey, UK (1995). He has published more than 300 papers that have been cited about 64000 times. His research interests include visual tracking, object recognition, image matching and retrieval, sequential pattern recognition, and RANSAC-type optimization methods. He received the best paper prize at the British Machine Vision Conferences in 2002, 2005 and 2022, at the Asian Conference on Computer Vision in 2007 and at the Int. Conf. on Document analysis and Recognition in 2015. J. Matas served as a programme or general chair at the European Conference of Computer Vision (ECCV) in 2004, 2016, 2022 and at Computer Vision and Pattern Recognition (CVPR) in 2007 and 2022. He is an Editor-in-Chief of the International Journal of Computer Vision was an Associate Editor-in-Chief of IEEE T. Pattern Analysis and Machine Intelligence. He has co-founded two companies, Eyedea Recognition (computer vision) and Locksley (combinatorial optimization). The industrial project he has lead at the Czech Technical University (Toyota, Samsung, Hitachi, Boeing) have generated income of about 5 million euros. He is an inventor of several patents.
Job Titles:
- Research Fellow of the Royal Academy of Engineering
Joao Henriques is a Research Fellow of the Royal Academy of Engineering, working at the Visual Geometry Group (VGG) at the University of Oxford. He created the KCF and SiameseFC visual object trackers, which are widely deployed in robotics and consumer hardware, and won two times the prestigious VOT Challenge, outperforming all competing visual tracking systems worldwide. His research focuses on robotics with deep learning, and meta-learning systems.
Joao Henriques is a Research Fellow of the Royal Academy of Engineering, working at the Visual Geometry Group (VGG) at the University of Oxford. He created the KCF and SiameseFC visual object trackers, which are widely deployed in robotics and consumer hardware, and won two times the prestigious VOT Challenge, outperforming all competing visual tracking systems worldwide. His research focuses on robotics with deep learning, and meta-learning systems.
Josef Sivic is a senior researcher (Directeur de recherche) at Inria, Distinguished researcher at Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague. Recipient of an ERC Starting Grant (2013), Sullivan Phd Thesis Prize (2007), and the CVPR (2017) and two ICCV (2017) test-of-time awards. Fellow in the Learning in Machines and Brains program of the Canadian Institute for Advanced Research.
Josef Sivic is a senior researcher (Directeur de recherche) at Inria, Distinguished researcher at Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague. Recipient of an ERC Starting Grant (2013), Sullivan Phd Thesis Prize (2007), and the CVPR (2017) and two ICCV (2017) test-of-time awards. Fellow in the Learning in Machines and Brains program of the Canadian Institute for Advanced Research.
Job Titles:
- Coordinator
- Panel Discussion Coordinator
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- Call for Contributions Officer
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- Finance Coordinator
- Marketing Officer
- Vice Project Leader
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- Member of the Panel Team
- Finance Team
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- Finance Coordinator
- Finance Officer
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- Project Leader
- Workshops Coordinator
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- Associate Professor at Delft University of Technology
Kateřina Staňková is an associate professor at Delft University of Technology and Delft Technology Fellow, at the faculty of Technology, Policy and Management. She also co-founded Institute for Health Systems Science at her faculty. She focuses on both theory of differential and evolutionary games and their application in understanding and managing evolving systems. In the past years, she has been focusing on understanding cancer through evolutionary game theory and designing evolutionary therapies, i.e. therapies that anticipate and steer/forestall treatment-induced resistance in cancer cells. These treatments show a great promise in first clinical trials. For this work, she received the 2020 Dutch Research Council Stairway to Impact award. She leads a number of national and international projects, including European Training Network EvoGamesPlus and the Dutch Research Council VIDI project "ANTICANCER: Game Theory Empowered by Data Science and Control Theory to Improve Treatment of Metastatic Cancer", which aims at designing evolutionary therapies for metastatic Non-Small Cell Lung Cancer.
Job Titles:
- Research Scientist at Google Brain Robotics Team
Krzysztof Choromanski is a research scientist at Google Brain Robotics Team in New York. He works on several topics in robotics and machine learning including: reinforcement learning, evolution strategies, structured random matrices, as well as quasi-Monte Carlo methods.
