Skip to main content

Kaizhu Huang

Professor of Electrical and Computer Engineering at Duke Kunshan University
DKU Faculty

Overview


Kaizhu Huang works on machine learning, neural information processing, and pattern recognition. Before joining DKU, he was a full professor at Xi’an Jiaotong-Liverpool University (XJTLU) and Associate Dean of research in School of Advanced Technology, XJTLU.  Prof. Huang obtained his PhD degree from Chinese University of Hong Kong (CUHK), Master degree from Institute of Automation, Chinese Academy of Sciences, and Bachelor degree from Xi'an Jiaotong University. He worked at Fujitsu Research Centre, CUHK, University of Bristol, Chinese Academy of Sciences from 2004 to 2012. He was the recipient of the 2011 Asia Pacific Neural Network Society Young Researcher Award. He received the best paper or book awards for seven times. He has published 9 books and over 230 international research papers including 120+ journal papers (e.g. IEEE T-PAMI, IEEE T-NNLS, IEEE T-BME, IEEE T-Cybernetics, JMLR) and 110+ conference papers (e.g. NeurIPS, IJCAI, SIGIR, UAI, CIKM, ICDM, ICML, ECML, CVPR). He serves as associated editors/advisory board members in a number of international journals and book series. He was invited as a keynote speaker in more than 30 international conferences or workshops.

Current Appointments & Affiliations


Professor of Electrical and Computer Engineering at Duke Kunshan University · 2022 - Present DKU Faculty
Director of Data Science Research Center (DSRC) at Duke Kunshan University · 2023 - Present DKU Faculty

Recent Publications


Stagger Network: Rethinking information loss in medical image segmentation with various-sized targets.

Journal Article Neural networks : the official journal of the International Neural Network Society · March 2025 Medical image segmentation presents the challenge of segmenting various-size targets, demanding the model to effectively capture both local and global information. Despite recent efforts using CNNs and ViTs to predict annotations of different scales, these ... Full text Cite

Revisiting 3D point cloud analysis with Markov process

Journal Article Pattern Recognition · February 1, 2025 3D point cloud analysis has recently garnered significant attention due to its capacity to provide more comprehensive information compared to 2D images. To confront the inherent irregular and unstructured properties of point clouds, recent research efforts ... Full text Cite

Open-Pose 3D zero-shot learning: Benchmark and challenges.

Journal Article Neural networks : the official journal of the International Neural Network Society · January 2025 With the explosive 3D data growth, the urgency of utilizing zero-shot learning to facilitate data labeling becomes evident. Recently, methods transferring language or language-image pre-training models like Contrastive Language-Image Pre-training (CLIP) to ... Full text Cite
View All Publications

Education, Training & Certifications


Chinese University of Hong Kong (Hong Kong) · 2004 Ph.D.

External Links


Personal Website