Personal profile
Biography
Jingjie Li is a Lecturer in the School of Informatics, University of Edinburgh and a member of the Institute for Computing Systems Architecture. Jingjie’s research spans privacy, security, and human-centered systems broadly. His research aims to develop user-centric solutions that seamlessly integrate privacy and security into users’ interactions with emerging digital technologies, including smart home, AR, and VR systems. He published impactful work at premier conferences in security and privacy (IEEE S&P, USENIX Security, and ACM CCS). His interdisciplinary work also received multiple best paper and design contest awards, including an ACM CHI Best Paper Award and an IEEE Micro Top Pick. Jingjie’s research led to an award from Meta for AR/VR privacy, and he has been recognized as a Cyber-Physical Systems (CPS) Rising Star by the NSF CPS program. He was an invited panelist at the US Federal Trade Commission’s PrivacyCon 2022. Before joining the University of Edinburgh, Jingjie obtained a Ph.D. degree from the University of Wisconsin-Madison in 2023 and a Bachelor’s degree with first-class honors from the Australian National University in 2017.
Education/Academic qualification
PhD in Electrical and Computer Engineering, University of Wisconsin-Madison
2017 → 2023
Bachelor of Engineering (R&D) (Honours), Australian National University
2015 → 2017
Bachelor of Science, Beijing Institute of Technology
2013 → 2015
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Collaborations and top research areas from the last five years
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Privacy Bills of Materials (PriBOM): A transparent privacy information inventory for collaborative privacy notice generation in mobile app development
Tao, Z., Pan, S., Xing, Z., Sun, X., Haggag, O., Grundy, J., Li, J. & Zhu, L., 19 Jul 2025, Proceedings of the 25th Privacy Enhancing Technologies Symposium. Jansen, R. & Shafiq, Z. (eds.). Privacy Enhancing Technologies Board, p. 392-409 18 p. (Proceedings on Privacy Enhancing Technologies; vol. 2025, no. 4).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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“Impressively scary": Exploring user perceptions and reactions to unraveling machine learning models in social media applications
West, J., Cagiltay, B., Zhang, S., Li, J., Fawaz, K. & Banerjee, S., 25 Apr 2025, CHI '25: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. Yamashita, N., Evers, V., Yatani, K., Ding, X., Lee, B., Chetty, M. & Toups-Dugas, P. (eds.). New York, NY, United States: Association for Computing Machinery (ACM), p. 1-21 21 p. 818Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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A glimpse into the Pandora’s box: Demystifying on-device AI on Instagram and TikTok
West, J., Li, J. & Fawaz, K., 19 Feb 2025, In: Communications of the ACM. 68, 3, p. 30-32 3 p.Research output: Contribution to journal › Comment/debate › peer-review
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"Just a tool, until you stab someone with it": Exploring Reddit users' questions and advice on the legality of port scans
Hrle, T., Milad, M., Li, J. & Woods, D., 20 Nov 2024, EuroUSEC '24: Proceedings of the 2024 European Symposium on Usable Security. Karegar, F. & Farooq, A. (eds.). New York, NY, United States: Association for Computing Machinery (ACM), p. 322-336 15 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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I see an IC: A mixed-methods approach to study human problem-solving processes in hardware reverse engineering
Walendy, R., Weber, M., Li, J., Becker, S., Wiesen, C., Elson, M., Kim, Y., Fawaz, K., Rummel, N. & Paar, C., 11 May 2024, Proceedings of the CHI Conference on Human Factors in Computing Systems. Mueller, F. F., Kyburz, P., Williamson, J. R., Sas, C., Wilson, M. L., Toups Dugas, P. & Shklovski, I. (eds.). ACM, p. 1-20 20 p. 831Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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