Prof. Dr. Li Qianmu | Technology | Best Researcher Award

Professor at Nanjing University of Science and Technology, China

Professional Profile

Orcid
Scopus

Summary

Professor Li Qianmu is an eminent academic and research leader at Nanjing University of Science and Technology, serving as Deputy Dean of its Research Institute and a PhD supervisor. Internationally recognized for his groundbreaking work in cybersecurity, Professor Li has held influential positions across academia, government, and industry, including as a foreign academician, Tencent Cloud Most Valuable Expert, and Deputy Director of the Expert Committee of the Talent Center under China’s Ministry of Industry and Information Technology. He has contributed significantly to trustworthy intelligent systems and data space technologies, and has published over 70 high-impact papers and authorized more than 100 patents.

Educational Details

Professor Li Qianmu holds a doctoral degree and has cultivated a career anchored in scientific excellence and innovation. As a doctoral supervisor, he plays a pivotal role in mentoring the next generation of researchers in cybersecurity and trustworthy systems.

Professional Experience

Professor Li currently serves as Professor and Deputy Dean at the School of Science and Technology, Nanjing University of Science and Technology. He is a member of the university’s Academic Committee and has also taken on leadership roles such as Vice President of the Jiangsu Computer Society, Vice President of the Jiangsu Cyberspace Security Society, and Team Leader of the General Group of the Jiangsu Digital Standardization Technical Committee. Nationally, he has been involved in shaping AI investment and standards as an Expert Member of the National Artificial Intelligence Industry Investment Fund Advisory Committee and Member of IEC SEG13.

Research Interests

His core research areas include cybersecurity in computing power networks, trustworthy intelligent systems, ontology-based security architectures, industrial internet security, and intelligent perception in large-scale computing networks. His research emphasizes multi-scenario threat modeling, autonomous defense systems, and cognitive countermeasure technologies for critical infrastructure.

Author Metrics 

Professor Li has published over 70 high-level scientific papers indexed in SCI and Scopus journals and conferences, including multiple top-tier international venues. He is the author of the book “Multi-Scenario Threat Endogenous Defense Architecture and Ontology Security Key Technologies” (ISBN: 978-1631815652). His work has garnered extensive citations, and his publications have been included in the 2023 Highly Cited Papers of Wiley and reprinted by NASA laboratories. He was also named the 2019 Challenge Problem Winner at AAAI and authored one of the Top 50 Best Papers at TRB’s centennial conference.

Awards and Honors

Professor Li has received 5 first prizes and 9 second prizes in provincial and ministerial science and engineering categories. Notable achievements include:

  • First Prize, Jiangsu Provincial Science and Technology Progress Award (2023)

  • Top 10 Scientific and Technological Advances in Communications, China Institute of Communications (2024)

  • Second Prize, Wu Wenjun Artificial Intelligence Science and Technology Award (2025)

  • First Prize, Science and Technology Award, China Command and Control Society (2024)

  • Second Prize, Outstanding Achievements Award in Social Sciences, Ministry of Education

  • Second Prize, Jiangsu Provincial Philosophy and Social Sciences Award
    His technologies have been recognized by the China Education and Research Network and adopted into Jiangsu’s standardization initiatives supporting high-quality economic development.

Publication Top Notes

1. A Knowledge Distillation Enhanced Semi-Supervised Federated Learning Framework for Intrusion Detection in EV Charging Networks

  • Journal: IEEE Internet of Things Journal

  • Publication Date: 2025

  • DOI: 10.1109/JIOT.2025.3577666

  • Contributors: Luanjuan Jiang, Qianmu Li, Xun Che, Xin Chen

  • Abstract Summary: This paper presents a semi-supervised federated learning framework enhanced with knowledge distillation for detecting intrusions in electric vehicle (EV) charging networks. The framework addresses data privacy concerns while achieving high detection accuracy with limited labeled data.

2. A Novel Multi-Agent Game-Theoretic Model for Cybersecurity Strategies in EV Charging Networks: Addressing Risk Propagation and Budget Constraints

  • Journal: Energy

  • Publication Date: September 2025

  • DOI: 10.1016/j.energy.2025.136847

  • Contributors: Luanjuan Jiang, Qianmu Li, Xin Chen

  • Abstract Summary: The study introduces a game-theoretic model involving multiple agents to optimize cybersecurity strategies in EV charging networks, accounting for the spread of cyber risks and financial limitations.

3. Research on Hidden Backdoor Prompt Attack Method

  • Journal: Symmetry

  • Publication Date: June 16, 2025

  • DOI: 10.3390/sym17060954

  • Contributors: Huanhuan Gu, Qianmu Li, Yufei Wang, Yu Jiang, Aniruddha Bhattacharjya, Haichao Yu, Qian Zhao

  • Abstract Summary: This article proposes a new prompt-based hidden backdoor attack technique targeting large language models and neural networks, exploring stealth strategies and their implications for AI security.

4. Understanding Convolutional Neural Networks From Excitations

  • Journal: IEEE Transactions on Neural Networks and Learning Systems

  • Publication Date: May 2025

  • DOI: 10.1109/TNNLS.2024.3430978

  • Contributors: Zijian Ying, Qianmu Li, Zhichao Lian, Jun Hou, Tong Lin, Tao Wang

  • Abstract Summary: This research provides a new interpretability framework for convolutional neural networks (CNNs) based on excitation analysis, enhancing understanding of model behavior and feature relevance.

5. BioElectra-BiLSTM-Dual Attention Classifier for Optimizing Multilabel Scientific Literature Classification

  • Journal: The Computer Journal

  • Publication Date: May 15, 2025

  • DOI: 10.1093/comjnl/bxae132

  • Contributors: Muhammad Inaam ul Haq, Qianmu Li, Khalid Mahmood, Ayesha Shafique, Rizwan Ullah

  • Abstract Summary: The paper introduces a novel BioElectra-BiLSTM-Dual Attention model to enhance the multilabel classification of scientific documents, addressing semantic dependencies and optimizing classification accuracy.

Conclusion

Prof. Dr. Li Qianmu stands out as a top-tier candidate for the Best Researcher Award in Technology. His sustained contributions to cutting-edge cybersecurity and AI research, policy advisory roles, and patent output reflect a rare blend of scholarly excellence and practical impact. He represents the ideal embodiment of innovation-driven research leadership.

Li Qianmu | Technology | Best Researcher Award