7 - 10 November / Copernicus Science Centre, Warsaw, Poland

0 days / 00 hours / 00 minutes / 00 seconds

/ Tickets

Early bird registration

Selective registration that is available until 31 August, 23:59 (AoE). Notifications will be sent before 7 September.

Ticket Early Bird Price
Student 300 PLN
Regular 600 PLN
Regular registration

First-come-first-served registration, which starts 9 September, 18:00 CEST (GMT+2) and last until all tickets are sold out.

Ticket Regular Price
Student 450 PLN
Regular 900 PLN
Late registration

Missed out on ticket sales? We've set aside a very limited number of tickets just for you. Available from 24 October, 18:00 CEST (GMT+2).

Ticket Late Price
Student 1200 PLN
Regular 1200 PLN

/ About the event

is the 8th edition of an annual conference focused on the best of Machine Learning both in academia and in business. Join us and...

Learn from the best experts in the world!

Attend a stellar lineup of keynote and invited lectures of internationally recognized researchers, learn about state-of-the-art, and get inspired.

Share your knowledge with others!

Take part in Call for Contributions and present your work as an engaging talk or as a captivating poster. All presenters get free entry to the conference.

Meet with the community!

Experience a friendly and inclusive atmosphere. Engage in meaningful conversations and establish lasting connections with other machine learning enthusiasts.

Find this year's program below

/ Invited Speakers

Bernardino Romera Paredes photo

Bernardino Romera Paredes

Google DeepMind

Bernardino is a researcher at Google DeepMind, where he has been a core team member of AlphaFold2 for protein folding, and AlphaTensor for matrix multiplication algorithms. More recently, he initiated FunSearch, a system which uses Large Language Models for program search and has discovered new mathematical knowledge. Long before that, in 2009, Bernardino started his AI journey by studying the MSc Computational Statistics and Machine Learning at UCL. In 2010 he started a PhD, also at UCL, supervised by Prof. Massimiliano Pontil and Prof. Nadia Berthouze, and in 2013 he also did an internship at Microsoft Research. After finishing his PhD in 2014, he joined the Torr Vision Group as a Postdoc at the University of Oxford, researching about semantic segmentation and zero-shot learning. He has several papers published in Nature, as well as in machine learning conferences like NeurIPS and ICML. His main motivation is to leverage the power of AI to bring light to important scientific problems.

Tom Rainforth photo

Tom Rainforth

University of Oxford

Tom is a Senior Researcher in Machine Learning and leader of the RainML Research Lab at the Department of Statistics in the University of Oxford. He is the principal investigator for the ERC Starting Grant Data-Driven Algorithms for Data Acquisition. His research covers a wide range of topics in and around machine learning and experimental design, with areas of particular interest including Bayesian experimental design, deep learning, representation learning, generative models, Monte Carlo methods, active learning, probabilistic programming, and approximate inference.

Wojciech Samek photo

Wojciech Samek

Technische Universität Berlin

Wojciech Samek is a Professor in the EECS Department at TU Berlin and is jointly heading the AI Department at Fraunhofer HHI. He is a Fellow at BIFOLD - Berlin Institute for the Foundation of Learning and Data, the ELLIS Unit Berlin, and the DFG Research Unit DeSBi. Furthermore, he is a Senior Editor for IEEE TNNLS, an Associate Editor for Pattern Recognition, and an elected member of the IEEE MLSP Technical Committee and Germany's Platform for AI. He also serves as a member of the scientific advisory board of IDEAS NCBR - Polish Centre of Innovation in the Field of Artificial Intelligence. Wojciech has co-authored more than 200 papers and was the leading editor of the Springer book "Explainable AI: Interpreting, Explaining and Visualizing Deep Learning" (2019), and co-editor of the open access Springer book “xxAI – Beyond explainable AI” (2022). He has served as Program Co-Chair for IEEE MLSP'23, and as Area Chair for NAACL'21 and NeurIPS'23, and is a recipient of multiple best paper awards, including the 2020 Pattern Recognition Best Paper Award and the 2022 Digital Signal Processing Best Paper Prize.