Job Titles:
- Assistant Professor at Poznan University of Technology
Krzysztof Dembczyński is an assistant professor at Poznan University of Technology. He received his Ph.D. and Habilitation degrees in computer science from the same university. As a post-doctoral researcher he spent two years from 2009 to 2011 in the Knowledge Engineering & Bioinformatics Lab at Marburg University.
Job Titles:
- Assistant Professor at NYU
- Associate Professor at NYU School of Medicine
Krzysztof Geras is an associate professor at NYU School of Medicine and an affiliated faculty at NYU Center for Data Science. His main interests are in unsupervised learning with neural networks, model compression, transfer learning, evaluation of machine learning models and applications of these techniques to medical imaging. He previously completed a postdoc at NYU with Kyunghyun Cho, a PhD at the University of Edinburgh with Charles Sutton and an MSc as a visiting student at the University of Edinburgh with Amos Storkey. His BSc is from the University of Warsaw. He also completed industrial internships in Microsoft Research (Redmond and Bellevue), Amazon (Berlin) and J.P. Morgan (London).
Krzysztof is an assistant professor at NYU. His main interests are in unsupervised learning with neural networks, model compression, transfer learning, evaluation of machine learning models and applications of these techniques to medical imaging.
Job Titles:
- Student Relations Officer
Léon Bottou received the Diplôme d'Ingénieur de l'École Polytechnique (X84) in 1987, the Magistère de Mathématiques Fondamentales et Appliquées et d'Informatique from École Normale Supérieure in 1988, and a Ph.D. in Computer Science from Université de Paris-Sud in 1991. His research career took him to AT&T Bell Laboratories, AT&T Labs Research, NEC Labs America and Microsoft. He joined Meta AI (formerly Facebook AI Research) in 2015. The long-term goal of Léon Bottou's research is to understand and replicate intelligence. Because this goal requires conceptual advances that cannot be anticipated, Leon's research has followed many practical and theoretical turns: neural networks applications in the late 1980s, stochastic gradient learning algorithms and statistical properties of learning systems in the early 1990s, computer vision applications with structured outputs in the late 1990s, theory of large scale learning in the 2000s. During the last few years, Léon Bottou's research aims to clarify the relation between learning and reasoning, with more and more focus on the many aspects of causation (inference, invariance, reasoning, affordance, and intuition.
Maciej Wysocki is a first-year Ph.D. student in Quantitative Finance at the University of Warsaw and works as a data scientist at Allegro Pay. In his academic research he tackles the problems of derivatives pricing and portfolio optimization, while at Allegro Pay on a daily basis he deals with terabytes of data to deliver state-of-the-art machine learning solutions for credit risk management. With a passion for data-driven insights, he has a track record of applying advanced analytics and machine learning methods to solve complex business challenges in the banking and fintech industries.
Job Titles:
- Branding Coordinator
- Conference Branding Coordinator
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- Member of the Sponsors Team
- Marketing Team
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- Marketing Coordinator
- Officer
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- Researcher at Google Brain
Marcin Andrychowicz is a researcher at Google Brain in Zurich where he works on Reinforcement Learning. He received his PhD in Computer Science from the University of Warsaw where his research concerned cryptography and cryptocurrencies. Afterward, he worked on meta-learning and memory-augmented neural networks at DeepMind and on Reinforcement Learning for robotics at OpenAI.
Job Titles:
- Associate Professor at the University of Warsaw
Marek Cygan is currently an associate professor at the University of Warsaw, leading a newly created Robot learning group, focused on robotic manipulation and computer vision. Additionally, CTO and co-founder of Nomagic, a startup delivering smart pick-and-place robots for intralogistics applications. Earlier doing research in various branches of algorithms, having an ERC Starting grant on the subject.
Marek Cygan was doing research on the theory of algorithms for many years. He did his scientific internships at University of Maryland, College Park and University in Lugano. Recently, however, he has switched to machine learning. In 2017, he co-founded a startup NoMagic.AI which focuses on AI for robotics.
Job Titles:
- Coordinator
- Call for Contributions Coordinator
- Website / Infrastructure Team Coordinator
Job Titles:
- Research Scientist at Uber AI Labs
Martin Jankowiak is a Research Scientist at Uber AI Labs. Before joining Uber he worked as a Research Scientist at the NYU Center for Urban Science and Progress. Before switching to machine learning he obtained a Ph.D. in theoretical particle physics from Stanford University. His research interests span probabilistic machine learning, including gaussian processes, probabilistic programming, and variational inference.
