📈 Talk at Learning and Control Colloquium Conference at IIT Bombay
Happy to share that I will present our AAAI work at the LCC organised by CSE and Systems & Control department at IIT Bombay. The logistics of the presentation will be shared soon
I am a Researcher in the Decision Sciences Research Area at TCS Research, driven by a deep passion for leveraging machine learning and operational research to address complex, real-world challenges. My core expertise lies in reinforcement learning and machine learning, with a focus on its practical applications in networked systems.
My academic journey includes an M.Tech. in Electrical Engineering from IIT Gandhinagar, where I contributed to the Department of Science and Technology (DST India) Project on the “Development of a Prosumer Driven Integrated Smart Grid.” During my time at IITGN, I played a key role in developing India’s first peer-to-peer energy trading test rig, a blockchain-enabled testbed (April 2020), in collaboration with IIMA, BESS Yamuna, and Rajdhani Power. This pioneering project, completed in June 2020 under the supervision of Dr. Naran Pindoriya, led to two publications and one patent filing. My contributions were recognized with prestigious awards, including the M.Tech. Grid-India Power Systems Award and the Platinum award from the India Smart Grid Forum (ISGF) in 2023.
At TCS Research, I work closely with Dr. Mayank Baranwal and Dr. Harshad Khadilkar to explore the application of reinforcement learning to complex, uncertain environments. My research focuses on designing RL pipelines to tackle challenges in networked environments, such as power grids, transportation systems, and supply chains, with an emphasis on planning under uncertainty and adversarial conditions. Through this work, I aim to translate cutting-edge theoretical insights into impactful, real-world solutions.
Interests
- Reinforcement Learning
- Generative Artificial Intelligence
- Networked Systems (Power & Transportation)
- Deep Learning
Education
M.Tech. in Electrical Engineering
Indian Institute of Technology, Gandhinagar
B.E. in Electrical Engineering
L.D. College of Engineering
📚 My Research
My research is centered on advancing machine learning techniques, particularly reinforcement learning (RL) and optimization, to tackle complex challenges across various domains. The crux of my work lies in developing intelligent solutions that bridge the gap between theoretical advancements and their practical applications in critical infrastructure.
Networked Systems: I focus on creating robust control and optimization strategies for networked systems, such as power grids, vehicle networks, and railway systems. By enhancing efficiency and reliability, this work aims to bolster the resilience and performance of essential infrastructure.
Supply Chain Management:: I apply machine learning to optimize supply chain operations, directly addressing logistical challenges that impact efficiency and cost-effectiveness. This work is particularly relevant in the context of global supply chain disruptions, where AI-driven solutions can offer significant improvements.
Attention Models for Vehicle Routing: I investigate the use of attention models to solve vehicle routing problems with time windows. This research contributes to advancements in transportation logistics, aiming to improve the efficiency of routing systems in dynamic environments.
Integration of Large Language Models and Reinforcement Learning: I explore novel methodologies that combine large language models (LLMs) with RL to enhance scheduling and optimization across various networked systems, including innovative applications in train scheduling. This interdisciplinary approach seeks to push the boundaries of AI’s capabilities in real-world scenarios.
My research has led to presentations at prestigious conferences, including main track papers at AAAI and ECAI, as well as workshops at NeurIPS. I continue to contribute to the field with ongoing paper submissions and patent applications. My focus remains on advancing reinforcement learning and optimization techniques, particularly in their application to networked systems, where I aim to develop intelligent and efficient solutions for real-world challenges in power, transportation, and related fields.
Recent Publications
(2024).
Optimizing Multi-Robot Task Allocation in Dynamic Environments via Heuristic-Guided Reinforcement Learning.
In 27th Proceedings of the European Conference on Artificial Intelligence, October 2024.
(2024).
An Experimental Evaluation of a Blockchain-based Peer-to-Peer Energy Trading Framework.
In IEEE PES ISGT.
(2024).
A Learning Approach for Discovering Cost-Efficient Integrated Sourcing and Routing Strategies in E-Commerce.
CODS-COMAD 2024.
(2023).
Multi-Agent Learning of Efficient Fulfilment and Routing Strategies in E-Commerce.
GenPlan Workshop, NeurIPS 2023.
(2023).
Reinforcement learning and heuristic based real time power grid management.
Published at US Patent and Trademark Office.
Recent News and Talks
🎉 Nasscom AI Gamechanger Award in Research Category
Happy to share that we have been awarded the NASSCOM AI Gamechangers Award 2024 in the AI Research category for our work on reinforcement learning-based control of power networks. It’s a great honor to be among the top ten research projects.!
✅ Certificate of Merit, Adoption of AI, ML and Robotics Solution, India Smart Grid Forum (ISGF)
Happy to share that our work data-driven control and management of power networks has been awarded with the certificate of merit by the India Smart Grid Forum. This work was published as main track in AAAI 2023.