I am a 3rd year PhD Student at KAUST AI Initiative, supervised by Jürgen Schmidhuber . I am interested in reasoning in neural networks. In practice, it means that I mostly work on analyzing and improving transformer architecture, LLMs and (goal-conditioned / hierarchical) reinforcement learning algorithms.
I have 4 years of industry experience. Apart from my 2024 Amazon research internship, I worked for over 3 years as a Deep Learning engineer before starting my PhD. During that time I worked with some of the biggest Polish companies like Allegro, LPP or AmRest.
I studied simultaneously Mathematics (BSc+MSc) and Computer Science (BSc) at the University of Warsaw. I wrote my Master's thesis on improving BERT's mathematical skills under the supervision of Mateusz Malinowski and Henryk Michalewski
Apart from deep learning I enjoy bicycle trips, playing chess and playing some instruments (I play guitar and I am started learning to play the piano).
Don't hesitate to contact me if you have questions about my work, want to chat about research overall or just want to play a chess game!
GCRL NeurIPS 2023 Workshop
Piotr Piękos, Aditya Ramesh, Francesco Faccio, Jürgen Schmidhuber
Robert Csordás, Piotr Piękos, Kazuki Irie, Jürgen Schmidhuber
ICRA 2024
Renzo Cabalero*, Piotr Piękos*, Eric Feron, Jürgen Schmidhuber
* - equal contribution
ACL 2021 (oral)
Piotr Piękos, Henryk Michalewski, Mateusz Malinowski
ICLR 2023 Oral (Notable top 5%)
Michał Zawalski, Michał Tyrolski, Konrad Czechowski, Tomasz Odrzygóźdź. Damian Stachura. Piotr Piękos, Yuhuai Wu, Łukasz Kuciński, Piotr Miłoś
R0-FoMo NeurIPS 2023 Workshop (Best Paper Award)
Mingchen Zhuge, Haozhe Liu, Francesco Faccio, Dylan R Ashley, Róbert Csordás, Anand Gopalakrishnan, Abdullah Hamdi, Hasan Abed Al Kader Hammoud, Vincent Herrmann, Kazuki Irie, Louis Kirsch, Bing Li, Guohao Li, Shuming Liu, Jinjie Mai, Piotr Piękos, Aditya Ramesh, Imanol Schlag, Weimin Shi, Aleksandar Stanić, Wenyi Wang, Yuhui Wang, Mengmeng Xu, Deng-Ping Fan, Bernard Ghanem, Jürgen Schmidhuber
May 2024 - October 2024
Creating hierarchical discrete representations from dense vector representations used for representations of product in the Amazon catalog. The work will be published after going through internal Amazon processes.
June 2023 - Aug 2023
Working on sample efficient Goal-Conditioned RL and improving the speed of the Transformer. The result of that were two publications, "Efficient Value Propagation with the Compositional Optimality Equation " and "SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention".
Sept 2022 - Present
Supervised by Prof. Jürgen Schmidhuber. I am working on generalization, sample efficiency in context of language processing and reinforcement learning.
Jan 2022 - Jul 2022
Working on AdaSubS. Implementing experiments on the sokoban environment
Oct 2021 - Jan 2022
Researching neural search methods for improving search recommendations on the Allegro.pl ("Polish Amazon") platform
May 2020 - Sept 2021
After promising initial results I decided to focus fully on my Master's thesis, the effect of that is the Measuring and Improving BERT's Mathematical Abilities by Predicting the Order of Reasoning paper.
July 2017 - June 2020
In ITmagination I created DL/ML solutions to help other companies. Example projects are: Object detection system for evaluating influencers, recommender system or a system to help with estimating staff needs in physical shops.
piotrpiekos@gmail.com