Abhinav Verma

Abhinav Verma is an Assistant Professor in Computer Science and Engineering, focusing on reinforcement learning, neural networks, and formal verification of control systems. His research bridges machine learning, program synthesis, and theoretical computer science to ensure interpretable and verifiable AI.

• Research Interests: Reinforcement learning, neurosymbolic AI, policy synthesis, formal guarantees in control systems.
• Key Contributions: Developed frameworks combining neural networks with formal methods for verifiable sequential decision-making, contributed to explainable AI through programmatic policy learning.

Article Trends: Recent work emphasizes temporal logic constraints, counterfactual experience replay, and reduced-variance reinforcement learning. His publications highlight compositional approaches, differentiable programs, and neurosymbolic integration.

Collaborations: Collaborates with institutions and researchers in computer science, with a focus on stochastic systems and interpretable machine learning.