Responsibilities and key contributions include: - Leading research projects in the Data and Decision Sciences research wing under the mentorship of Dr. Mayank Baranwal and Dr. Harshad Khadilkar.

• Focusing on real-world applications of reinforcement learning (RL) to address complex challenges in planning under uncertainty, with key areas of expertise including:

  • Data-driven power control and management systems.
  • Supply chain network optimization.
  • Advanced railway scheduling, leveraging large language models (LLMs) for enhanced decision-making.
  • Mixed-Fleet Vehicle Routing Problem with Time Windows (CVRPTW), utilizing attention mechanisms for improved logistics.
  • Multi-robot task allocation for dynamic and efficient resource management.

• Currently working on the Mixed-Fleet Vehicle Routing Problem with Time Windows (VRPTW), integrating traditional and electric vehicles to optimize logistics in response to the increasing adoption of EVs by fleet operators. Additionally, exploring innovative applications of attention models to enhance solutions for vehicle routing with time windows.

• Investigating the integration of large language models (LLMs) with reinforcement learning (RL) to enhance RL agent reward mechanisms, particularly for optimizing train scheduling. This approach reduces excessive computational complexity and supports control room operators in making more efficient decisions.

• Contributing to the development of robust and adaptive algorithms for networked systems, enhancing efficiency and reliability in critical infrastructure.

I currently serve as an Adjunct Faculty, where I am responsible for teaching courses to first-year undergraduate students, including - Introduction to Programming - Introduction to Data Science