Iryna Gurevych photo

Iryna Gurevych

Technical University of Darmstadt

Iryna Gurevych is Professor of Ubiquitous Knowledge Processing in the Department of Computer Science at the Technical University of Darmstadt in Germany. She also is an adjunct professor at MBZUAI in Abu-Dhabi, UAE, and an affiliated professor at INSAIT in Sofia, Bulgaria. She is widely known for fundamental contributions to and innovative applications of natural language processing and machine learning. Professor Gurevych is a past president of the Association for Computational Linguistics (ACL), the leading professional society in the field of natural language processing. Her many accolades include being a Fellow of the ACL, an ELLIS Fellow, and the recipient of an ERC Advanced Grant.

Alejandro Frangi photo

Alejandro Frangi

University of Manchester

Prof. Alejandro Frangi FREng, holds the Bicentennial Turing Chair in Computational Medicine at the University of Manchester, UK, with joint appointments in the Schools of Computer Science and Health Science. Additionally, he is the Royal Academy of Engineering Chair in Emerging Technologies, specialising in Precision Computational Medicine for in silico trials of medical devices. He serves as the Director of the Christabel Pankhurst Institute for Health Technology Research and Innovation and is a Fellow at the Alan Turing Institute. Recently, his research vision was recognised with an ERC Advanced Grant from the European Research Council. He leads the InSilicoUK Pro-Innovation Regulations Network (www.insilicouk.org). Professor Frangi's main research interests lie at the crossroads of medical image analysis and modelling with an emphasis on machine learning (phenomenological models) and computational physiology (mechanistic models). His work has had a profound impact on the field, particularly in the areas of cardiovascular, musculoskeletal and neurosciences. He is particularly interested in statistical methods applied to population imaging and in silico clinical trials. Prof. Frangi's contributions to the field have been widely recognised. He has received numerous accolades, including the IEEE Engineering in Medicine and Biology Technical Achievement Award (2021) and Early Career Award (2006). In 2011, he was honored with the UPF Medal for his service as Dean of the Escuela Politècnica Superior. He also received the ICREA-Academia Prize from the Institució Catalana de Recerca i Estudis Avançats (ICREA) in 2008, a President's International Initiative Award from the Chinese Academy of Science in 2019. Prof. Frangi has also edited a textbook on Medical Image Analysis, published in the MICCAI-Elsevier Book Series by Academic Press.

Yuki Asano photo

Yuki Asano

University of Amsterdam

Yuki is an assistant professor for computer vision and machine learning at the QUVA lab at the University of Amsterdam, where he works with Cees Snoek, Max Welling and Efstratios Gavves. His PhD was at the Visual Geometry Group (VGG) at the University of Oxford where he worked with Andrea Vedaldi and Christian Rupprecht. Prior to this, he studied physics at the University of Munich (LMU) and Economics in Hagen as well as a MSc in Mathematical Modelling and Scientific Computing at the Mathematical Institute in Oxford.

Danielle Belgrave photo

Danielle Belgrave

GSK AI

Danielle Belgrave is a VP of AI/ML at GSK. Her experience spans conducting machine learning research and leading teams across academia and industry focused on scientific discovery and personalising interventions in health. She has previously worked at Google DeepMind, Microsoft Research Cambridge, UK and Imperial College London. She has a BSc in business mathematics and statistics from the London School of Economics and a master’s degree in statistics from University College London. Her PhD was at the University of Manchester in Machine Learning for Healthcare.

Lucas Beyer photo

Lucas Beyer

Google DeepMind

Lucas grew up in Belgium wanting to make video games and their AI. He went on to study mechanical engineering at RWTH Aachen in Germany, then did a PhD in robotic perception and computer vision there too. Now, he is a staff research scientist at Google DeepMind (formerly Brain) in Zürich, leading multimodal vision-language research.

