Zhihai He IEEE Fellow Chair Professor, Department of Electronics, Southern University of Science and Technology

Professor He is a Chair Professor in the Department of Electronic Engineering at the Southern University of Science and Technology, IEEE Fellow (2015). Prior to returning to China full-time in June 2021, he served as a Chair Professor in the Department of Electronic Engineering at the University of Missouri, USA. His research interests Generative visual AI, inference and control optimization for multimodal large models, health guardian robots, AI agents. From 2019 to 2025, he has been consecutively listed on Stanford University's World's Top 2% Scientists Lifetime Scientific Impact Rankings. He possesses extensive experience in the industrialization of scientific research achievements in the fields of industrial AI inspection and AI-based home-based healthcare and elderly care. As the principal investigator, he has undertaken key projects funded by the National Natural Science Foundation of China and the Tianyuan Mathematical and Intelligence + Cross-disciplinary Key Special Program of the National Natural Science Foundation of China. He has been honored with awards such as the Best Paper Award from the IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT) international journal and the Wu Wenjun AI Technological Invention Award from the Chinese Association for Artificial Intelligence.

AI Lab website：https://nkdailab.github.io/

Education

Ph.D.    University of California, Santa Barbara, Electrical and Computer Engineering (Advisor: Prof. Sanjit K. Mitra)   1998-2001

M.S.    Chinese Academy of Sciences, Institute of Computational Mathematics   1994-1997

B.S.     Beijing Normal University, Beijing, P R China, Mathematics   1990-1994

Working Experiences

Professor, Southern University of Science & Technology, China 202106 - present

Professor, University of Missouri, Columbia 2013-2021

Associate Professor, University of Missouri, Columbia 2009-2013

Assistant Professor, University of Missouri, Columbia 2003-2009

Research Engineer, David Sarnoff Research Center (Sarnoff Co.), Princeton NJ. 2001-2003

Research Introduction

Research Directions: Generative Visual for AI, Inference and Control Optimization of Multimodal Large Models, Health Guardian Robots, AI Agents

The main research achievements include: establishing a unified bit rate control model for image and video compression communication systems; being the first to extend Shannon's rate-distortion (R-D) model in information theory to the power domain (P), thereby establishing the P-R-D model for energy consumption optimization in mobile video devices; being among the earliest to propose and investigate visual sensor networks; and achieving wide applications in fields such as health monitoring, battlefield intelligence, wildlife tracking, and environmental protection.

Awards & Honors

IEEE Transactions on Circuits and Systems for Video Technology Best Paper Award for Year 2002，2002

2004 SPIE VCIP Young Investigator Award，2004

Missouri Honors Engineering Junior Faculty Research Award，2008

Provost's Outstanding Junior Faculty Research and Creative Activity Award，2009

IEEE Fellow，2015

Missouri Honors Engineering Senior Faculty Research Award，2017

Shenzhen Overseas High-level Talents，2021

Second Prize of the 2024 WU WEN JUN AI SCIENCE & TECHNOLOGY AWARD for Technological Invention. (Chinese Association for Artificial Intelligence，CAAI)，2025

Papers

[1] Yi Zhang, Chun-Wun Cheng, Junyi He, Zhihai He, Carola-Bibiane Schönlieb, Yuyan Chen, Angelica I Aviles-Rivero. "Cross-Modal Few-Shot Learning with Second-Order Neural Ordinary Differential Equations."[J] AAAI Conference on Artificial Intelligence (AAAI2025). (Oral paper).

[2] Siqi Wu, Yinda Chen, Dong Liu, Zhihai He. " Conditional Latent Coding with Learnable Synthesized Reference for Deep Image Compression."[J] AAAI Conference on Artificial Intelligence (AAAI2025). (Oral paper).

[3] Yi Zhang, Ke Yu, Siqi Wu, Zhihai He. "Conceptual Codebook Learning for Vision-Language Models"[J]. European Conference on Computer Vision (ECCV 2024).

[4] Yushun Tang, Shuoshuo Chen, Zhihe Lu, Xinchao Wang, Zhihai He. "Dual-Path Adversarial Lifting for Domain Shift Correction in Online Test-time Adaptation"[J]. European Conference on Computer Vision (ECCV 2024).

[5] Yi Zhang, Ke Yu, Angelica I Aviles-Rivero, Jiyuan Jia, Yushun Tang, Zhihai He. "Training-Free Feature Reconstruction with Sparse Optimization for Vision-Language Models"[J]. Proceedings of the 32nd ACM International Conference on Multimedia, 2024. 4387-4396

[6] Yushun Tang, Shuoshuo Chen, Jiyuan Jia, Yi Zhang, Zhihai He. "Domain-Conditioned Transformer for Fully Test-time Adaptation."[J] Proceedings of the 32nd ACM International Conference on Multimedia, 2024. 6260-6269.

