Chandreyee Bhowmick

Graduate Research Assistant

Chandreyee Bhowmick

Chandreyee is a Ph.D. student at Vanderbilt University, in the Electrical Engineering Department. Her research is focused on designing resilient algorithms in the areas of distributed machine learning and multi-agent reinforcement learning. We use the idea of resilient aggregation to ensure satisfactory performance of the agents in the presence of Byzantine attacks. Another focus of her research is the applications of graph machine learning in designing decentralized controllers for swarms, while ensuring robustness against adversarial agents.

Prior to joining Vanderbilt, Chandreyee worked as a research assistant at Missouri University of Science and Technology. Her research at this school focused on the security of networked control systems, for which she designed novel detection and mitigation algorithms for different types of attacks. She has looked into the problem of detecting intelligent attacks by incorporating learning or adaptation in the control methodology.

Before starting her doctoral studies, Chandreyee pursued a master's degree from the Indian Institute of Technology (IIT) Kanpur, which was followed by a short appointment as a project engineer. She worked in the Intelligent Systems and Control Laboratory, where her research focus was on the control of multi-agent systems in a specific formation and target tracking.

Chandreyee has a strong background in various control methods and schemes, which include, but are not limited to adaptive control, neural-network-based control, optimal control, nonlinear control, discrete neural control, robust control, etc. She also has explored areas of learning and optimizations using various techniques, robotics, etc. She is comfortable with the design of control methods for various applications and requirements.

Currently Chandreyee uses Python for most of her work, but is well-versed in MATLAB from past experience.