Roberto Calandra photo

Roberto Calandra

Technische Universität Dresden

Roberto Calandra is a Full (W3) Professor at the Technische Universität Dresden where he leads the Learning, Adaptive Systems and Robotics (LASR) lab. Previously, he founded at Meta AI (formerly Facebook AI Research) the Robotic Lab in Menlo Park. Prior to that, he was a Postdoctoral Scholar at the University of California, Berkeley (US) in the Berkeley Artificial Intelligence Research (BAIR) Lab. His education includes a Ph.D. from TU Darmstadt (Germany), a M.Sc. in Machine Learning and Data Mining from the Aalto university (Finland), and a B.Sc. in Computer Science from the Università degli Studi di Palermo (Italy). His scientific interests are broadly at the conjunction of Robotics and Machine Learning, with the goal of making robots more intelligent and useful in the real world. Among his contributions is the design and commercialization of DIGIT -- the first commercial high-resolution compact tactile sensor, which is currently the most widely used tactile sensor in robotics. Roberto served as Program Chair for AISTATS 2020, as Guest Editor for the JMLR Special Issue on Bayesian Optimization, and has previously co-organized over 16 international workshops (including at NeurIPS, ICML, ICLR, ICRA, IROS, RSS). In 2024, he received the IEEE Early Academic Career Award in Robotics and Automation.

Tomek Korbak photo

Tomek Korbak

UK AI Safety Institute

Tomek Korbak is a Senior Research Scientist at the UK AI Safety Institute working on safety cases for frontier models. Previously, he was a Member of Technical Staff at Anthropic working on honesty. Before that, he did a PhD at the University of Sussex focusing on RL from human feedback (RLHF) and spent time as a visiting researcher at NYU working with Ethan Perez, Sam Bowman and Kyunghyun Cho. He studied cognitive science, philosophy and physics at the University of Warsaw.

and more is coming!

/ AI Audio Challenge

Join us for AI Audio Challenge, a competition organised by ElevenLabs in partnership with , open to all enthusiasts of applied AI. Participating teams are asked to develop a solution leveraging ElevenLabs audio AI technologies.

/ Discussion Panels

AI in Medicine

Join us for a panel discussion on "AI in Medicine", where we will delve into the influence of artificial intelligence on the healthcare sector. The focus areas are practical applications of AI in clinical settings and the role of AI in expediting research breakthroughs across medicine and biology.

Anna Gambin

Anna Gambin

University of Warsaw

Professor Anna Gambin is deputy dean for research and international cooperation at the Faculty of Mathematics, Computer Science and Mechanics at the University of Warsaw (term 2016-2024). In her scientific work she deals with mathematical modeling of molecular processes and efficient algorithms for the analysis of biomedical data. Recently, her research is focused on computational methods supporting medical diagnostics based on genomic and proteomic data. She is the author of over 100 scientific publications and, to date, has supervised 13 PhDs in computational biology.

Wouter Bulten

Wouter Bulten

Aiosyn

Wouter is the Chief Operation and Product Officer (COO & CPO) of Aiosyn. At Aiosyn he works on precision pathology for cancer and kidney diseases using AI. Wouter studied Artificial Intelligence and worked as a software engineer and data scientist. He holds a Ph.D. in computational pathology with a focus on using artificial intelligence for clinical diagnostics. Wouter’s research showed that AI algorithms could grade prostate cancer on the level of experienced pathologists and actively assist pathologists in performing better diagnoses. Wouter was also one of the main organizers of the PANDA challenge, collaborating with Karolinska Institute and Google Health. Wouter’s research was published in top journals like The Lancet Oncology and Nature Medicine.

Danielle Belgrave

Danielle Belgrave

GSK AI

Danielle Belgrave is a VP of AI/ML at GSK. Her experience spans conducting machine learning research and leading teams across academia and industry focused on scientific discovery and personalising interventions in health. She has previously worked at Google DeepMind, Microsoft Research Cambridge, UK and Imperial College London. She has a BSc in business mathematics and statistics from the London School of Economics and a master’s degree in statistics from University College London. Her PhD was at the University of Manchester in Machine Learning for Healthcare.

AI in Law

Join us for the "AI in Law" panel, where we would like to explore the influence of artificial intelligence on the legal sector. During discussion we will delve into the potential role for AI-driven technologies and their promise to increase access to justice as well as challenges for responsible AI adoption.

Gabriela Bar

Gabriela Bar

Founder of the Gabriela Bar Law & AI firm, an experienced expert in the field of new technology law and the law and ethics of Artificial Intelligence (AI), researcher, member of Women in AI, recognised in Forbes’ list of the 25 Best Business Lawyers (2022) and the TOP100 Women in AI in Poland (2022). Member of the IEEE Legal Committee within the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems, the Association for New Technology Law, and the FBE New Technologies Commission. Teaches at several universities, actively participates in scientific conferences and industry seminars. Author of numerous publications in the field of AI, digital services, and personal data protection. Lawyer in EU projects: Smart Human Oriented Platform for Connected Factories – SHOP4CF, Multi-Agent Systems for Pervasive Artificial Intelligence for assisting Humans in Modular Production Environments – MAS4AI, and an independent AI ethics expert in the EXTRA-BRAIN project.

Natalie Byrom

Natalie Byrom

Dr Natalie Byrom is a researcher and policy adviser with expertise in justice system reform, AI, data-driven technologies and justice data governance. She has a track record of leading high-quality research and translating this into policy impact. Between 2018 and 2020 Dr Byrom was seconded to the UK Ministry of Justice as expert adviser on data in the context of an ongoing £1bn programme of digital court reform. She has also completed projects for the OECD and the Law Society of England and Wales on justice data and AI. Dr Byrom has given evidence to a number of parliamentary committees including the Justice Select Committee and the House of Lords Constitution Committee on issues relating to justice system reform, data collection and governance. Her writing on these issues has been published in the legal and national press. She is part of the BBC Expert Women Network, holds several public appointments, and is an Honorary Senior Research Fellow at UCL Faculty of Laws

Career Paths in ML

Join us for the "Career Paths in Machine Learning" panel, where we will explore the critical decisions and turning points in the careers of machine learning professionals. This discussion will delve into the important choice between pursuing a career in industry or academia.

Bartłomiej Twardowski

Bartłomiej Twardowski

IDEAS NCBR, Computer Vision Center UAB

Bartłomiej Twardowski is a Research Team Leader at the IDEAS NCBR and a researcher at the Computer Vision Center, Universitat Autònoma de Barcelona. His research interests focus on computer vision and continual learning of neural networks. He earned his Ph.D. in 2018, focusing on recommender systems and neural networks. Following his doctoral studies, he served as an assistant professor at Warsaw University of Technology in the AI group for 1.5 years before deciding to join the Computer Vision Center, UAB, for a post-doctoral program. He has been actively involved in various research projects related to DL/NLP/ML (ranging from €40k to €1.4M). He is a Ramón y Cajal fellow. He has a wide industry experience (more than 12 years), including international companies, e.g., Zalando, Adform, Huawei, Naspers Group (Allegro), as well as helping startups with research projects (Sotrender, Scattered). Throughout his career, he has had the opportunity to publish papers in prestigious conferences such as CVPR (2020, 2024, 3 papers), NeurIPS (2020, 2023), ICCV (2021, 2023), ICLR (2023, 2024), and ECIR (2021, 2023). Additionally, he has served as a reviewer for multiple AI/ML conferences, i.e., AAAI, CVPR, ECCV, ICCV, ICML, WACV and NeurIPS. Currently, his research primarily focuses on lifelong machine learning in computer vision, efficient neural network training, transferability and domain adaptation, as well as information retrieval and recommender systems.

Anna Dawid

Anna Dawid

Flatiron Institute

Ania is a research fellow at the Center of Computational Quantum Physics of the Flatiron Institute in New York, happily playing with interpretable machine learning for science and ultracold platforms for quantum simulations. She defended her joint Ph.D. in physics and photonics in 2022 at the University of Warsaw and ICFO — The Institute of Photonic Sciences in Spain. Before that, Ania earned an MSc in quantum chemistry and a BSc in biotechnology at the University of Warsaw. Next to authoring papers on quantum physics, the theory of machine learning, and machine learning applications in science, she is the first author of the book "Machine Learning in Quantum Sciences" by Cambridge University Press (in press). She is also a 2022 FNP START laureate, awardee of two NCN grants, and one of the selected participants in the Lindau Nobel Laureate Meeting in 2024.

