I am a Senior Lecturer at the Optimisation research group of the Faculty of Information Technology of Monash University.
Previously, I was a postdoctoral researcher supervised by Joao Marques-Silva and then a researcher at the Reason Lab, Faculty of Sciences, University of Lisbon, working on various topics related to computing and reasoning with SAT oracles, among many other problem areas.
I did my Ph.D. (candidate of physico-mathematical sciences in Russia) under the supervision of Alexander A. Semenov at Matrosov Institute for System Dynamics and Control Theory, a research institute of the Russian Academy of Sciences. My thesis was about combining conflict-driven clause learning (CDCL) with binary decision diagrams (BDDs) done in parallel.
Currently, my research is mainly focused on the development and improvement of highly efficient SAT- and SMT-based (satisfiability modulo theories) decision and optimization procedures targeting a variety of important practical applications in AI: from software package upgradability and Boolean formula minimization to model-based diagnosis (MBD), software fault localization and eXplainable AI (XAI).
|Oct 16, 2021||Our paper “Delivering Trustworthy AI through Formal XAI” (coauthored together with Joao Marques-Silva) is accepted at AAAI 2022!|
|Oct 12, 2021||Our article “Learning Optimal Decision Sets and Lists with SAT” (coauthored together with Jinqiang Yu, Peter J. Stuckey and Pierre Le Bodic) is accepted to JAIR!|
|Jun 28, 2021||Our article “Propositional Proof Systems Based on Maximum Satisfiability” (coauthored together with Maria Luisa Bonet, Sam Buss, Antonio Morgado, and Joao Marques-Silva) is accepted to AIJ!|
|Jun 15, 2021||Our paper “On Efficiently Explaining Graph-Based Classifiers” (coauthored together with Xuanxiang Huang, Yacine Izza, and Joao Marques-Silva) is accepted at KR 2021!|
|May 8, 2021||Our paper “Explanations for Monotonic Classifiers” (coauthored together with Joao Marques-Silva, Thomas Gerspacher, Martin Cooper, and Nina Narodytska) is accepted at ICML 2021!|