Mr Anandarup Roy| Internet of Things | Best Researcher Award

Mr Anandarup Roy,Senior Research Fellow, Indian Statistical Institute, Kolkata,India

Anandarup Roy is a Ph.D. candidate in Computer Science at the Indian Statistical Institute (ISI), Kolkata, specializing in combinatorial secret sharing. His thesis was submitted on July 19, 2024, and he expects to receive his degree by December 2024. He is advised by Prof. Bimal Kumar Roy and co-supervised by Prof. Mridul Nandi, both from the Applied Statistics Unit at ISI.

Professional Profile:

Summary of Suitability for the Best Researcher Award:

Anandarup Roy, a Ph.D. candidate at the Indian Statistical Institute, has made significant contributions to the field of computer science, particularly in combinatorial secret sharing. His research extends previous work in Bayesian incentive-compatible mechanism design and social learning, demonstrating a robust understanding of complex statistical models and their applications.

Education

He Naifeng is pursuing a PhD at the prestigious Nanjing University of Aeronautics and Astronautics, where he has built a strong foundation in automation and robotics. His academic journey reflects a commitment to advancing technology in mobile robotics, demonstrating a keen interest in both theoretical knowledge and practical applications.

Work Experience

From 2016 to 2018, Anandarup worked as a project-linked person at the Economics Research Unit of ISI, where he contributed to a project on Bayesian incentive-compatible mechanism design under the supervision of Prof. Manipushpak Mitra. This research extended his master’s thesis by examining learning processes in a social choice environment with risk-neutral agents.

Skills

Anandarup is proficient in using Linux OS (Ubuntu) and LaTeX. He possesses basic programming knowledge in C, making him well-equipped for computational tasks related to his research.

Research Focus

His research focuses on autonomous navigation for wheel-legged robots, with particular emphasis on reinforcement learning in control systems and intelligent motion control. He aims to develop practical applications that enhance the performance and adaptability of mobile robots in challenging environments.

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