Nilanjan Chakraborty, PhD

Associate Professor

Office: Heavy Engineering 212

Email Address: nilanjan.chakraborty@stonybrook.edu

Phone Number: (631) 632-9327

Websites: Interacting Robotic Systems Laboratory

Bio:

Nilanjan Chakraborty joined the Mechanical Engineering Faculty at Stony Brook University in the Fall of 2014. His research interests are in robotics, artificial intelligence, dynamical systems, and applied optimization. He is interested in developing capabilities for robots that will allow them to work robustly and reliably with or without human teammates and enable long-term autonomy in robotic systems. He specializes in developing contact dynamics based algorithms for manipulation planning, robot motion planning, and distributed planning for multi-robot systems. He is a member of the IEEE Robotics and Automation Society and ACM. He has served as a reviewer for leading robotics journals and conferences and also served as an Associate Editor for IEEE International Conference on Robotics and Automation. He was a recipient of the Best Paper Award (Computer Systems Technical Group) at the Annual Meeting of the Human Factors and Ergonomics Society in 2013 and the Best Student Paper Award at Robotics: Science and Systems Conference in 2007.

Education:

PhD, Rensselaer Polytechnic Institute
MSc, Indian Institute of Science
BE, Jalpaiguri Government Engineering College

Professional Experience:

Department of Mechanical Engineering, Stony Brook University, 2014 - Present

Awards & Publications:

Best Paper Award (Computer Systems Technical Group) at the Annual Meeting of the Human Factors and Ergonomics Society in 2013
Best Student Paper Award at Robotics: Science and Systems Conference in 2007

Professional Memberships & Service:

Associate Editor for IEEE International Conference on Robotics and Automation
Member of IEEE Robotics,
Member of Automation Society
Member of Association for Computing Machinery (ACM)

Overview:

Nilanjan Chakraborty’s research interests are in robotics, artificial intelligence, dynamical systems, and applied optimization. He is interested in developing capabilities for robots that will allow them to work robustly and reliably with or without human teammates and to enable long-term autonomy in robotic systems. He specializes in developing contact dynamics-based algorithms for manipulation planning, algorithms for robot motion planning, and algorithms for distributed planning in multi-robot systems.

Highlights & Accomplishments:

Developed a Novel Approach to Programming by Demonstration (PbD) That Allows Active Incremental Acquisition of Demonstrations With Performance Assurance.
Developed the First and Only Unified Framework for Combining Grasp Planning and Constrained Manipulation Planning.
Developed a Novel Method for Multirobot Task Allocation Under Uncertainty with Performance Guarantees.

Research Interests:

Use of robots as assistants in small-batch manufacturing, patient care, nursing, and lab automation
ISR, Search and Rescue, Environmental Monitoring applications