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 |
Missed out on ticket sales? We've set aside a very limited number of tickets just for you. Currently all tickets are sold out 😎
| Ticket | Late Price |
|---|---|
| Student | 1200 PLN |
| Regular | 1200 PLN |
First-come-first-served registration for tutorials. Starts 21 October, 18:00 CEST (GMT+2) and last until all tickets are sold out.
| Ticket | Price |
|---|---|
| Student | 60 PLN |
| Regular | 120 PLN |
ML in PL Conference 2024 is the 8th edition of an annual conference focused on the best of Machine Learning both in academia and in business. Join us and...
Attend a stellar lineup of keynote and invited lectures of internationally recognized researchers, learn about state-of-the-art, and get inspired.
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.
Experience a friendly and inclusive atmosphere. Engage in meaningful conversations and establish lasting connections with other machine learning enthusiasts.
Bernardino Romera Paredes 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 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 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 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.
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.
Jan Peters is a full professor (W3) for Intelligent Autonomous Systems at the Computer Science Department of the Technische Universitaet Darmstadt. Jan Peters has received the Dick Volz Best 2007 US PhD Thesis Runner-Up Award, the Robotics: Science & Systems – Early Career Spotlight, the INNS Young Investigator Award, and the IEEE Robotics & Automation Society’s Early Career Award as well as numerous best paper awards. In 2015, he received an ERC Starting Grant and in 2019, he was appointed as an IEEE Fellow and in 2020 an ELLIS fellow.
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.
Yuki Asano is the head of the Fundamental AI (FunAI) Lab and full Professor at the University of Technology Nuremberg. Prior to this, Yuki lead the QUVA lab at the University of Amsterdam, where he closely collaborated with Qualcomm AI Research. His PhD was at the Visual Geometry Group (VGG) at the University of Oxford, where he worked with Andrea Vedaldi and Christian Rupprecht. Also, he loves running, the mountains, and their combination.
Lucas Beyer 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 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 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.
Join us for AI Audio Challenge, a competition organised by ElevenLabs in partnership with ML in PL Conference 2024, open to all enthusiasts of applied AI. Participating teams are asked to develop a solution leveraging ElevenLabs audio AI technologies.
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.
Organized in cooperation with OCTO Legal. Moderators: Marek Ballaun, Emilia Wiśnios
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.
Prof. Michał Jackowski - Executive MBA at ESCP Europe, International Cooperation Leader of the AI Working Group at the Ministry of Digitital Affairs, member of Plenary Group drafting LLM Code of Practice for EU AI Office, law professor (SWPS University), attorney and tax advisor with over 20 years of experience as an entrepreneur. Advisor and representative of the technology industry in difficult legislative processes. Co-founder of DSK Law Firm - a law and tax firm specializing in advising the IT sector, and co-founder of innovative startups AnyLawyer and LexDigital. Arbitrator of the arbitration court at the Polish Chamber of Information Technology and Telecommunications. Advisor and representative of the technology industry in difficult legislative processes. Author of several books and numerous scientific publications in the field of law. A promoter of knowledge at the intersection of law and AI - he hosts the Monday Bagel podcast on YT, where he regularly publishes interviews with scientists, legal practitioners and AI experts. Privately - he is a marathon runner and skier, and enjoys reading books - especially about digital transformation in the future, medieval history and Asian culture.
Alkan Dogan is the European Lead for Legal Engineering at Simmons & Simmons Wavelength. Based in Frankfurt, he is spearheading the firm’s legal engineering activities and projects across Europe. Alkan specializes in initiating and creating tech-driven solutions for our clients to ensure a streamlined delivery of legal services. This includes the utilization of technology, data analytics, AI, design thinking and process optimization techniques to increase usability and efficiency of client processes. In addition to his position as European Lead for Legal Engineering, Alkan is currently pursuing a doctorate degree (Dr. rer. pol.) at the Friedrich Schiller University in Jena. His field of study focuses on the impact of behavioural biases on effective innovation management and measures to mitigate these effects as an organization.
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.
Moderators: Alicja Grochocka-Dorocińska, Maciej Chrabąszcz
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.
Leiden University
Ania is an assistant professor at the Leiden Institute of Advanced Computer Science (LIACS) at Leiden University in the Netherlands, happily playing with interpretable machine learning for science, ultracold platforms for quantum simulations, and the theory of machine learning. Before joining LIACS, she was a research fellow at the Center of Computational Quantum Physics of the Flatiron Institute in New York. In 2022, she defended her joint Ph.D. in physics and photonics under the supervision of Prof. Michał Tomza (Faculty of Physics, University of Warsaw, Poland) and Prof. Maciej Lewenstein (ICFO – The Institute of Photonic Sciences, Spain). Before that, she did an MSc in quantum chemistry and a BSc in biotechnology at the University of Warsaw. Ania 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.
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.
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.
Moderators: Błażej Dolicki, Aleksandra Daniluk
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.
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.
