Ping Chen

Ping Chen is a Professor and Doctoral Supervisor at the Institute of Big Data, Fudan University. He leads the Endogenous Security Laboratory, a 30+ member team that partners with automotive OEMs, AI platform providers, and public agencies to deliver resilient intelligent vehicle and AI systems. His research spans intelligent connected vehicle security, AI robustness, system and software security, and privacy-aware risk analytics. Prof. Chen was selected for the national-level youth talent program and has coordinated 18 national and provincial projects with cumulative funding of roughly 20M RMB.

Areas of Research

• Large model security – heterogeneity driven safety reviews for diffusion models, RAG poisoning defense, watermarking, and capability boundary assessment for foundation models.
• Intelligent connected vehicles – endogenous defense architectures for ADAS and T-Box units, network resilience assessment, and integrated functional safety plus cybersecurity assurance.
• Endogenous cybersecurity – multi-agent offensive and defensive simulation, reinforcement-learning driven risk detection, adaptive protection against zero-day, APT, and large scale threats.
• System and software security – data structure layout randomization, virtualization monitoring, and lightweight fuzzing strategies for complex software stacks.

Academic and Professional Appointments

• 2021 - Present · Professor and Doctoral Supervisor, Institute of Big Data, Fudan University.
• 2018 - 2021 · Senior Security Architect and Head of Data/Risk Control Security, JD.com Silicon Valley R&D Center.
• 2014 - 2018 · Postdoctoral Researcher, Pennsylvania State University (USA).
• 2012 - 2014 · Senior Researcher, EMC (USA).

Education

• Ph.D. Computer Software and Theory, Nanjing University, 2007-2012.
• Joint Ph.D. Training Cloud Computing Security, Purdue University, 2010-2011.

Flagship Programs

• National Key R&D Program on integrated assurance for intelligent driving systems (PI).
• National Key R&D Program on cyberspace endogenous security mechanisms and assessment (PI).
• MIIT Quantum + Intelligent Connected Vehicles Challenge Project (Lead, 2025-2028).
• Diversified Directed Fuzzing Toolset (Lead, recognized in Shanghai Cybersecurity Innovation Catalog 2024).
• Fu Bao Think Tank LLM (Lead, selected for Shanghai Large Model Product Catalog 2024).

Program Spotlights

• Fudan Security Laboratory – 30+ researchers across all levels deliver 18 national and provincial projects (~20M RMB) while partnering with SAIC, Geely, Huawei, Ant Group, and municipal authorities. The lab helped establish Shanghai’s Nuclear Energy & Nuclear Power Collaborative Innovation Center and the Intelligent Connected Vehicle Collaborative Innovation Center.
• Intelligent Driving Safety & Security Assurance – A National Key R&D Program led by Ping Chen that unifies functional safety and cybersecurity. Outputs include endogenous ADAS/T-Box defense architectures, network resilience assessments, penetration exercises, and turnkey toolkits co-developed with OEMs such as SAIC, Geely, and Chery.
• Large Model Security & Directed Fuzzing Toolset – A heterogeneous AI security stack featuring multimodal directed fuzzing, watermarking for Fu Bao Think Tank deployments, and activation-level RAG poisoning defense. Recognized as a Rank-1 achievement in the 2024 Shanghai Cybersecurity Innovation and Breakthrough Catalog.

Selected Honors

• 2025 · Project on intelligent connected vehicle security risk assessment awarded the 2024 Major Scientific and Technological Progress Award in Network and Data Security (Rank 1).
• 2024 · National Talent Program awardee.
• 2024 · “Diversified Directed Fuzzing Toolset” listed in the Shanghai Cybersecurity Innovation and Breakthrough Achievements Catalog (Rank 1).
• 2024 · “Fu Bao Think Tank” LLM included in the Shanghai Large Model Product Catalog.
• 2021 · Shanghai Leading Talent; co-established city-level innovation centers spanning nuclear energy and intelligent vehicles.

Teaching and Mentorship

Ping Chen teaches a mix of undergraduate and graduate courses while mentoring interdisciplinary security teams.

Current Courses

• Introduction to Artificial Intelligence – Undergraduate core course focusing on trustworthy AI foundations (2024–2026).
• Cybernetics, Information Theory, and Systems Theory – Undergraduate special topics sequence launching in 2025.

Recent Courses

• Computer Principles – Undergraduate, 2022–2024.
• Large-scale Distributed Systems – Graduate, 2022–2024.

Mentorship & Program Leadership

• Advisor for the Undergraduate AI Class and Tengfei College mentor (2025 cohort).
• Supervises 15 Ph.D., 6 Master’s, 4 undergraduate, and 2 postdoctoral researchers; graduates include 1 Ph.D., 7 Master’s, and 2 undergraduate alumni.
• Student teams earned titles at the 2024 Chuang’an Cup Intelligent Vehicle Security CTF, the 2023 and 2024 Qiangwang IoV Security Challenges, and reached the Intel AI Innovation Application finals in 2025.

Service to the Community

• Guest Editor, Mathematics (MDPI), 2025-2026.
• Program Committee member for AAAI 2026, CCS Poster 2025, CCS MTD 2016-2017.
• Reviewer for Journal of Computer Security, Chinese Journal of Computers, Science China, ACM Multimedia, CVPR, IEEE TDSC, IEEE TIFS, Automatica, RAID, CCS, ESORICS, and IET Information Security.

Prof. Chen collaborates closely with industry and government partners to advance trustworthy mobility and AI infrastructures. Contact him via email to explore research partnerships, technology transfer opportunities, or prospective student placements within the Security Laboratory.