Jie Fu

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Assistant Professor,
Electrical & Computer Engineering Department,
Robotics Engineering Program,
Worcester Polytechnic Institute (WPI)

85 Prescott 222, Worcester, MA 01604
Tel: (508) 831-4963
jfu2@wpi.edu
http://www.wpi.edu/~jfu2

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Dr. Jie Fu is an Assistant Professor with the Department of Electrical and Computer Engineering, with an affiliation in Robotics Engineering Program, at Worcester Polytechnic Institute, Worcester, MA, USA since 2016. She received the M.Sc. degree in Electrical Engineering and Automaton from Beijing Institute of Technology, Beijing, China, in 2009, and the Ph.D. degree in Mechanical Engineering from the University of Delaware, Newark, DE, USA, in 2013. From 2013 to 2015, she was a Postdoctoral Scholar with the University of Pennsylvania. Her research interests include: Control theory, Formal methods, Machine Learning, with applications to Robotic systems and Cyber-Physical Systems.

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Research lab:

To find out more information about our ongoing projects and research activities, please see our labwebpage:

Control and Intelligent Robotics Laboratory (CIRL)

News

  • Jul. 2019. Congratulations to Abhishek and Lening for our papers being accepted at CDC2019.

  • Jan. 2019. Congratulations to Xuan and Lening for our papers being accepted at ACC2019.

  • Jan. 2019. Congratulations to Renato and Xuan for our paper being accepted at ICRA2019.

  • Dec. 2018. In collaboration with Scientific Systems , we won $1 million DARPA grant from SI3CMD program.

  • Aug. 2018. Our research lab website is live: Control and Intelligent Robotics Laboratory (CIRL).

  • Jul. 2018. Two papers were accepted by IEEE CDC 2018.

  • Jan. 2018. Two papers were accepted by IEEE ACC 2018.

  • Sep. 2017. Siddharthan Perundurai Rajasekaran successfully defended his MS thesis titled “Nonparametric Inverse Reinforcement Learning and Approximate Optimal Control with Temporal Logic Tasks”. Congratulations, Siddharthan!

  • Aug. 2017. Received NSF Grant as Co-PI with Prof. Cagdas Onal (PI) on project “Intelligent Soft Robot Mobility in the Real World”.

  • Jul. 2017. Paper titled “Data-Driven Inverse Learning of Passenger Preferences in Urban Public Transits” was accepted by IEEE CDC 2017.

  • Jan. 2017. Paper titled “Adapting to Flexibility: Model Reference Adaptive Control of Soft Bending Actuators” was accepted by IEEE Robotics and Automation Letters. This is a collaborative research with Prof. Cagdas Onal from The Soft Robotics Lab.

  • Jan. 2017. Paper titled “Sampling-based approximate optimal control under temporal logic constraints” was accepted by ACM International Conference on Hybrid Systems: Computation and Control (HSCC 2017).