Martin Jankowiak is a Research Scientist at Uber AI Labs. Before joining Uber he worked as a Research Scientist at the NYU Center for Urban Science and Progress. Before switching to machine learning he obtained a Ph.D. in theoretical particle physics from Stanford University. His research interests span probabilistic machine learning, including gaussian processes, probabilistic programming, and variational inference.
Job Titles:
- Scientific Program Officer
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- Senior Researcher at the Italian Institute of Technology
Massimiliano Pontil is Senior Researcher at the Italian Institute of Technology, where he leads the CSML research unit, and co-director of ELLIS unit Genoa. He is also Professor at University College London and member of the UCL Centre for Artificial Intelligence. He has been active in machine learning for over twenty-five years, working on theory and algorithms, including the areas of kernel methods, learning dynamical systems, meta-learning, multitask and transfer learning, sparse estimation, and statistical learning theory.
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- Marketing Officer
- Marketing Vice - Coordinator
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- Next Team Member
- Sponsorship Coordinator
Michał Karpowicz joined NASK PIB in 2006. He has gone through a full academic career path, from a research assistant position to a professor at the institute, leading a team, department, and branch along the way (in the field of cyber security systems). He was visiting professor at the MIT Mathematics Department. He has given guest lectures at institutions like Stanford University and UCSD (University of California San Diego). He has been a long-time lecturer at the Faculty of Electronics and Information Technology at the Warsaw University of Technology. He is the creator of the meta-factorization theory and new algorithms for detecting and mitigating DDoS attacks. He has formulated optimality conditions for a class of energy-efficient stochastic control problems with an infinite horizon, as well as necessary and sufficient conditions for the effectiveness of Nash equilibrium points in games induced by KKT conditions for nonlinear optimization problems with constraints. He is a co-creator of FLDX technology, energy-efficient network control systems, and energy-efficient CPU controllers (for the Linux kernel). He is the recipient of the NASK PIB Director's Award for his exceptional contribution to the development of the institute. He is also the recipient of the Warsaw University of Technology Rector's Award for his original lecture on Control Theory, as well as the Rector's Award for achievements in scientific research related to the development of energy-efficient control mechanisms for computer systems.
Job Titles:
- Next Team Member
- Vice Project Leader
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- Officer
- Speakers Team Coordinator
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- Call for Contributions Team
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- Call for Contributions Team
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- Logistics Coordinator
- Logistics Officer
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- Learning Engineer at Hugging Face
Omar Sanseviero is a lead machine learning engineer at Hugging Face, where he works at the intersection of open source, community, and product. Omar leads multiple ML teams that work on topics such as ML for Art, Developer Advocacy Engineering, ML Partnerships, Mobile ML, and ML for Healthcare. Previously, Omar worked at Google as a Software Engineer on Google Assistant and TensorFlow. In Google Assistant, Omar worked with on-device language models, model training and quality refinement, and serving infrastructure.
Job Titles:
- Professor in Computer Science at the Université De Lille
Philippe Preux is a professor in Computer Science at the Université de Lille, France. He has been active in research in artificial intelligence for 30 years now, mostly dealing with machine learning and data mining in the last 2 decades, especially reinforcement learning. He has been the head of the SequeL research group at Inria/CNRS/Université de Lille since 2006, a group now renamed Scool. His research ranges from fundamental algorithmic and methodological questions to applications of reinforcement learning in collaboration with companies. Philippe currently focuses his efforts on applications related to health or sustainable development. He has hosted ICML 2015, and co-organized various scientific events such as the European Workshop on Reinforcement Learning in 2008 and 2018, as well as the Reinforcement Learning Summer School in 2019.
Piotr Biliński is an Associate Professor in the Faculty of Mathematics, Informatics, and Mechanics at the University of Warsaw, as well as an Associate Member in the Active Vision Laboratory at the Oxford University.
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- Premeetings and Tutorials Team
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- Member of the Special Ops Team
- Finance Team
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- Member of the Special Ops Team
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- Associate Professor at the Faculty of Mathematics
- Associate Professor in the Polish Academy of Sciences
Piotr Miłoś is an associate professor in the Polish Academy of Sciences, a team leader at IDEAS NCBR and a member of the ELLIS Society. He is interested in methods that can deliver robust decision-making capabilities in complex scenarios. This covers many scenarios including continual learning, automated reasoning in mathematics, planning algorithms and sequential modelling.
