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About

Shohin Mukherjee is a robotics researcher whose work spans humanoid robot control, autonomous aerial systems, surgical robotics, and motion planning algorithms. His early research demonstrated innovative approaches to human-robot imitation, implementing inverse kinematics techniques — including fuzzy logic and iterative Jacobian methods — to enable NAO robots to replicate human motion via Kinect tracking, a paper that has accumulated 41 citations and remains a foundational reference in the field. His work then extended into precision medical robotics, contributing to monocular camera-guided retinal vein cannulation and graph-based retinal vasculature mapping during intraocular microsurgery, areas where robotic precision can directly impact patient outcomes. Mukherjee has also made significant contributions to algorithmic planning, developing parallelized search frameworks such as ePA\*SE and MPLP that leverage modern multi-threading architectures for faster, more efficient robot motion planning. His multi-UAV coverage planning work addresses persistent aerial autonomy with robust deconfliction strategies. Rounding out his portfolio, his research into sim-to-real transfer for zero-shot task execution pushes the boundaries of generalizable robot intelligence. With over 100 cumulative citations, Mukherjee's interdisciplinary contributions reflect a researcher uniquely bridging theoretical planning advances with real-world robotic applications.