[7] Zhehan Kan, Shuoshuo Chen, Ce Zhang, Yushun Tang, Zhihai He, "Self-Correctable and Adaptable Inference for Generalizable Human Pose Estimation." 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5537-5546, 17-24 June 2023.

[8] Yushun Tang, Ce Zhang, Heng Xu, Shuoshuo Chen, Jie Cheng, Luziwei Leng, Qinghai Guo, Zhihai He, "Neuro-Modulated Hebbian Learning for Fully Test-Time Adaptation."  In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3728-3738. 2023.17-24 June 2023.

[9] Zhehan Kan, Shuoshuo Chen, Zeng Li, Zhihai He, "Self-Constrained Inference Optimization on Structural Groups for Human Pose Estimation." Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part V. Cham: Springer Nature Switzerland, 2022.

[10] Shichao Kan, Yigang Cen, and Zhihai He, Relative Order Analysis and Optimization for Unsupervised Learning of Discriminative Features, IEEE Proceedings of Computer Vision and Pattern Recognition (CVPR), June 2021.

[11] Hao Sun and Zhihai He, “Reciprocal learning networks for human trajectory prediction,” IEEE Proceedings of Computer Vision and Pattern Recognition (CVPR), June 2020 (Oral paper).

[12] Yang Li, Zhiqun Zhao, Yigang Cen, and Zhihai He, Snowball: Iterative Model Evolution and Confident Sample Discovery for Semi-Supervised Learning on Very Small Labeled Datasets, accepted by IEEE Transactions on Multimedia, May 2020.

[13] Jianhe Yuan and Zhihai He, “Ensemble generative cleaning for adversarial defense of deep neural networks,” IEEE Proceedings of Computer Vision and Pattern Recognition (CVPR), June 2020.

[14] Kan, Shichao, Yigang Cen, Zhihai He, Zhi Zhang, Linna Zhang, and Yanhong Wang. "Supervised deep feature embedding with handcrafted feature." IEEE Transactions on Image Processing 28, no. 12 (2019): 5809-5823.

[15] Zhi Zhang, Zhihai He, and Wenmin Cao, Animal Detection from Highly Cluttered Natural Scenes Using Spatiotemporal Object Region Proposals and Patch Verification, IEEE Transaction on Multimedia, Vol. 18, No. 10, pp. 2079-2092, July 2016. 

[16] Chenglin Li, Hongkai Xiong, Junni Zou, Zhihai He, "Joint Source and Flow Optimization for Scalable Video Multi-rate Multicast over Hybrid Wired/Wireless Coded Networks", IEEE Transactions on Circuits and Systems for Video Technology, Vol. 21, No. 5, pp. 550-564, May 2011.

[17] Zhou, Zhongna, Xi Chen, Yu-Chia Chung, Zhihai He, Tony X. Han, and James M. Keller. "Activity analysis, summarization, and visualization for indoor human activity monitoring." IEEE transactions on circuits and systems for video technology 18, no. 11 (2008): 1489-1498.

[18] He, Zhihai, and Sanjit K. Mitra. "A linear source model and a unified rate control algorithm for DCT video coding." IEEE transactions on Circuits and Systems for Video Technology 12, no. 11 (2002): 970-982.

[19] He, Zhihai, Jianfei Cai, and Chang Wen Chen. "Joint source channel rate-distortion analysis for adaptive mode selection and rate control in wireless video coding." IEEE Transactions on circuits and systems for video technology 12, no. 6 (2002): 511-523.

[20] He, Zhihai, and Sanjit K. Mitra. "A unified rate-distortion analysis framework for transform coding." IEEE Transactions on Circuits and Systems for Video Technology 11, no. 12 (2001): 1221-1236. (Best Paper)

Recruitment Announcement

He Zhihai’s research group is recruiting research assistant professors, post-doctoral fellows, and doctoral students in deep learning, machine vision, artificial intelligence and Internet of Things. At the same time, visiting scholars and exchange students from universities and research institutions at home and abroad are welcome. If you are interested in joining, please send your resume to: hezh@sustech.edu.cn. Contact Address: Unit 434, South Building, School of Engineering, Southern University of Science and Technology, 1088 Xueyuan Avenue, Nanshan District, Shenzhen, Guangdong Province, Tel: +86 13602642426

Contact Information

Artificial Intelligence Laboratory, Department of Electronic and Electrical Engineering, Southern University of Science and Technology

Room 434, South Building, School of Engineering, Southern University of Science and Technology, 1088 Xueyuan Avenue, Nanshan District, Shenzhen