Piotr Miłoś is an Associate Professor at the Faculty of Mathematics, Mechanics and Computer Science of the University of Warsaw. He received his Ph.D. in probability theory. From 2016 he has developed interest in machine learning. Since then he collaborated with deepsense.ai on various research projects. His focus in on problems in reinforcement learning.
Job Titles:
- Professor at the Institute of Informatics
Piotr Sankowski is a professor at the Institute of Informatics, University of Warsaw, where he received his habilitation in 2009 and where he received a doctorate in computer science in 2005. His research interest focuses on practical application of algorithms, ranging from economic applications, through learning data structures, to parallel algorithms for data science. In 2009, Piotr Sankowski received also a doctorate in physics in the field of solid state theory at the Polish Academy of Sciences. In 2010 he received ERC Starting Independent Researcher Grant, in 2015 ERC Proof of Concept Grant, and in 2017 ERC Consolidator Grant. He is a president of IDEAS NCBR - a research
Job Titles:
- Call for Contributions Team
Przemysław Biecek obtained his Ph.D. in Mathematical Statistics and MSc in Software Engineering at Wroclaw University of Science and Technology. He is currently working as an Associate Professor at the Faculty of Mathematics and Information Science, Warsaw University of Technology, and an Assistant Professor at the Faculty of Mathematics, Informatics and Mechanics, University of Warsaw.
Job Titles:
- Research Scientist at Google DeepMind
Razvan Pascanu is a Research Scientist at Google DeepMind, London. He obtained a Ph.D. from the University of Montreal under the supervision of Yoshua Bengio. While in Montreal he was a core developer of Theano. Razvan is also one of the organizers of the Eastern European Summer School. He has a wide range of interests around deep learning including optimization, RNNs, meta-learning and graph neural networks.
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- CTO and Chief Scientist at Molecule
Stanislaw Jastrzebski serves as the CTO and Chief Scientist at Molecule.one, a biotech startup in the drug discovery space. He is passionate about improving the fundamental aspects of deep learning and applying it to automate scientific discovery. He completed his postdoctoral training at New York University in deep learning. His PhD thesis was based on work on foundations of deep learning done during research visits at MILA (with Yoshua Bengio) and the University of Edinburgh (with Amos Storkey). He received his PhD from Jagiellonian University, advised by Jacek Tabor. Beyond academia, he gained industrial experience at Google, Microsoft and Palantir. In his scientific work, he has published at leading machine learning venues (NeurIPS, ICLR, ICML, JMLR, Nature SR). He is also actively contributing to the machine learning community as an Area Chair (most recently NeurIPS '23) and as an Action Editor for TMLR. At Molecule.one, he leads technical teams working on software for synthesis planning based on deep learning, public data sources, and experiments from a highly automated laboratory.
Job Titles:
- Learning Researcher ( Principal Engineer ) at Qualcomm AI Research
Taco Cohen is a machine learning researcher (Principal Engineer) at Qualcomm AI Research in Amsterdam. He received a BSc in theoretical computer science from Utrecht University, and a MSc in artificial intelligence and PhD in machine learning (with prof. Max Welling) from the University of Amsterdam (all three cum laude). He was a co-founder of Scyfer, a company focussed on deep active learning, acquired by Qualcomm in 2017. His research is focused on geometric deep learning and reinforcement learning. During his studies he has interned at Google Deepmind (working with Geoff Hinton) and OpenAI. He received the 2014 University of Amsterdam MSc thesis prize, a Google PhD Fellowship, ICLR 2018 best paper award for "Spherical CNNs", was named one of 35 innovators under 35 by MIT Tech Review, and won the 2022 ELLIS PhD Award and 2022 Kees Schouhamer Immink prize for his PhD research.
Tomasz Trzciński is an Assistant Professor in the Division of Computer Graphics in the Institute of Computer Science at Warsaw University of Technology. He obtained his Ph.D. in Computer Vision at École Polytechnique Fédérale de Lausanne. He has (co)-authored several papers and serves as a reviewer in prestigious computer science conferences and journals.
