Scholar
Piotr Piękos
Google Scholar ID: XkmDf7gAAAAJ
KAUST
Citations & Impact
Citations
187
H-index
4
i10-index
4
Publications
10
Co-authors
0
Publications
Resume
Academic Achievements
- Published in top ML conferences such as NeurIPS, ACL, ICLR, or ICRA, with two papers being presented orally at ACL and ICLR.
Research Experience
- Applied Scientist Intern at Amazon (May 2024 - October 2024), creating hierarchical discrete representations; Research Intern at IDSIA (June 2023 - Aug 2023), working on sample-efficient goal-conditioned RL; Over 3 years as a Deep Learning engineer before starting his PhD, collaborating with major Polish companies like Allegro, LPP, or AmRest.
Education
- BSc+MSc in Mathematics and BSc in Computer Science from the University of Warsaw. Master's thesis on improving BERT's mathematical skills, supervised by Mateusz Malinowski and Henryk Michalewski.
Background
- Research Interests: Scalable methods for improving reasoning in neural networks, Mixture-of-Experts, analyzing and improving transformer architecture, LLMs, and (goal-conditioned/hierarchical) reinforcement learning algorithms. Briefly: A 4th-year PhD Candidate at KAUST AI Initiative, supervised by Prof. Jürgen Schmidhuber.
Miscellany
- Personal interests include bicycle trips, playing chess, and playing musical instruments (guitar and piano).