Yiwen WANG (王怡雯)
PhD, University of Florida
Master, University of Science and Technology of China
Bachelor, University of Science and Technology of China
Assistant Professor
Dept of Electronic & Computer Engineering, HKUST

Research Areas
Biomedical Engineering (BME)

Tel : +852 2358 7053
Email : eewangyw
Room : 2437


Research Interests
Brain Machine Interfaces, Adaptive Signal Processing, Computational Neuroscience, Neuromorphic Engineering,

Yiwen Wang received the B.S. and M.S. degrees in electrical engineering from University of Science and Technology of China (USTC), Hefei, Anhui, China in 2001 and 2004 respectively. Under the guidance of Dr. Jose C. Principe (IEEE Fellow), she received the Ph.D. degree from University of Florida, Gainesville, FL, USA in 2008. She worked as a Fellow Intern in Siemens Corporation Research, Princeton, NJ, USA in 2007. In 2008, she joined the Department of Electronics and Computer Engineering as a Research Associate at the Hong Kong University of Science and Technology, Kowloon, Hong Kong, and corporated with Dr. Bertram Shi (IEEE Fellow).  From 2010 to 2016, she worked as an Associate Professor at Zhejiang University, Hangzhou, China. In 2017, she joined the faculty of Department of Electronics and Compter Engineering and Division of Biomedical Engineering at the Hong Kong University of Science and Technology, Kowloon, Hong Kong. Her research interests are in neural decoding of brain-machine interfaces, adaptive signal processing, computational neuroscience, neuromorphic engineering. She serves in the IEEE EMBS Neural Engineering Tech Committee, and is an Associate Editor of the IEEE Transactions of Neural Systems and Rehabilitation Engineering. She holds one US patent and has authored more than 70 peer-reviewed publications.

Postdoc Fellowship/RA are available now!!

One Post-doctoral Fellow/Research Assistant position are available in Prof. Yiwen Wang’s Lab jointly run by the Department of Electronic Engineering the Division of Biomedical Engineering. 

The appointees will study neuroplasticity in developing and applying computational approaches to discover and understand the underlying principle of how brain learns to generate accurate autonomous control on neuro-prosthesis via adaptation to the environmental demands,  and to pursue the translational application for clinical use.  The appointees will have collaboration opportunities with the University of Florida, USA and Ulsan National Institute of Science and Technology Ulsan, South Korea. 

Applicants for the Post-doctoral Fellow position should have a PhD degree in neuroscience, electrical engineering, mathematics, physics, computer science or a related discipline with solid knowledge of computational neuroscience, and background of signal processing, machine learning. 
Relevant working experience in a laboratory setting with animals, including electro physiology recording, animal behavior training and brain surgery, will be an asset. 

Applicants for the Research Assistant position should have a bachelor’s or higher degree in biology or medicine with experience in programming.  Candidates with practical experience in electro physiology recording, animal behavior training and brain surgery are preferred.  The successful candidate should be capable of working independently and have strong analytical skills. 

Starting salary will be commensurate with qualifications and experience.  Fringe benefits including annual leave, medical and dental benefits will be provided. 

Please check
HKUST Careers - Current Job Openings with Job ID 3262, or email me together with a curriculum vitae and a statement of interests. 


Selected Journal Papers
  •          F. Wang, Yiwen Wang*, K. Xu, Q. Zhang, S. Zhang, X. Zheng, J. Principe, Quantized Kernel Reinforcement Learning for Brain-Machine Interfaces, IEEE Trans. on Neural Networks and Learning, In press
  •          Y. Wang, Y. Qi, Yu; Yiwen Wang*, Z. Lei; X. Zhang, G. Pan, Delving an alpha-stable Distribution in Noise Suppression for Seizure Detection from Scalp EEG, Journal of neural engineering, 13(5):056009
  •          Yiwen Wang*, X. She, Y. Liao, H. Li, Q. Zhang, S. Zhang, X. Zheng, J. Principe, Tracking Neural Tuning Plasticity by Dual Sequential Monte Carlo Estimation on Point Processes for Brain Machine Interfaces, IEEE Trans. on Biomedical Engineering, (Cover article) , 63(8): 1728-1741, 2016
  •          Y. Liao, X. She, Yiwen Wang*, S. Zhang, Q. Zhang, X. Zheng and J. Principe, Monte Carlo point process estimation of electromyographic envelopes from motor cortical spikes for brain-machine interfaces, Journal of Neural Engineering, 12(6):066014, 2015
  •          Yiwen Wang*, L. Jiang, Y. Wang, B. Cai, Y. Wang, W. Chen and X. Zheng, An Iterative Approach for EEG based Rapid Face Search: A refined retrieval by Brain-Computer Interface, IEEE Trans. on Autonomous and Mental Development, 7(3):211, 2015
  •          Yiwen Wang*, F. Wang, K. Xu, Q. Zhang, S. Zhang, X. Zheng, Neural Control of a Tracking Task via Attention-gated Reinforcement Learning for Brain-Machine Interfaces, IEEE Transactions on Neural Systems & Rehabilitation Engineering, (Cover article), 23(3): 458, 2015
  •          Y. Wang. Qi, Y, J. Zhu, J. Zhang, Yiwen Wang, X. Zheng, Z. Wu, A Cauchy-based State-space model for Seizure Detection in a EEG Monitoring System, IEEE Intelligent System, 30(1): 6, 2015
  •          Y. Hao, Q. Zhang, M. Controzzi, C. Cipriani, Y. Li, J. Li, S. Zhang, Yiwen Wang, W. Chen, M. Carrozza, X. Zheng, Distinct neural patterns enable grasp types decoding in monkey dorsal premotor cortex, Journal of Neural Engineering, 2014, 11(6): 066011.
  •          K. Xu, Yiwen Wang*, F. Wang, Y. Liao, Q. Zhang, H. Li and X. Zheng, Neural Decoding using a Parallel Sequential Monte Carlo method on Point Processes with Ensemble Effect, BioMed Research International (formerly titled Journal of Biomedicine and Biotechnology), 685492, 2014 
  •      D. Wang, Q. Zhang, Y. Li, Yiwen Wang; J. Zhu, S. Zhang, X. Zheng, Long-term decoding stability of local field potentials from silicon arrays in primate motor cortex during a 2-D center out task, Journal of Neural Engineering, 11(3):036009, 2014
  •      K. Xu, Yiwen Wang*, Y. Wang, F. Wang, Q. Zhang, S. Zhang, W. Chen, X. Zheng, Local-learning-based neuron selection for grasping gesture prediction in motor Brain Machine Interfaces, Journal of Neural Engineering, 10(2): 026008, 2013
  •      Yiwen Wang*, B. Shi, Improved Binocular Vergence Control via a Neural Network Trained to Maximize an Internally Derived Reward, IEEE trans. on Autonomous Mental Development, 3(3): 247-256, 2011
  •      Yiwen Wang*, J. Sanchez, J. Principe, Instantaneous Estimation of Motor Cortical Neural Encoding for online Brain-Machine Interfaces, Journal of Neural Engineering, 7(5):056001-056013, 2010
  •      Yiwen Wang*, B. Shi, Autonomous Development of Vergence Control Driven by Disparity Energy Neuron Populations, Neural Computation, 22(3):730-751, 2010.
  •      Yiwen Wang*, A. Paiva, J. Principe, J. Sanchez, Sequential Monte Carlo Point Process Estimation of Kinematics from Neural Spiking Activity for Brain Machine Interfaces, Neural Computation, 2009, 21(10): 2894-2930. doi:10.1162/neco.2009.01-08-699 
  •      Yiwen Wang*, J. Principe, J. Sanchez, Ascertaining neuron importance for kinematics decoding by information theoretical analysis in motor brain machine interfaces, Neural Networks, 2009, vol. 22(5-6):781-790. doi:10.1016/j.neunet.2009.06.007 
  •      W. Liu, Il Park, Yiwen Wang, J. Principe, Extended Kernel Recursive Least Squares Algorithm, IEEE transactions on Signal Processing, vol. 57, no. 10: 3801-3814, 2009. Digital Object Identifier :10.1109/TSP.2009.