• Lecturer, College of Computer Science and Engineering, Shandong University of Science and Technology
  Main Courses: Artificial Intelligence, Advanced Algebra (Linear Algebra)

Bao Han, PhD, Master's Supervisor, graduated from the School of Computer Science and Engineering, Beihang University in June 2022, studied under Academician Huai Jinpeng and Professor Zhang Richong, and received a PhD in Computer Software and Theory. He was awarded the title of Honorary Doctor of Shen Yuan Honors College of Beihang University. In July of the same year, he joined the College of Computer Science and Engineering, Shandong University of Science and Technology. His research interests include Hopfield neural networks, deep neural networks, and interpretability research. He has presided over or participated in the National 973 Project, the National 973 Youth Project, the National Natural Science Foundation Project, the Shandong Provincial Natural Science Foundation Youth Project, and the Shandong University of Science and Technology Elite Program Project. He has published 4 papers in well-known domestic and foreign journals and conferences such as Information Sciences and Neurocomputing. He serves as a reviewer for the journals "Information Sciences" and "Neurocomputing".

I am a young researcher who is committed to the research of interpretability of deep neural networks. I focus on the theoretical exploration of deep learning algorithms in the field of artificial intelligence. At the same time, I am passionate about the practical application of deep neural networks and have long been concerned about the development of general artificial intelligence (AGI). My research focuses on the theoretical research of Hopfield neural networks, and I try to unveil the operating mechanism of deep neural networks through this model, laying the foundation for the research of interpretability of deep neural networks.
At the application level, I am currently very interested in the blind path recognition algorithms and software that improve the travel experience of blind people, and pay attention to the technological improvement of the modern life of vulnerable groups. I am committed to using cutting-edge algorithms to solve practical problems, so as to promote the implementation and development of artificial intelligence in the field of social welfare, do some practical and interesting things, and truly realize the goal of technology empowering society.

As a mentor, I firmly believe that the following points are crucial to the growth of students:

1. Autonomous learning and practical ability: help students develop autonomous learning ability, independent analysis and problem-solving ability.
2. Innovation and critical thinking: encourage students to propose new ideas and question existing theories, and explore unknown areas of knowledge.
3. Comprehensive development: Focus on the cultivation of academic ability and personal comprehensive quality, laying the foundation for the long-term development of students.

We recruit master's degree students all year round, and we look forward to the following characteristics of students: self-motivated and good at thinking! Whether you are familiar with my research field or have your own research interests and ideas, I will work with you to explore the academic world that interests you. In my team, you will have the opportunity to participate in frontier research projects, learn and practice the latest artificial intelligence technologies. At the same time, I support students to actively participate in domestic and international academic conferences, publish high quality papers, and promote the sustainable development of the academic community. Those with excellent paper results can be recommended to top universities in China such as Chinese Academy of Sciences, Tsinghua University, Beihang University, Zhejiang University, Xi'an Jiaotong University, Huazhong University of Science and Technology, Tianjin University, or to well-known universities abroad such as Canada, the United States, Finland, Norway, Australia, etc. for further study. Looking forward to your joining! If interested, please contact me.

1. 2017.02-2017.08 Visiting scholar at the School of Electronic Engineering and Computer Science (EECS) at the University of Ottawa, Canada.
2. 2013.06-2013.08 Summer research at the School of Mathematics, Michigan State University (MSU), USA.

1. 2025.01-2027.12 (Host) Youth Fund of Natural Science Foundation of Shandong Province (ZR2024QF269), Model structure research and memory capacity analysis of associative memory networks.
2. 2022.12-2027.12 (Host) Elite Foundation of Shandong University of Science and Technology, Research Start-up Fund.
3. 2017.01-2021.12 (Participant) National Natural Science Foundation of China General Project (61772059), Research on knowledge graph construction, reasoning and question answering based on multi-source heterogeneous data.
4. 2015.01-2019.12 (Participant) National Youth 973 Program (2015CB358700), Basic theory and key technology of big data group computing.
5. 2014.09-2018.12 (Participant) National Key Basic Research and Development Program (973 Program) (2014CB340300), Theory of big data computing in network information space.
6. 2014.01-2016.12 (Participant) National Natural Science Foundation Youth Fund (61300070), Research on recommendation system for social network user needs.

1. Bao H, Zhao Z. Binary Associative Memory Networks: A Review of Mathematical Framework and Capacity Analysis[J], Information Sciences, Information Sciences, 2025, 694: 121697.
2. Bao H, Zhang R, Mao Y. The capacity of the dense associative memory networks[J]. Neurocomputing, 2022, 469: 198-208.
3. Bao H, Zhang R, Mao Y, et al. Writing to the hopfield memory via training a recurrent network[C] Pacific Rim International Conference on Artificial Intelligence. Cham: Springer International Publishing, 2019: 241-254.
4. Zhang R, Bao H, Sun H, et al. Recommender systems based on ranking performance optimization[J]. Frontiers of Computer Science, 2016, 10: 270-280.