MIM Fertility
Piotr Wygocki, PhD, is the Co-Founder and CEO of MIM Fertility, a Polish deep tech company developing AI solutions tailored to the needs of IVF clinics. He is also the Co-Founder of MIM Solutions, a software house specializing in MedTech innovations. Piotr Wygocki holds a Ph.D. in Informatics and dual master's degrees in Informatics and Mathematics from the University of Warsaw, where he serves as an Assistant Professor. A winner of KaggleDays Warsaw 2019. He is a member of the AIFS and the Business Advisory Group to EC President Ursula von der Leyen for the Global Gateway Programme. He has also earned recognition in the Deloitte Technology Fast 50 Central Europe 2023.
Join us for the “AI Safety” panel, powered by ElevenLabs, where we will discuss real-world challenges of building and assessing models for safety, while maintaining top performance. We will explore ways for AI manipulation, as well as automated and human-in-the-loop systems for preventing misuse.
Moderator: Aleksandra Pedraszewska
ElevenLabs
Aleksandra leads AI Safety Operations at ElevenLabs – the most realistic AI audio tool for generating speech, voices and dubbing of content in 32 languages, with over 1 million users (including TIME, HarperCollins, and nvidia) and $1.1bn valuation. She is responsible for ensuring that ElevenLabs’ products are developed, deployed, and used in a safe way, maximising audio AI's transformative potential. Aleksandra has extensive operational experience, having directed a venture-backed deep tech company for 7 years, and holds an MPhil in Technology Policy from Cambridge Judge Business School, and a BA from the University of Cambridge. She supports IP-driven companies as an Entrepreneur-in-Residence at Cambridge and a mentor at Conception X.
Cohere
Anna is a Machine Learning Engineer at Cohere, a provider of foundational LLM models for enterprise customers. Her work focuses on post-training techniques to customize models and ensure safety, consistency, and accuracy, while also designing evaluation frameworks to assess model performance. Previously, she worked as a Quant at Goldman Sachs and as a Natural Language Data Scientist at Harvard Business School. Anna holds a Bachelor's degree in Computer Science from Oxford University and a Master's in Data Science from Harvard University. Her research on adversarial attacks on large language models was featured at ICML 2023.
Lakera AI
Julia is a Machine Learning Engineer at Lakera AI, developing their core product. Lakera AI is a frontrunner in AI security, known for empowering developers to build secure AI applications with Lakera Guard, which protects against prompt injections, data leaks, and other risks. Her career trajectory includes internships at Google, DeepMind, and IBM Research. Julia earned her Bachelor's degree in Computer Science from the University of Warsaw and completed her Master's at ETH Zurich in 2023. Her professional interests are in Machine Learning for Natural Language Processing, AI security, and performance optimization of ML systems.
Human In the Loop / UCL
Matija is an AI Safety Researcher who has worked with OpenAI, DeepMind, the AI Objectives Institute, ContextualAI, and Mercor on advancing methods for collecting human data for post-training, developing evals and benchmarks. His work on AI Manipulation and General Purpose AI Systems has impacted the EU AI Act, and he is currently involved in crafting the Codes of Practice for the EU AI Office. He holds a BA/MSc in Psychological Sciences and Experimental Psychology from the University of Cambridge, and completed his PhD in Cognitive Science at the Causal Cognition Laboratory, at University College London.
Georgy Marchuk is a Software Engineer at ElevenLabs – the most realistic AI audio tool for generating speech, voices and dubbing of content in 32 languages, with over 1 million users (including TIME, HarperCollins, and nvidia). Georgy oversees the development of new product features within the self-serve platform and developer APIs, optimises data collection processes, and ensures the safety of AI systems. He is passionate about applying AI in practical, real-world contexts, always looking for ways to make cutting-edge technologies more accessible and impactful. Before joining ElevenLabs, Georgy was a member of technical staff at Pipedrive, a leading CRM platform, where he worked with the core platform and drove new products from zero to shipped. Prior to that, he held various design engineering positions. Georgy is deeply involved in open-source communities, running the Open Source Software Institute and co-hosting the Rebase podcast, where he meets the biggest names of open-source technology. He holds a BSc in Computing from Teesside University.
Alicja Rączkowska is a Senior Research Engineer in the Machine Learning Research team at Allegro, where she works on applying and advancing NLP methods in the e-commerce domain. She is also a postdoc at IDEAS NCBR, working on explainability and uncertainty in digital pathology. Obtained her PhD from the University of Warsaw, where she focused on machine learning methods for histopathology.
Dr Charles Martinez is the Academic Relations Manager at G-Research. Charles completed a PhD in Phonon interactions in Gallium Nitride nanostructures at the University of Nottingham. 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 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.
Scarlett Bailey is currently an intern in the Talent Acquisition department at G-Research, completing her placement year while studying for a BSc in Management at the University of Bath. As part of the team, Scarlett supports recruitment for the Summer Research Programme and other internship opportunities, with a focus on engaging emerging talent in quantitative research and technology. She also contributes to G-Research's global attraction events, connecting students with career opportunities across the company.