Veronika Cheplygina's research focuses on limited labeled scenarios in machine learning, in particular in medical image analysis. She received her Ph.D. from Delft University of Technology in 2015. After a postdoc at the Erasmus Medical Center, in 2017 she started as an assistant professor at Eindhoven University of Technology. In 2020, failing to achieve various metrics, she left the tenure track of search of the next step where she can contribute to open and inclusive science. In 2021 she started as an associate professor at IT University of Copenhagen. Next to research and teaching, Veronika blogs about academic life at https://www.veronikach.com. She also loves cats, which you will often encounter in her work.
Job Titles:
- Investigator at the University of Copenhagen
Job Titles:
- Research Scientist in DeepMind
Viorica Patraucean is a research scientist in DeepMind. She obtained her PhD from University of Toulouse on probabilistic models for low-level image processing. She then carried out postdoctoral work at Ecole Polytechnique Paris and University of Cambridge, on processing of images, videos, and point-clouds. Her main research interests revolve around efficient vision systems, with a focus on deep video models. She is one of the main organisers of EEML summer school and has served as program committee member for top Computer Vision and Machine Learning conferences.
Job Titles:
- Research Scientist at Google DeepMind
Volodymyr Mnih is a Research Scientist at Google DeepMind. He completed an MSc at the University of Alberta working under the supervision of Csaba Szepesvari and a PhD at the University of Toronto working under the supervision of Geoffrey Hinton. Since joining DeepMind, he has been working at the intersection of deep learning and reinforcement learning, co-developing Deep Q Networks (DQN), the asynchronous advantage actor critic (A3C), and reinforcement learning-based hard attention mechanisms.
Job Titles:
- Assistant Professor at Poznan University of Technology, Polan
Wojciech Kotlowski is an assistant professor at Poznan University of Technology, Poland. From 2009 to 2012, he was a post-doctoral researcher in Centrum Wiskunde & Informatica (Amsterdam, Netherlands) in the group of Peter Grünwald. He obtained his Ph.D. degree in Computer Science from Poznan University of Technology in 2009 under supervision of Roman Słowiński. His main research interests are in the theory of machine learning, particularly in the online learning with adversarial data.
Wojciech Kotlowski is an assistant professor at Poznan University of Technology, Poland. From 2009 to 2012, he was a post-doctoral researcher in Centrum Wiskunde & Informatica (Amsterdam, Netherlands) in the group of Peter Grünwald. He obtained his Ph.D. degree in Computer Science from Poznan University of Technology in 2009 under supervision of Roman Słowiński. His main research interests are in the theory of machine learning, particularly in the online learning with adversarial data.
Yannic runs the world's largest YouTube channel dedicated to Machine Learning Research. His video topics range from technical analysis of new papers to covering the ML community's recent news and developments, as well as mini-research projects. He holds a PhD in ML from ETH Zurich and is a co-founder of the Swiss LegalTech startup DeepJudge.
Job Titles:
- Member of the Speakers Team
- Marketing Team
Job Titles:
- Lead Data Scientist at BCG Gamma
Łukasz Bolikowski, is a Lead Data Scientist at BCG Gamma, where he builds advanced mathematical models working on big data sets for the largest global clients. Lukasz is also a scientific advisor and technical code reviewer for Gamma cases. Before joining BCG, founder and leader of Applied Data Analysis Lab at Interdisciplinary Centre for Mathematical and Computational Modelling at University of Warsaw. PhD in Computer Science from Systems Research Institute, Polish Academy of Sciences, MSc in Computer Science from MIM, University of Warsaw. Independent expert of the OECD and European Commission.
Job Titles:
- Assistant Professor at the Institute of Mathematics
Łukasz Kuciński is an Assistant Professor at the Institute of Mathematics of the PAS, a Senior Research Scientist at IDEAS NCBR, and a Member of the ELLIS Society. His ambition is to design and implement AI agents that can learn to solve problems autonomously in a self-improvement manner. His research is published at CORE A* conferences, such as NeurIPS and ICLR, and covers machine learning and sequential decision-making topics, including reinforcement learning, planning, game theory, automated theorem proving, or alignment of large language models. Prior to his current roles, he worked at PFSA as Vice-Director, where he led a risk modeling team. He obtained a master's degree from the Faculty of Mathematics, Informatics, and Mechanics of the University of Warsaw and a Ph.D. in mathematics from the Polish Academy of Sciences.
Job Titles:
- Logistics Coordinator
- Networking Event Coordinator