Rate My Professor Zhipeng Cai

His research interests include machine learning, privacy and security, large language models, and big data, with notable contributions to resource management and scheduling for high-performance computing and data acquisition, collection, computation, and publication in wireless networks. Cai has authored over 300 publications, including more than 100 in IEEE/ACM Transactions journals, accumulating over 20,000 citations. Key works include "Generative Adversarial Networks: A Survey Towards Private and Secure Applications" in ACM Computing Surveys (2022), "Towards Neural Network-based Communication System: Attack and Defense" in IEEE Transactions on Dependable and Secure Computing (2023), "Privacy-Preserved Data Sharing Towards Multiple Parties in Industrial IoTs" in IEEE Journal on Selected Areas in Communications (2020), "A Private and Efficient Mechanism for Data Uploading in Smart Cyber-Physical Systems" in IEEE Transactions on Network Science and Engineering (2020), and "Collective Data-Sanitization for Preventing Sensitive Information Inference Attacks in Social Networks" in IEEE Transactions on Dependable and Secure Computing (2018).

Cai is an IEEE Fellow (2024), ACM Distinguished Member (2025), NSF CAREER Award recipient (2013), and AAIA Fellow (2023). He ranks among the World’s Top 2% Scientists by Stanford University (2020–2024) and top 0.05% of scholars by ScholarGPS. As Editor-in-Chief of Elsevier High-Confidence Computing Journal, he edits multiple IEEE Transactions and has chaired conferences including ICDCS. He has supervised over 24 Ph.D. students, 15 now tenure-track faculty in U.S. institutions, and supports cybersecurity education through Eureka Labs, with over 75,200 views since 2020.