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Dr. Andrew Ho Chun WU

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Dr. Andrew Ho Chun WU
Dr. Andrew Ho Chun WU
Lecturer
BEng (Hons) UNSW; MSc(Eng) (EEE) HKU; PhD (EEE) HKU; MIEEE; MIET
  3917 2704
  CB-613
Research Interests:
Smart Grid; Big Data Analytics; Deep Learning; Bioinformatics; Biomedical Informatics; Artificial Intelligence of Things.

Biography

Dr. Andrew H.C Wu received his B. Eng. in Electrical Engineering from the University of New South Wales, Australia, in 2008, M. Sc. in Engineering (Electrical and Electronic Engineering) in 2009 and Ph. D. in 2013 from the University of Hong Kong. Before joining the University of Hong Kong, Dr. Wu worked as a Part-time Lecturer at the HKU School of Professional and Continuing Education from 2017 to 2021 and as a Visiting Lecturer at the Hong Kong Community College, Hong Kong Polytechnic University from 2019 to 2021. From 2021 to 2024, Dr. Wu served as a Lecturer in the School of Science and Technology at Hong Kong Metropolitan University. During this period, he was the winner of the President’s Awards for Excellence in Inspirational Teaching (Early Career Teaching, University-wide) in 2022, recognizing him among all teaching staff at Hong Kong Metropolitan University. In 2024, Dr. Wu was appointed as Lecturer in the Department of Electrical and Computer Engineering at the University of Hong Kong.

Related Links

Selected Publications

  • Chan, S. C., & Wu, H. C. (2020). U.S. Patent No. 10,742,954. Washington, DC: U.S. Patent and Trademark Office.
  • Yang, Z., Qi, W., Chan, S. C., & Wu, H. C. (2024). MIB-Net: Balance the mutual information flow in deep learning network for multi-dimensional segmentation of COVID-19 CT images. Biomedical Signal Processing and Control, 95, 106376.
  • Qi, W., Wu, H. C., & Chan, S. C. (2023). MDF-net: A multi-scale dynamic fusion network for breast tumor segmentation of ultrasound images. IEEE Transactions on Image Processing. 32, 4842-4855.
  • Lin, J. Q., Wu, H. C., & Chan, S. C. (2021). A new regularized recursive dynamic factor analysis with variable forgetting factor and subspace dimension for wireless sensor networks with missing data. IEEE Transactions on Instrumentation and Measurement, 70, 1-13.
  • Ho, C. H., Wu, H. C., Chan, S. C., & Hou, Y. (2019). A robust statistical approach to distributed power system state estimation with bad data. IEEE Transactions on Smart Grid, 11(1), 517-527.