Prof. Dr. Haiyan Kang , Beijing Information Science and Technology University, China

Prof. Dr. Kang Haiyan is a prominent academic in the field of Information Security, currently serving as a professor in the Department of Information Security at Beijing Information Science and Technology University, China. He earned his Ph.D. in Computer Application Technology from Beijing Institute of Technology in 2005. A senior member of the China Computer Federation and an ACM member, Prof. Kang has received recognition as an outstanding talent in Beijing and serves as an executive member of the Privacy Protection Committee of the China Confidentiality Association. He is the chief of the national first-class major in Information Security and has contributed significantly to the field through over 110 academic publications and six monographs. His research focuses on network security, blockchain technology, and privacy protection, resulting in six provincial and ministerial awards and 25 invention patents. Committed to education, he has been honored with national and local teaching achievement awards and recognized as an Excellent Graduate Thesis Supervisor in Beijing. Additionally, he holds editorial board positions with several academic journals in the field.

Professional Profile:

Work Experience

Professor
Department of Information Security, Beijing Information Science and Technology University, Beijing, China

Chief
National First-Class Major (Information Security) and Electronic Information (Network and Information Security) 📚

Editorial Board Member

Journal of Information Security Research
Cyberspace Security
Journal of Cyberspace Security Science
Journal of Beijing University of Information Science and Technology

Publication Top Notes:

Hierarchical Stackelberg Game Swarm Learning Incentive Method for Wireless Edge Network

Community overlap discovery algorithm based on industrial big data

Research on the Deep Learning Method Based on Data Feature Relevance and Adaptive Differential Privacy

Enhancing data security in massive data sets using blockchain and federated learning: a loosely coupled approach

Research on Federated Sharing Methods for Massive Data in Blockchain

Assoc. Prof. Dr. Jing Huang | Network Security Awards | Best Researcher Award

Assoc. Prof. Dr. Jing Huang, Beijing university of technology, China

Jing Huang is an Associate Professor at the Faculty of Information Technology at Beijing University of Technology, where he has been a faculty member since July 2007. He holds a strong research focus on blockchain safety supervision, big data, data mining, machine learning, and brain-inspired computing. Dr. Huang has received several accolades for his contributions to education and research, including the Students’ Favourite Teacher Award at Beijing University of Technology in July 2021 and the Wu Wenjun AI Science & Technology Award (Second Prize) from the Chinese Association for Artificial Intelligence in January 2021. Additionally, he has been recognized as an Annual Excellent Member of CAAI in the same year. Dr. Huang is actively involved in professional activities, serving as a supervisor and member of the Beijing Association for Artificial Intelligence (BAAI) since 2018 and as Associate Secretary-General and Standing Committee member of the Committee of Education and Popular Science in CAAI since 2020. He is also a member of the evaluation panel for the Beijing Nova Program, contributing to the advancement of artificial intelligence and technology in China.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award: Dr. Jing Huang

Profile: Dr. Jing Huang is an Associate Professor at the Faculty of Information Technology, Beijing University of Technology, China. With a robust academic background and over 16 years of experience in the field, Dr. Huang has established herself as a leading researcher in areas such as blockchain safety supervision, big data, data mining, machine learning, and brain-inspired computing.

Education 🎓

Ph.D. in Computer Science
Beijing University of Technology, Beijing, China
(Year of completion not specified)
M.S. in Computer Science
Beijing University of Technology, Beijing, China
(Year of completion not specified)
B.S. in Computer Science
Beijing University of Technology, Beijing, China
(Year of completion not specified)

Work Experience 💼

Associate Professor
Faculty of Information Technology, Beijing University of Technology, Beijing, China
Duration: July 2007 – Present

Achievements 🌟

Students’ Favourite Teacher Award
Beijing University of Technology, July 2021
Wu Wenjun AI Science & Technology Award (Second Prize)
Chinese Association for Artificial Intelligence, January 2021
Annual Excellent Member for CAAI
Chinese Association for Artificial Intelligence (CAAI), January 2021

Professional Activities 🤝

Supervisor and Member
Beijing Association for Artificial Intelligence (BAAI)
Duration: 2018 – Present
Associate Secretary-General and Standing Committee Member
Committee of Education and Popular Science in CAAI
Duration: 2020 – Present
Evaluation Panel Member
Beijing Nova Program

Publication Top Notes

An Improved Dyna-Q Algorithm Inspired by the Forward Prediction Mechanism in the Rat Brain for Mobile Robot Path Planning

Smart contracts vulnerability detection model based on adversarial multi-task learning

Prof. Dr. Haiyan Kang | Network Security Awards | Best Researcher Award

Prof. Dr. Haiyan Kang | Network Security Awards | Best Researcher Award

Prof. Dr. Haiyan Kang , Beijing Information Science and Technology University, China

Prof. Dr. Kang Haiyan for the Best Researcher Award

Education

Work Experience

Achievements

Awards and Honors

Publication Top Notes:

Hierarchical Stackelberg Game Swarm Learning Incentive Method for Wireless Edge Network

Community overlap discovery algorithm based on industrial big data

Research on the Deep Learning Method Based on Data Feature Relevance and Adaptive Differential Privacy

Enhancing data security in massive data sets using blockchain and federated learning: a loosely coupled approach

Research on Federated Sharing Methods for Massive Data in Blockchain