主讲课程：

人工智能

高等代数（线性代数）秋季课程 计算机图灵班 欢迎旁听学习

线性代数学习建议：推荐使用《线性代数及其应用》刘深泉等译的Linear Algebra and Its Applications，该书对于线性代数的知识点讲解很详细，逻辑性较强，配套习题有详解，很适合作教材学习；英语好的同学可使用MIT教授Gilbert Strang祖师爷写的Introduction to Linear Algebra，这本教材比前一本更好，逻辑性启发性非常强，是一本能让你觉得线性代数原来如此之美的经典书籍，而且B站有Gilbert Strang教授在MIT的教学视频；国内老师出版的教材只推荐李尚志老师的《线性代数》，教你用1.5招亢龙有悔打遍天下无敌手，打不过就跑到打得过的地方再打！

研究兴趣：

我是致力于深度神经网络可解释性研究的青椒一枚，专注于人工智能领域中深度学习算法的理论探索，同时对深度神经网络的实际应用充满热情，长期关注通用人工智能AGI的发展。我的研究重点是Hopfield神经网络的理论研究，力图通过这一模型揭开深度神经网络运行机理的面纱，为深度神经网络的可解释性研究奠定基础。

在应用层面，目前我对改善盲人出行体验的盲道识别算法与软件有浓厚兴趣，关注弱势群体现代化生活的技术提升。我致力于将前沿算法用于解决实际问题，以推动人工智能在社会公益领域的落地与发展，做一些实际且有意思的实事，真正实现技术赋能社会的目标。

培养理念：

作为导师，我坚信以下几点对于学生成长至关重要：

1. 自主学习与实践能力：帮助学生培养自主学习能力，独立分析与解决问题能力。

2. 创新与批判思维：鼓励学生提出新想法并质疑现有理论，探索知识的未知领域。

3. 全面发展：注重学术能力与个人综合素质的培养，为学生的长远发展奠定基础。

常年招收硕士学术研究生，期待的学生特质：自主上进、善于思考！无论您是否熟悉我的研究领域，或有自己的研究兴趣与想法，我都将与您携手探索你感兴趣的学术世界。在我的团队中，您将有机会参与前沿研究项目，学习和实践最新的人工智能技术。同时，我支持学生积极参与国内外学术会议、发表高水平论文，并推动学术界的持续发展。论文成果优秀者可推荐至国内如中科大、清华、北航、浙大、西交大、华科大、天大等顶尖高校，或国外如加拿大、美国、芬兰、挪威、澳大利亚等知名高校继续深造。期待您的加入！有意请联系 baohan@sdust.edu.cn,  QQ：478317316.

学术信息：

海外经历：

2017.02-2017.08 加拿大渥太华大学电子工程与计算机学院（EECS） 访学

2013.06-2013.08 美国密歇根州立大学（MSU）数学学院 暑期研学

主持或参与项目：

2025.01-2027.12（主持） 山东省自然科学基金青年基金（ZR2024QF269） 联想型记忆网络的模型结构研究及记忆容量分析

2022.12-2027.12（主持） 山东科技大学 菁英计划科研启动资金

2017.01-2021.12（参与） 国家自然科学基金面上项目（61772059） 基于多源异构数据的知识图谱构建、推理与问答研究

2015.01-2019.12（参与） 国家青年973计划（2015CB358700） 大数据群体计算的基础理论与关键技术

2014.09-2018.12（参与） 国家重点基础研究发展计划（973计划）（2014CB340300） 网络信息空间大数据计算理论

2014.01-2016.12（参与） 国家自然科学基金青年基金（61300070） 面向社会网络用户需求的推荐系统研究

代表性论文：

Bao H, Zhao Z. Binary Associative Memory Networks: A Review of Mathematical Framework and Capacity Analysis[J], Information Sciences, Information Sciences, 2025, 694: 121697. (SCI 一区TOP期刊，一作唯一通讯)

Bao H, Zhang R, Mao Y. The capacity of the dense associative memory networks[J]. Neurocomputing, 2022, 469: 198-208. (SCI二区TOP期刊，一作导师通讯)

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. (EI CCF C类会议，一作导师通讯)

Zhang R, Bao H, Sun H, et al. Recommender systems based on ranking performance optimization[J]. Frontiers of Computer Science, 2016, 10: 270-280. (SCI 三区期刊，二作导师一作)

English CV:

Personal Profile:

Baohan, 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 Colledge 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".

Details:

Main courses:

Artificial Intelligence

Advanced Algebra (Linear Algebra), Fall Course, Computer Turing Class, Welcome to audit.

Linear Algebra Learning Suggestions: It is recommended to use “Linear Algebra and Its Applications”. The book explains the knowledge points of linear algebra in detail, has strong logic, and has detailed explanations for the accompanying exercises. It is very suitable as a textbook for learning; In addition, students who are good at English can use “Introduction to Linear Algebra” written by MIT professor Gilbert Strang. This textbook is better than the previous one, with strong logic and inspiration. It is a classic book that can make you feel that linear algebra is so beautiful, and there is a teaching video of Professor Gilbert Strang at MIT on bilibili.com; The textbook published by domestic teachers is only recommended to be "Linear Algebra" by Teacher Li Shangzhi, which teaches you to use 1.5 moves to defeat all opponents in the world. If you can't beat them, run to a place where you can beat them and fight again!

Research interests:

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.

Cultivation concept:

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 baohan@sdust.edu.cn, QQ: 478317316.

Academic information:

Experience:

2017.02-2017.08 Visiting scholar at the School of Electronic Engineering and Computer Science (EECS) at the University of Ottawa, Canada

2013.06-2013.08 Summer research at the School of Mathematics, Michigan State University (MSU), USA

Projects hosted or participated in:

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

2022.12-2027.12 (host) Elite Foundation of Shandong University of Science and Technology, Research Start-up Fund

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

2015.01-2019.12 (participated) National Youth 973 Program (2015CB358700), Basic theory and key technology of big data group computing

2014.09-2018.12 (participated) National Key Basic Research and Development Program (973 Program) (2014CB340300), Theory of big data computing in network information space

2014.01-2016.12 (participated) National Natural Science Foundation Youth Fund (61300070), Research on recommendation system for social network user needs

Publications:

Bao H, Zhao Z. Binary Associative Memory Networks: A Review of Mathematical Framework and Capacity Analysis[J], Information Sciences, Information Sciences, 2025, 694: 121697.

Bao H, Zhang R, Mao Y. The capacity of the dense associative memory networks[J]. Neurocomputing, 2022, 469: 198-208.

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.

Zhang R, Bao H, Sun H, et al. Recommender systems based on ranking performance optimization[J]. Frontiers of Computer Science, 2016, 10: 270-280.