Hi, I'm Łukasz! My goal is to design artificial intelligence that learns how to solve problems autonomously and in a self-improvement loop.
Hi, I'm Łukasz! My goal is to design artificial intelligence that learns how to solve problems autonomously and in a self-improvement loop.
I am an Assistant Professor at the Polish Academy of Sciences, an Assistant Professor at the University of Warsaw, a Senior Research Scientist at IDEAS, and a member of the ELLIS Society. I am also involved with Ingenix.ai. Recently, I was awarded an OPUS grant for research on debates, Large Language Models (LLMs), and Reinforcement Learning (RL).
I teach Reinforcement Learning and Machine Learning at the University of Warsaw. I regularly review papers for NeurIPS, ICML, ICLR, TMLR, and CoLLAs, including an AC role at NeurIPS24. I am also a member of the Polish AI Olympiad Organizing Committee.
I received my PhD in mathematics from IMPAN and my MSc from the University of Warsaw. Prior to my current position, I led a Solvency 2 internal models team at the Polish Financial Supervision Authority.
See IDEAS website for some PhD research topics.
e-mail: lukasz.kucinski at ideas-ncbr dot pl
Selected publications
Accelerating Goal-Conditioned RL Algorithms and Research
Michał Bortkiewicz, Władek Pałucki, Vivek Myers, Tadeusz Dziarmaga, Tomasz Arczewski, Łukasz Kuciński, Benjamin Eysenbach
ICLR 2025, spotlight (5% acceptance rate)
BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games
Davide Paglieri, Bartłomiej Cupiał, Samuel Coward, Ulyana Piterbarg, Maciej Wolczyk, Akbir Khan, Eduardo Pignatelli, Łukasz Kuciński, Lerrel Pinto, Rob Fergus, Jakob Nicolaus Foerster, Jack Parker-Holder, Tim Rocktäschel
ICLR 2025
Structured Packing in LLM Training Improves Long Context Utilization
Konrad Staniszewski, Szymon Tworkowski, Yu Zhao, Sebastian Jaszczur, Henryk Michalewski, Łukasz Kuciński, Piotr Miłoś
AAAI 2025
Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem
Maciej Wołczyk, Bartłomiej Cupiał, Mateusz Ostaszewski, Michał Bortkiewicz, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś
ICML 2024, spotlight (3.5% acceptance rate)
Magnushammer: A Transformer-based Approach to Premise Selection
Maciej Mikuła, Szymon Antoniak, Szymon Tworkowski, Bartosz Piotrowski, Albert Qiaochu Jiang, Jin Peng Zhou, Christian Szegedy, Łukasz Kuciński, Piotr Miłoś, Yuhuai Wu
ICLR 2024, top-50 average score 8.0
Trust Your ∇: Gradient-based Intervention Targeting for Causal Discovery
Mateusz Olko, Michał Zając, Aleksandra Nowak, Nino Scherrer, Yashas Annadani, Stefan Bauer, Łukasz Kuciński, Piotr Miłoś
NeurIPS 2023
Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
Michał Zawalski, Michał Tyrolski, Konrad Czechowski, Damian Stachura, Piotr Piękos, Tomasz Odrzygóźdź, Yuhuai Wu, Łukasz Kuciński, Piotr Miłoś
ICLR 2023, notable-top-5%
Disentangling Transfer in Continual Reinforcement Learning
Maciej Wołczyk, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś
NeurIPS 2022
Continual World: A Robotic Benchmark For Continual Reinforcement Learning
Maciej Wołczyk, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś
NeurIPS 2021
Subgoal Search For Complex Reasoning Tasks
Konrad Czechowski, Tomasz Odrzygóźdź, Marek Zbysiński, Michał Zawalski, Krzysztof Olejnik, Yuhuai Wu, Łukasz Kuciński, Piotr Miłoś
NeurIPS 2021
Łukasz Kuciński, Tomasz Korbak, Paweł Kołodziej, Piotr Miłoś
NeurIPS 2021
Selected preprints
BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games
Davide Paglieri, Bartłomiej Cupiał, Samuel Coward, Ulyana Piterbarg, Maciej Wolczyk, Akbir Khan, Eduardo Pignatelli, Łukasz Kuciński, Lerrel Pinto, Rob Fergus, Jakob Nicolaus Foerster, Jack Parker-Holder, Tim Rocktäschel
2024
Accelerating Goal-Conditioned RL Algorithms and Research
Michał Bortkiewicz, Władek Pałucki, Vivek Myers, Tadeusz Dziarmaga, Tomasz Arczewski, Łukasz Kuciński, Benjamin Eysenbach
2024
GUIDE: Guidance-based Incremental Learning with Diffusion Models
Bartosz Cywiński, Kamil Deja, Tomasz Trzciński, Bartłomiej Twardowski, Łukasz Kuciński
2024
tsGT: Stochastic Time Series Modeling With Transformer
Łukasz Kuciński, Witold Drzewakowski, Mateusz Olko, Piotr Kozakowski, Łukasz Maziarka, Marta Emilia Nowakowska, Łukasz Kaiser, Piotr Miłoś
2024
Teaching:
University of Warsaw: Reinforcement Learning, Summer 2021, Summer 2022, Summer 2023, Summer 2024.
University of Warsaw: Machine Learning Seminar, Fall 2021, Summer 2022, Fall 2022, Summer 2023, Fall 2024, Summer 2024.