Resume
Academic Achievements
- - Publications:
- - Explainably Safe Reinforcement Learning (NeurIPS 2025)
- - Symbiotic Local Search for Small Decision Tree Policies in MDPs (UAI 2025)
- - Explaining Control Policies through Predicate Decision Diagrams (HSCC 2025)
- - 1-2-3-Go! Policy Synthesis for Parameterized Markov Decision Processes via Decision-Tree Learning and Generalization (VMCAI 2025)
- - Learning Explainable and Better Performing Representations of POMDP Strategies (TACAS 2024)
- - Bi-Objective Lexicographic Optimization in Markov Decision Processes with Related Objectives (ATVA 2023)
- - Formally-Sharp DAgger for MCTS: Lower-Latency Monte Carlo Tree Search using Data Aggregation with Formal Methods (AAMAS 2023)
- - Safe Learning for Near-Optimal Scheduling (QEST 2021)
- - Monte Carlo Tree Search guided by Symbolic Advice for MDPs (CONCUR 2020)
Research Experience
- - 2023 to 2025: Postdoc at the Learning in Verification lab, Faculty of Informatics, Masaryk University, Brno, working with Prof. Jan Křetínský.
- - Current: Postdoctoral researcher at the College of Computing and Data Science, Nanyang Technological University, Singapore, working with Prof. Luke Ong.
Education
- - PhD: Graduated from the Formal Methods and Verification group, Département d’Informatique, Université Libre de Bruxelles in 2023, supervised by Prof. Jean-François Raskin.
- - MSc: Computer Science, Chennai Mathematical Institute.
- - BSc: Mathematics and Computer Science, Chennai Mathematical Institute.
Background
- Research interests include verification learning, formal methods, and reinforcement learning. Currently a postdoctoral researcher at the College of Computing and Data Science, Nanyang Technological University, Singapore, working with Prof. Luke Ong.
Miscellany
- Contact details:
- - Address: Debraj Chakraborty, College of Computing and Data Science, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore.
- - Email: <firstname>.<lastname><at>ntu.edu.sg