Jingjie Li (李竞捷)
Ph.D. Candidate, University of Wisconsin-Madison
My research aims to design user-centric systems that preserve user privacy for interactive technologies, particularly augmented/virtual reality and smart home. To empower users in controlling privacy, I adopt two angles: (1) designing practical privacy-enhancing tools and (2) investigating how users navigate privacy and security, which further provides design guidelines. I am happy to apply a broad range of skills from HW/SW design to qualitative methods (and more!) in solving practical and futuristic problems. I enjoy building tangible gadgets that would make our lives more fun to exhaust the daydreams hoarded up during the Wisconsin winter. I am on the academic job market this year! Feel free to reach out if you think I am a good fit for any opportunities :)
Education
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Ph.D. Candidate in Computer Engineering
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University of Wisconsin—Madison (09.2017 to Present)
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Master of Science
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University of Wisconsin—Madison (09.2017 to 05.2019)
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Bachelor of Engineering (First-Class Honours)
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Australian National University (07.2015 to 07.2017)
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Bachelor of Science (ANU-BIT joint degree)
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Beijing Institute of Technology (09.2013 to 07.2015)
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Research Intern
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Visa Research (05.2022 to 08.2022)
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Visiting Scholar
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Max Planck Institute for Security and Privacy (09.2021 to 12.2021)
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Research Intern
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Commonwealth Scientific and Industrial Research Organisation (11.2016 to 02.2017)
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Research Student
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Australian National University (07.2015 to 07.2017)
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Professional Experience
Themes of My Ph.D. Research
“It’s up to the Consumer to be Smart”: Understanding the Security and Privacy Attitudes of Smart Home Users on Reddit
Jingjie Li, Kaiwen Sun, Brittany Huff, Anna Bierley, Younghyun Kim, Florian Schaub, Kassem Fawaz (IEEE S&P'23)
We reveal how smart home users on Reddit develop S&P considerations, how their attitudes evolve given the changing context, and how online discourse influences them.
Kalεido: Real-Time Privacy Control for Eye-Tracking Systems
Jingjie Li, Amrita Roy Chowdhury, Kassem Fawaz, Younghyun Kim (USENIX Sec'21)
Kalεido provides privacy for streaming eye gaze data in real-time by local differential privacy. It offers a user-facing control knob to balance between privacy and utility easily. We implement Kalεido in Unity, which acts as an tunable intermediary privacy layer for various eye-tracking systems including mixed reality.
Velody: Nonlinear Vibration Challenge-Response for Resilient User Authentication
Jingjie Li, Kassem Fawaz, Younghyun Kim (ACM CCS'19)
Velody is a biometric user authentication that leverages nonlinear vibration challenge-response. By updating the unique and unlinkable nonlinear challenge-responses used in authentication, Velody thawrts the threats from reusing/modelling static biometrics.