2026 International Conference on Human-Computer Interaction, Neural Networks and Deep Learning (HNNDL 2026)

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Prof. Daojing He

Harbin Institute of Technology, Shenzhen

He Daojing, a tenured professor and doctoral supervisor, serves as the Associate Dean of the School of Computer Science at Harbin Institute of Technology (Shenzhen) and the Executive Vice President of the Institute of Computing and Intelligence at HIT (Shenzhen). He is also the Director of the Guangdong Provincial Engineering Technology Research Center for Cryptographic Applications and Innovation. As the project leader of a key national research and development program under the Ministry of Science and Technology, he has long been engaged in innovative research in artificial intelligence, large-scale models, cyberspace security, robotics, and new quality productivity, achieving multiple breakthroughs. He has led the completion of 49 national and provincial-level key projects.

With 83 first-author papers published in authoritative IEEE journals and 185 patented inventions, 36 of which have been successfully commercialized, he has been consistently recognized as a Highly Cited Chinese Researcher and ranked among the top 2% of scientists worldwide over the past five years. His achievements have been successfully applied to several national key missions, filling multiple technological gaps.

The multi-category information tools developed under his leadership have supported special operations in various critical national departments. His research outcomes have been industrialized and adopted by renowned enterprises and institutions, serving billions of users globally and delivering significant economic and social benefits.

Prof. Lei Zhang

Chongqing University

Zhang Lei, a Professor and Doctoral Supervisor at the School of Microelectronics and Communication Engineering, Chongqing University, serves as the Director of the Chongqing Key Laboratory of "Biological Perception and Multimodal Intelligent Information Processing" and leads the "Visual Intelligence and Learning" research team at Chongqing University. He has been recognized as a high-level young national talent, selected for the third cohort of the Hong Kong Scholars Program by the Ministry of Human Resources and Social Security, and is a recipient of the Chongqing Distinguished Young Scientists Fund and the Chongqing High-Level Talent Special Support Program. Additionally, he has been listed in both the "Career-Long Scientific Impact" and "Annual Scientific Impact" rankings of the World's Top 2% Scientists released by Stanford University.

His primary research focuses on multimodal artificial intelligence, computer vision, robust machine learning, efficient transfer of large models, and vision-language large models. He has undertaken over 20 national and provincial-level projects, including those from the Organization Department's High-Level Talent Program, the Ministry of Science and Technology's National Key R&D Program, the National Natural Science Foundation of China, the Ministry of Human Resources and Social Security's Talent Program, the Chongqing Distinguished Young Scientists Fund, and collaborations with leading national enterprises.

He has published more than 160 academic papers in prestigious IEEE journals and top-tier conferences such as TPAMI, IJCV, CVPR, ICCV, ECCV, ICML, and AAAI, including 10 ESI Top 1% Highly Cited Papers. He has authored one academic monograph, with Google Scholar citations exceeding 10,000, and holds nearly 20 invention patents.

His awards include the Wu Wenjun Artificial Intelligence Natural Science Award, the Wu Wenjun Artificial Intelligence Outstanding Youth Award, the Chongqing Natural Science Award, the Chongqing Top Ten Youth in Science and Technology Award, the Huawei Spark Award, the Huawei Outstanding Project Achievement Award, the ACM SIGAI Rising Star Award, and the CCBR Best Paper Award.

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Prof. Hongbin Ma

Beijing Institute of Technology

Professor Ma's research revolves around the theme of "Adaptation · Learning · Cognition." Grounded in **mathematical algorithms and computer technology**, it involves persistent, long-term efforts in the interdisciplinary integration of **control, mathematics, software, and hardware**.

Theoretical research is primarily dedicated to control theory and complex systems, particularly the **stability and stabilization of discrete-time dynamical systems**, along with the corresponding **algorithm design and analysis**. A key focus is on developing novel theories and algorithms in the field of **adaptive estimation and control**.

Applied research concentrates primarily on **navigation, guidance, and control**, including the related issues of learning and cognition. This encompasses **integrated navigation and intelligent navigation**, human-machine intelligent interaction, visual and auditory cognition, **multi-agent and wireless sensor network applications**, as well as **embedded systems and software development**.

During his doctoral studies, his research involved **stochastic control systems, signal processing, adaptive estimation and control, and nonlinear or hybrid systems**. The central focus was on addressing challenges related to **complexity, nonlinearity, and uncertainty** within systems.