Abhijit Majumdar
Papers
8
Total Citations
228
H-Index
4
About
Abhijit Majumdar is a robotics and artificial intelligence researcher whose work spans human-robot interaction, autonomous systems, and machine learning. His most influential contribution, "Toward Artificial Emotional Intelligence for Cooperative Social Human–Machine Interaction" (2019, 118 citations), investigates how robots can recognize and respond to human emotional states — a critical frontier in assistive robotics and social AI. This work reflects his broader commitment to making machines more intuitive and socially aware collaborators. Majumdar has also made notable strides in unmanned aerial vehicle (UAV) research, developing bio-inspired formation control algorithms using stereo cameras and contributing an open-source quadcopter flight controller compatible with the Robot Operating System (ROS). His object tracking work using deep neural networks (43 citations) demonstrates expertise in computer vision applied to home robotics. Across his portfolio, Majumdar bridges theoretical AI with practical implementation — from reinforcement learning simulations transferred to physical robots, to indoor localization using commercial VR hardware. His research consistently prioritizes reproducibility, real-world applicability, and multi-system coordination. With over 225 cumulative citations, his work serves as a valuable resource for students and engineers working at the intersection of autonomous systems, perception, and human-centered AI.
Research Focus
Key Achievements
Top Papers
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- 4HTC Vive Tracker: Accuracy for Indoor Localization24 citations · 2020
- 5
- 6Lightweight Multi Car Dynamic Simulator for Reinforcement Learning4 citations · 2018
- 7Stereo Camera Based Formation Control for Unmanned Aerial Vehicles3 citations · 2018
- 8