About me
Welcome, I'm Pavol, currently a co-founder and CTO at LatticeFlow. Before that, I obtained my PhD in the Secure, Reliable, and Intelligent Systems Lab, supervised by Prof. Martin Vechev. My main research interests include Programming Languages, Program Synthesis and Machine Learning.Publications
2024
COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act
Philipp Guldimann, Alexander Spiridonov, Robin Staab, Nikola Jovanović, Mark Vero, Velko Vechev, Anna Gueorguieva, Mislav Balunović, Nikola Konstantinov, Pavol Bielik, Petar Tsankov, Martin Vechev
arXiv
2024
2021
Automated Discovery of Adaptive Attacks on Adversarial Defenses
Chengyuan Yao, Pavol Bielik, Petar Tsankov, Martin Vechev
NeurIPS
2021
Machine Learning for Health -- Algorithm Auditing & Quality Control
Luis Oala, Andrew G. Murchison, Pradeep Balachandran, Shruti Choudhary, Jana Fehr, Alixandro Werneck Leite, Peter G. Goldschmidt, Christian Johner, Elora D. M. Schorverth, Rose Nakasi, Martin Meyer, Federico Cabitza, Pat Baird, Carolin Prabhu, Eva Weicken, Xiaoxuan Liu, Markus Wenzel, Steffen Vogler, Darlington Akogo, Shada Alsalamah, Emre Kazim, Adriano Koshiyama, Sven Piechottka, Sheena Macpherson, Ian Shadforth, Regina Geierhofer, Christian Matek, Joachim Krois, Bruno Sanguinetti, Matthew Arentz, Pavol Bielik, Saul Calderon-Ramirez, Auss Abbood, Nicolas Langer, Stefan Haufe, Ferath Kherif, Sameer Pujari, Wojciech Samek, Thomas Wiegand
Journal of Medical Systems
2021
Automated Discovery of Adaptive Attacks on Adversarial Defenses
Chengyuan Yao, Pavol Bielik, Petar Tsankov, Martin Vechev
AutoML@ICML
2021
Oral
Oral
Robustness Certification with Generative Models
Matthew Mirman, Alexander Hägele, Timon Gehr, Pavol Bielik, Martin Vechev
PLDI
2021
2020
Adversarial Attacks on Probabilistic Autoregressive Forecasting Models
Raphaël Dang-Nhu, Gagandeep Singh, Pavol Bielik, Martin Vechev
ICML
2020
Guiding Program Synthesis by Learning to Generate Examples
Larissa Laich, Pavol Bielik, Martin Vechev
ICLR
2020
2019
Learning to Infer User Interface Attributes from Images
Philippe Schlattner, Pavol Bielik, Martin Vechev
ArXiv
2019
2018
Robust Relational Layouts Synthesis from Examples for Android
Pavol Bielik, Marc Fischer, Martin Vechev
ACM OOPSLA
2018
2017
Program Synthesis for Character Level Language Modeling
Pavol Bielik, Veselin Raychev, Martin Vechev
ICLR
2017
2016
Probabilistic Model for Code with Decision Trees
Veselin Raychev, Pavol Bielik, Martin Vechev
ACM OOPSLA
2016
Learning Programs from Noisy Data
Veselin Raychev, Pavol Bielik, Martin Vechev, Andreas Krause
ACM POPL
2016
SDNRacer: Concurrency Analysis for Software-Defined Networks
Ahmed El-Hassany, Jeremie Miserez, Pavol Bielik, Laurent Vanbever, Martin Vechev
ACM PLDI
2016
2015
SDNRacer: Detecting Concurrency Violations in Software-Defined Networks
Jeremie Miserez, Pavol Bielik, Ahmed El-Hassany, Laurent Vanbever, Martin Vechev
SOSR
2015
Scalable Race Detection for Android Applications
Pavol Bielik, Veselin Raychev, Martin Vechev
ACM OOPSLA
2015
Programming with Big Code: Lessons, Techniques and Applications
Pavol Bielik, Veselin Raychev, Martin Vechev
SNAPL
2015
Awards
- Facebook PhD Fellow, 2017
- Received Romberg Grant at 4th Heidelberg Laureate Forum (1 out of 40), 2016
- Selected to participate at 4th Heidelberg Laureate Forum (1 out of 200), 2016
- Finalist - Facebook Fellowship (1 out of 31), 2016
- Selected to participate at Google’s 2nd PhD Student Summit on Compiler & Programming Technology, 2014
- Represented ETH Zurich at University Mobile Challenge World Finals, 2013
- 1st place - Students project of the year 2011, Czech and Slovak ACM Chapter, 2011
- Excellence scholarship, Slovak University of Technology, 2009, 2010, 2011
Education
ETH Zurich, since 2015 PhD in Computer Science
ETH Zurich, 2012–2014 MSc in Computer Science
Slovak University of Technology, Faculty of Informatics and Information Technology, 2008–2011 BSc in Informatics