26 - 29 October / Warsaw, Poland

0 days / 00 hours / 00 minutes / 00 seconds

/ About the event

is the 7th 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.

Bigger and better than ever!

We are excited to announce that this year, the main part of the conference will take place at the remarkable Copernicus Science Centre in Warsaw. Thanks to this change, we will be able to host more attendees and provide you with the best experience ever!

/ Timeline

1 June

Call for Contributions (Talks and Posters) open

1 August

Start of Early Bird (selective) registration

1 September

Call for Contributions submissions deadline / End of Early Bird registration period

7 September

Talks and posters acceptance notifications

11 September

Regular ticket sales start

26 - 29 October

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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.

Emilia Wiśnios

Project Leader

Maciej Pióro

Vice Project Leader

Marek Ballaun

Legal Team Coordinator

Franek Budrowski

Speakers Team Coordinator

Maciej Chrabąszcz

Panel Team Coordinator

Karolina Cwojdzińska

Finance Coordinator

Adam Dubowski

Sponsors Coordinator

Maja Jabłońska

Marketing Coordinator

Jakub Myśliwiec

Visual Identity Coordinator

Filip Szatkowski

Call for Contributions Coordinator

Michał Tyrolski

Speakers Team Coordinator

Marek Wydmuch

Infrastructure Team Coordinator

Maria Wyrzykowska

Premeetings Coordinator

Mateusz Borowski

Sponsors Team

Magdalena Cebula

Marketing Team

Sebastian Dziadzio

Sponsors Team

Alicja Grochocka

Panel Team

Piotr Hondra

Premeetings and Tutorials Team

Maciej Kaczkowski

Special Ops Team

Piotr Komorowski

Panel Team

Antoni Kowalczuk

Sponsors Team

Andrzej Krupka

Marketing Team

Bartek Krzepkowski
Bartek Krzepkowski

Registration Team

Piotr Kucharski

Speakers Team

Zuzanna Kwiatkowska

Marketing Team

Dawid Mączka
Dawid Mączka

Infrastructure Team

Ernest Perkowski

Sponsors Team

Weronika Piotrowska
Weronika Piotrowska

Registration Team

Mikołaj Piórczyński

Call for Contributions Team

Andrzej Pióro

Special Ops Team

Jakub Podolak

Panel Team

Karolina Romanowska

Premeetings and Tutorials Team

Kacper Skonieczka

Research Platform Team

Jakub Sobolewski

Sponsors Team

Piotr Sotniczuk

Call for Contributions Team

Mikołaj Słupiński

Call for Contributions Team

Jakub Walendowski

Infrastructure Team

Joanna Wojciechowska
Joanna Wojciechowska

Sponsors Team

Dima Zhylko

Special Ops Team

Alicja Ziarko

Infrastructure Team

/ Scientific Board

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

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.

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.

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.

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.

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 assistant 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).

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 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.

Piotr Miłoś

University of Warsaw

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.

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

Przemysław Biecek

Warsaw University of Technology, University of Warsaw

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.

Razvan Pascanu


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.

Stanisław Jastrzębski


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.

Tomasz Trzciński

Warsaw University of Technology, Tooploox, Jagiellonian University

Tomasz Trzciński is an Associate Professor at Warsaw University of Technology since 2015, where he leads a Computer Vision Lab. 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 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.

Viorica Patraucean


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.

/ Contact

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