7 - 10 November / Warsaw, Poland

0 days / 00 hours / 00 minutes / 00 seconds

/ 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.

/ Invited Speakers

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.

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.

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.

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.

Jakub Tomczak photo

Jakub Tomczak

Eindhoven University of Technology

Jakub M. Tomczak is an associate professor and the PI of the Generative AI group at the Eindhoven University of Technology (TU/e). Before joining the TU/e, he was an assistant professor at Vrije Universiteit Amsterdam, a deep learning researcher (Engineer, Staff) in Qualcomm AI Research in Amsterdam, a Marie Sklodowska-Curie individual fellow in Prof. Max Welling's group at the University of Amsterdam, and an assistant professor and a postdoc at the Wroclaw University of Technology. His main research interests include deep generative modeling, deep learning, and Bayesian inference, with applications to image/text processing, Life Sciences, and Molecular Sciences. He serves as an action editor of "Transactions of Machine Learning Research", and an area chair of major AI conferences (e.g., NeurIPS, ICML, AISTATS). He will be a program chair at NeurIPS 2024. He is the author of the book entitled "Deep Generative Modeling", the first comprehensive book on Generative AI. He is also the founder of Amsterdam AI Solutions.

and more is coming!

/ Call for Contributions (Talks, Posters and Tutorials)

We are very excited to invite all to submit proposals for talks, posters, and tutorials for ! Like every year, the majority of the conference program will be dedicated to presenting our participants' work and research.

If you would like to present a talk or a poster, please check the details of the Call for Contributions, that can be found here. And if you are interested in giving a tutorial, the details of Call for Tutorials can be found here.

/ Call for Sponsors

If you would like to sponsor our conference, please get in touch with us at sponsors@conference.mlinpl.org

/ Timeline

1 May

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

1 August

Start of Early Bird (selective) registration

20 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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/ 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 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

Piotr Kitłowski

Finance Team

Antoni Kowalczuk

Sponsors Team

Bartłomiej Krzepkowski

CfC + Tutorials Team

Zuzanna Kwiatkowska

Sponsors Team

Ewelina Kędzior

Special Ops Team

Aleksandra Możwiłło

Visual Identity Team

Jakub Myśliwiec

Speakers Team

Arkadiusz Paterak

Website Team

Ernest Perkowski

Sponsors Team

Weronika Piotrowska
Weronika Piotrowska

Special Ops Team

Mikołaj Piórczyński

CfC + Tutorials Team

Andrzej Pióro

Sponsors Team

Maciej Pióro

Finance Team

Michał Pstrąg

Website Team

Karol Rogoziński

Finance Team

Jakub Sobolewski

Sponsors Team

Piotr Sotniczuk
Piotr Sotniczuk

Special Ops Team

Mikołaj Słupiński

CfC + Tutorials Team

Maciej Szymkowski

Speakers Team

Maria Wyrzykowska

CfC + Tutorials Team

Dima Zhylko

Panel Team

/ 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: