I am a PhD candidate in Computer Science at NTU Singapore, broadly interested in Trustworthy Reinforcement Learning and its applications to safety-critical domains. My research focuses on improving the transparency, safety, robustness, and verifiability of RL policies. Currently, I am exploring neurosymbolic approaches, such as programmatic policies, to enhance trustworthiness by leveraging their inherent interpretability and amenability to formal verification.

In parallel, I have a strong interest in Neurosymbolic AI, particularly in developing end-to-end methods that support explicit knowledge representation and reasoning, integrating both System 1 (intuitive) and System 2 (deliberative) processes. To deepen my conceptual understanding of AI, I actively study foundational mathematical topics such as learning theory, logic, and statistics.

Before joining NTU, I completed my Master’s degree in Computer Science at the Indian Statistical Institute (ISI), Kolkata, India, and my Bachelor’s degree in Electronics and Instrumentation at NIT Silchar, India.

Coming Soon!: Giving Back – a series of notebooks implementing NeSy/RLHF/GenAI models from scratch.

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