Research
What I work on, what I've published, and what's in progress.
✦ Research Interests
I work on making hardware verification more reliable and more automatic. Two questions drive most of it: can LLM agents write and repair the assertions that verification engineers currently write by hand — and how do multiple learning agents coordinate when they share an environment? The first is my day-to-day work at ISI Kolkata; the second is multi-agent reinforcement learning, the direction I want to take a PhD in.
▸ News
- 2026
SuperSAGA accepted at ASP-DAC 2026 (Special Sessions).
- 2026
VISTA submitted to the ACM Journal on Emerging Technologies in Computing Systems.
- 2025
LLM-Guided Reconciliation for Explainable Robotic Path Planning accepted at IEEE ACSOS 2025.
- 2025
LISA accepted at IEEE ISVLSI 2025.
- Jul 2024
Joined the Indian Statistical Institute, Kolkata as a Research Engineer.
◆ Publications
Formal Verification and Agentic AI
Subhajit Paul, Ansuman Banerjee, Sumana Ghosh
Accepted at IEEE Computer Society Annual Symposium on VLSI (ISVLSI 2025)
Indian Statistical Institute, Kolkata
Subhajit Paul, Ansuman Banerjee, Sumana Ghosh
Accepted at 31st Asia and South Pacific Design Automation Conference (ASP-DAC Special Sessions 2026)
Indian Statistical Institute, Kolkata
VISTA: An Agentic Workflow for Formal Verification Environment Synthesis
2026Subhajit Paul, Ansuman Banerjee, Sumana Ghosh
Under Review and Submitted to the ACM Journal on Emerging Technologies in Computing Systems
Indian Statistical Institute, Kolkata
LLMs in Robotics
Subhajit Paul, Ansuman Banerjee
Accepted at IEEE Autonomic Computing and Self-Organizing Systems (ACSOS 2025)
Indian Statistical Institute, Kolkata
● Ongoing Research Work
Multi-Agent Reinforcement Learning
Exploring cooperative and competitive learning among autonomous agents, focusing on coordination, credit assignment, and emergent behaviour in complex multi-agent settings.
LLM-based Agentic Systems
Building tool-augmented, supervisor-subordinate LLM agents that plan, reason, and self-correct to automate formal verification and environment synthesis within EDA pipelines.
✎ Resources I Learn From
Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
Albrecht, Christianos & Schäfer
MIT Press — free PDF available
Reinforcement Learning: An Introduction (2nd ed.)
Sutton & Barto
The RL foundation text — free online
Reinforcement Learning Course (UCL × DeepMind)
David Silver
Lectures + slides
Intro to Large Language Models
Andrej Karpathy
The best 1-hour LLM primer
SVA: The Power of Assertions in SystemVerilog
Cerny, Dudani, Bergeron & Korchemny
The SystemVerilog Assertions reference