Long Cheng is an Engineering Leader at Google Cloud Vertex AI - a unified machine learning (ML) platform that aims to streamline the entire ML workflow, making it easier for data scientists and ML engineers to build, deploy, and scale AI models. Vertex AI offers a comprehensive suite of tools to manage every stage of the ML development lifecycle, from data preparation and model training to deployment, monitoring, and maintenance. As the site lead for Google Cloud Vertex AI in Poland, Long spearheads the development of MLOps infrastructure (Model training pipelines, Model Garden, Fine-tuning and etc.) and AI serving infrastructure for both online and batch predictions of Gemini and other pretrained AI models, leveraging GPU and TPU acceleration. Long brings a wealth of experience in product strategy and cross-functional leadership, effectively guiding engineering and product management teams to achieve evolving business goals. Prior to that, he gained over 12 years of experience in the U.S. as a lead engineer with top tech companies such as Google, Oracle and Microsoft.
Tomasz Sapiński is a highly experienced IT professional with a strong background in software development and image processing using AI. He holds a degree from Lodz University of Technology and has spent over 15 years in the industry, gaining extensive experience in project management and IT system implementations around the world. Tomasz is also a skilled Data Scientist with a keen interest in the development of AI and neural networks, and their practical applications.
Przemysław Spurek is the leader of the Neural Rendering research team at IDEAS NCBR and a researcher in the GMUM group operating at the Jagiellonian University in Krakow. In 2014, he defended his PhD in machine learning and information theory. In 2023, he obtained his habilitation degree and became a university professor. He has published articles at prestigious international conferences such as NeurIPS, ICML, IROS, AISTATS, ECML. He co-authored the book Głębokie uczenie. Wprowadzenie [Deep Learning. Introduction] – a compendium of knowledge about the basics of AI. He was the director of PRELUDIUM, SONATA, OPUS and SONATA BIS NCN grants. Currently, his research focuses mainly on neural rendering, in particular NeRF and Gaussian Splatting models.
Daniel Śliwiński holds a master's degree in Data Science and Business Analytics from the University of Warsaw, where he focused on exploring the intersection of airline e-commerce and machine learning. He also has a bachelor's degree in Japanese Studies. Currently, Daniel is a Junior Data Scientist at LOT Polish Airlines, where he has contributed to various projects for over two years, working primarily on personalization, segmentation, forecasting, and big data initiatives. Outside of work, Daniel trains in Olympic weightlifting and competes in triathlon.
Patryk Radoń with a bachelors and master's degree from Cracow's AGH and Cracow University of Technology, he has honed his skills in data science over five years of practical experience. Currently working at LOT Polish Airlines, he specializes in modeling customer behavior with statistical background in causal inference and customer personalization, focused primarily on areas related to CRM and ecommerce. His expertise lies in leveraging data to drive business growth, optimize customer interactions, and enhance marketing strategies. In his free time he strives to balance his time between rock climbing, traveling and practicing martial arts.
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Join our conference game, engage with the other participants and sponsors, gather your dataset, discover the mapping function, and win prizes!
Below we present the draft of the conference agenda, it may change. The details will be announced in the following days.
We were very excited to invite all to submit proposals for contributed talks and posters for ML in PL Conference 2024!
This year we accepted 24 talks, 63 posters and 6 tutorials that were presented during the main conference. A list of talks and posters can be found in the full program of the conference. Results of the Best Contributed Talk and Poster Award can be found here.
A detailed description of the Call for Contribution can be found here, and Call for Tutorials here.
As in the previous year, the main 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.
The tutorials will be held at the Faculty of Mathematics, Informatics and Mechanics, University of Warsaw.
Address: Stefana Banacha 2, 02-097 Warsaw
For the first time, as an accompanying event to the conference, we are organizing a completely free festival dedicated to explore the intersection of Art and AI.
Learn more about the festival1 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
ML in PL Conference 2024
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.
Co-Project Leader
Co-Project Leader
Legal Team Coordinator
Finance Team Coordinator
Speakers Team Coordinator
Visual Identity Team Coordinator
Meetups Team Coordinator
Marketing Team Coordinator
Special Ops Team Coordinator
Panel Team Coordinator
CfC + Tutorials Team Coordinator
Speakers Team Coordinator
Sponsors Team Coordinator
Website Team Coordinator
Marketing Team
Panel Team
Sponsors Team
Speakers Team
Special Ops Team
Speakers Team
Panel Team
Meetups Team
Marketing Team
Finance Team
Sponsors Team
Special Ops Team
Visual Identity Team
Speakers Team
Meetups Team
Website Team
Sponsors Team
Special Ops Team
CfC + Tutorials Team
Finance Team
Sponsors Team
Website Team
Finance Team
CfC + Tutorials Team
Sponsors Team
Special Ops Team
Speakers Team
CfC + Tutorials Team
CfC + Tutorials Team
Panel Team
Marketing Team
Interested in joining our organization? Find out more here.
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.
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.
Pathway
Jan Chorowski is the CTO at Pathway building Live AI systems, underpinned by a proprietary real-time data processing engine and an AI framework. He received his M.Sc. degree in electrical engineering from Wrocław University of Technology and Ph.D. from University of Louisville. He has worked at the University of Wroclaw and has collaborated with several research teams, including Google Brain, Microsoft Research and Yoshua Bengio’s lab.
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.
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.
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).
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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