Tomek Korbak

Tomek Korbak

UK AI Safety Institute

Tomek Korbak is a Senior Research Scientist at the UK AI Safety Institute working on safety cases for frontier models. Previously, he was a Member of Technical Staff at Anthropic working on honesty. Before that, he did a PhD at the University of Sussex focusing on RL from human feedback (RLHF) and spent time as a visiting researcher at NYU working with Ethan Perez, Sam Bowman and Kyunghyun Cho. He studied cognitive science, philosophy and physics at the University of Warsaw.

and more is coming!

/ Venue

As in the previous year, the conference is held at the remarkable Copernicus Science Centre in Warsaw, Poland. The Centre, standing on the bank of the Vistula River is one of the largest science centres in Europe, containing over 450 interactive exhibits.

Address: Wybrzeże Kościuszkowskie 20, 00-390 Warsaw

/ Timeline

1 May

Call for Contributions (Talks, Posters, and Tutorials) submissions open

1 August

Start of Early Bird (selective) registration

31 August, 23:59 (AoE)

Call for Tutorials submissions deadline

31 August, 23:59 (AoE)

Call for Talks and Posters submissions deadline
/ End of Early Bird registration period

7 September

Early bird tickets acceptance notifications

9 September, 18:00 CEST (GMT+2)

Regular tickets sales start

18 September

Talks and posters acceptance notifications

24 October, 18:00 CEST (GMT+2)

Late tickets sales start

7 - 10 November

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/ Strategic sponsor

/ Platinum sponsors

/ Gold sponsors

/ Silver sponsors

/ Partners

/ Honorary Patronages

/ Media partners

/ Organizers

The conference is organized by a non-profit ML in PL Association. We are a group of young people who are determined to bring the best of Machine Learning to Central and Eastern Europe by creating a high-quality event for every ML enthusiast. Although we come from many different academic backgrounds, we are united by the common goal of spreading knowledge about the discipline.

Mateusz Olaf Borowski

Co-Project Leader

Jakub Podolak

Co-Project Leader

Marek Ballaun

Legal Team Coordinator

Kamil Bladoszewski

Finance Team Coordinator

Franciszek Budrowski

Speakers Team Coordinator

Aleksandra Daniluk

Visual Identity Team Coordinator

Adam Dubowski

Meetups Team Coordinator

Maja Jabłońska

Marketing Team Coordinator

Maciej Kaczkowski

Special Ops Team Coordinator

Piotr Komorowski

Panel Team Coordinator

Filip Szatkowski

CfC + Tutorials Team Coordinator

Michał Tyrolski

Speakers Team Coordinator

Emilia Wiśnios

Sponsors Team Coordinator

Marek Wydmuch

Website Team Coordinator

Magdalena Cebula

Marketing Team

Maciej Chrabąszcz

Panel Team

Błażej Dolicki

Sponsors Team

Sebastian Dziadzio

Speakers Team

Zuzanna Glinka

Special Ops Team

Adam Goliński

Speakers Team

Alicja Grochocka-Dorocińska

Panel Team

Piotr Hondra

Meetups Team

Başak Kaplan

Marketing Team

Piotr Kitłowski

Finance Team

Antoni Kowalczuk

Sponsors Team

Ewelina Kędzior

Special Ops Team

Aleksandra Mulewicz

Visual Identity Team

Jakub Myśliwiec
Jakub Myśliwiec

Speakers Team

Karolina Nowacka

Meetups Team

Arkadiusz Paterak

Website Team

Ernest Perkowski

Sponsors Team

Weronika Piotrowska
Weronika Piotrowska

Special Ops Team

Mikołaj Piórczyński

CfC + Tutorials Team

Maciej Pióro

Finance Team

Andrzej Pióro

Sponsors Team

Michał Pstrąg

Website Team

Karol Rogoziński

Finance Team

Patryk Rygiel

CfC + Tutorials Team

Jakub Sobolewski

Sponsors Team

Piotr Sotniczuk
Piotr Sotniczuk

Special Ops Team

Maciej Szymkowski

Speakers Team

Mikołaj Słupiński

CfC + Tutorials Team

Maria Wyrzykowska

CfC + Tutorials Team

Dima Zhylko

Panel Team

Wojciech Łapacz

Marketing Team

Interested in joining our organization? Find out more here.

/ Advisory Board

We have invited a group of outstanding researchers and entrepreneurs to serve on the advisory board of the conference. We consult the event's program with them to guarantee the best scientific level.

Przemysław Biecek

Warsaw University of Technology / University of Warsaw

"We are here to fix Al!" That's the central topic of Przemyslaw Biecek's research on the safety and explainability of artificial intelligence at the Warsaw University of Technology and the University of Warsaw. He leads the MI2.Al team conducting red-teaming of text and image models used in medicine, earth observation, or finance.

Jan Chorowski

University of Wrocław / Pathway

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.

Marek Cygan

University of Warsaw / Nomagic

Marek Cygan is currently an associate professor at the University of Warsaw, leading a newly created Robot learning group, focused on robotic manipulation, reinforcement learning, computer vision and large language models. Additionally, Chief Al Officer and co-founder of Nomagic, a startup delivering smart pick-and-place robots for intralogistics applications. Earlier doing research in various branches of algorithms, with a background in competitive programming, having an ERC Starting grant on the subject.

Krzysztof Dembczyński

Yahoo Research

Prior to joining Yahoo Research Krzysztof Dembczyński was an Assistant Professor at Poznan University of Technology (PUT), Poland. He has received his PhD degree in 2009 and Habilitation degree in 2018, both from PUT. During his PhD studies he was mainly working on preference learning and boosting-based decision rule algorithms. During his postdoc at Marburg University, Germany, he has started working on multi-target prediction problems with the main focus on multi-label classification. Currently, his main scientific activity concerns extreme classification, i.e., classification problems with an extremely large number of labels. His articles has been published at the premier conferences (ICML, NeurIPS, ECML) and in the leading journals (JMLR, MLJ, DAMI) in the field of machine learning. As a co-author he won the best paper award at ECAI 2012 and at ACML 2015. He serves as an Area Chair for ICML, NeurIPS, and ICLR, and as an Action Editor for MLJ.

Krzysztof Geras

New York University

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).

Stanisław Jastrzębski

Molecule.one

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.

Agnieszka Ławrynowicz

Poznan University of Technology

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.

Henryk Michalewski

Google Brain

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. He was working on topology, determinacy of games, logic and automata. Then he turned his interests to more practical games and wrote two papers on Morpion Solitaire. Presenting these papers at the IJCAI conference in 2015 he met researchers from DeepMind and discovered the budding field of deep reinforcement learning. This resulted in a series of papers including Learning from memory of Atari 2600, Hierarchical Reinforcement Learning with Parameters, Distributed Deep Reinforcement Learning: Learn how to play Atari games in 21 minutes and Reinforcement Learning of Theorem Proving.

Piotr Miłoś

IDEAS NCBR / University of Warsaw

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.

Inez Okulska

NASK / Ministry of Digital Affairs Republic of Poland

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.

Razvan Pascanu

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.

Viorica Patraucean

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.

Piotr Sankowski

IDEAS NCBR / University of Warsaw

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 and development center operating in the field of artificial intelligence and digital economy. Piotr Sankowski is also a co-founder of the spin-off company MIM Solutions.

Ewa Szczurek

University of Warsaw

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.

Jacek Tabor

Jagiellonian University (GMUM)

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 Trzcinski (DSc, WUT'20; PhD, EPEL'14; MSc, UPC/PoliTo'10) is an Associate Professor at Warsaw University of Technology, where he leads a Computer Vision Lab. He is also a Computer Vision Group Leader at IDEAS NCBR, a publicly-funded Polish Center for Al. He was an Associate Professor at Jagiellonian University of Cracow (GMUM). He was a Visiting Scholar at Stanford University in 2017 and at Nanyang Technological University in 2019 and 2023. 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.

/ Contact

If you have any question about the event don't hesitate to contact us by email or via our social media: