Chun Pong Lau is currently an Assistant Professor at the School of Data Science, City University of Hong Kong. He received his Ph.D. in Computer Science in 2021 from Johns Hopkins University. He received his M.Sc. in Applied Mathematics in 2020 from University of Maryland, M.Phil. and B.Sc. in Mathematics from The Chinese University of Hong Kong in 2016 and 2018, respectively. From 2022 to 2023, he was a postdoctoral fellow at Mathematical Institute for Data Science, Johns Hopkins University. With a strong background in mathematics and computer science, Prof. Lau has strong research interests in developing reliable and robust computer vision algorithms, including Atmospheric Turbulence Mitigation, Adversarial Robustness, Biometrics at Severe Conditions, and Generative AI.
Prof. Lau has published numerous peer-reviewed articles in prestigious journals/conferences, such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, IEEE Transactions on Information Forensics and Security, IEEE Transactions on Biometrics, Behavior, and Identity Science, IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR), and The Conference on Neural Information Processing Systems (NeurIPS) etc. Prof. Lau was the recipient of a few awards from IEEE, including best paper awards from IEEE conference on Automatic Face and Gesture Recognition.
Prof. Lau has served as a reviewer for various top journals/conference, including IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, IEEE Transactions on Information Forensics and Security, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Multimedia, IEEE Transactions on Computational Imaging and CVPR, ICCV, ECCV, WACV, BMVC, AAAI, NeurIPS, ICML, ICLR.
- Computer Vision
- Image Processing
- Adversarial Robustness
- Unconstrained Biometrics
- Generative AI
- Deep Learning
- Jan 2022 - Jul 2023, Postdoctoral Fellow, Mathematical Institute for Data Science, Johns Hopkins University.