Forrest Li

Associate Professor of Computer Science and Technology

BS, Civil Engineering, Minor, Computer Science and Technology, Hefei University of Technology (China); MS, Computer Science and Engineering, Hefei University of Technology; PhD, Pattern Recognition and Artificial Intelligence, University of Science and Technology of China

Homepage: https://sites.google.com/view/yangmingli/home

Phone: (603) 535-2534

Office: Memorial Hall

About Forrest Li

Forrest Li is joining Plymouth State University as a tenure-track associate professor in fall 2018. He was previously an acting instructor at the Department of Electrical Engineering, University of Washington, and before that an associate professor at the Institute of Intelligent Machines, Chinese Academy of Sciences, where he was a faculty member of the Robot and Human Machine Interaction Lab and received the Young Researcher Award (2011) from National Science Foundation of China. He received a PhD from a joint program of the University of Science and Technology of China and the University of Michigan in 2010. His research interests include simultaneous localization and mapping and improving surgical outcomes with robotic surgeries, for which he has been granted several patents.

Selected Publications/Presentations/Exhibitions

  • Li and B. Hannaford. “Gaussian Process Regression for Sensorless Grip Force Estimation of Cable-Driven Elongated Surgical Instruments”. In: IEEE Robotics and Automation Letters 2.3 (2017), pp. 1312~1319
  • Li, R. Bly, R Harbison, I. Humphreys, M. Whipple, B. Hannaford, and K. Moe. “Anatomical Region Segmentation for Objective Surgical Skill Assessment with Operating Room Motion Data”. In: Journal of Neurological Surgery Part B: Skull Base 369.15 (2017), pp. 1434~1442
  • Li, J. He, Y. Li, and M. Raque. “Distributed recurrent neural networks for cooperative control of manipulators: A game-theoretic perspective”. In: IEEE transactions on neural networks and learning systems 28.2 (2017), pp. 415~426.
  • Li and B. Hannaford. “A Novel Recurrent Neural Network Control Scheme for Improving Redundant Manipulator Motion Planning Completeness”. In: Robotics and Automation (ICRA), 2018 IEEE International Conference on. IEEE. 2018

Courses

  • CS 2521 Introduction to Electromechanical Technology
  • CS 4250 Computer Architecture