Academic Profile

Academic Profile

Assoc Prof Wang Han

Associate Professor, School of Electrical & Electronic Engineering

Email: hw@ntu.edu.sg
Assoc Prof Wang Han

Biography
Prof WANG Han is currently in the School of EEE since 1992. He received his Bachelor degree in Computer Science from Northeast Heavy Machinery Institute(China), and Ph.D. degrees from the University of Leeds(UK) respectively. His research interests include Computer Vision, and Robotics. He has done significant research work his research areas and published over 120 top quality international conference and journal papers. He has been invited as an member of Editorial Advisory Board, The Open Electrical & Electronic Engineering Journal. Dr. Wang is a senior member of IEEE.

Research Interests
Prof. Wang' research interests include:

(1) Computer Vision
(2) 2D/2D image tracking
(3) Object recognition
(4) Mobile robot navigation using vision
(5) Vision application for robots
Current Projects
  • Design and Development of a Compact, Integrated Slam Module for Indoor Perception and Localization
Selected Publications
  • Mahdi Abolfazli Esfahani, Han Wang, Keyu Wu, Shenghai Yuan. (2020). OriNet: Robust 3-D Orientation Estimation With a Single Particular IMU. International Conference on Robotics and Automation 2020 (ICRA).
  • Mahdi Abolfazli Esfahani, Han Wang, Keyu Wu, Shenghai Yuan. (2019). OriNet: Robust 3D Orientation Estimation with a Single Particular IMU.IEEE Robotics and Automation Letters (RA-L).
  • K. Wu, M. Abolfazli Esfahani, S. Yuan, and H. Wang. (2019). BND*-DDQN: Learn to Steer Autonomously through Deep Reinforcement Learning. IEEE Transactions on Cognitive and Developmental Systems, .
  • K. Wu, M. Abolfazli Esfahani, S. Yuan, and H. Wang. (2019). TDPP-Net: Achieving Three-Dimensional Path Planning via a Deep Neural Network Architecture. Neurocomputing, .
  • K. Wu, M. Abolfazli Esfahani, S. Yuan, and H. Wang. (2019). OTDPP-Net: Achieving Deep Neural Network based Real-Time 3D Path Planning in Completely Unknown Cluttered Environments. International Journal of Machine Learning and Cybernetics, .

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