Tianshi Li header image

About me


I'm a Ph.D. Candidate at the Human-Computer Interaction Institute at Carnegie Mellon University, advised by Prof. Jason Hong. My main research interest lies at the intersection of Human-Computer Interaction, Security and Privacy, and Software Engineering. Specifically, I conduct two types of research:
In addition to my primary focus in developer privacy research, I have always yearned to apply my "Understanding + Building" research methodology to tackle more real-world problems. Thus, I have side projects in investigating the adoption problem of COVID-19 contact-tracing apps, using AI to improve text entry and notification management, and using social media data to help people combat natural disasters.

News

05/2021 πŸ“„ One paper is accepted to TOCHI 2022.
03/2022 πŸ€ Proposed my Ph.D. dissertation "Privacy-Enhancing Development Environment"
02/2022 πŸ“„ One paper is accepted to PETS 2022.
01/2022 πŸ‘©β€βš–οΈ I started serving on the CHI 2022 Late-Breaking Work (LBW) Program Committee.
11/2021 πŸ“„ One paper is accepted to CHI 2022. (updates on 04/2022: My CHI'22 paper on developers' challenges about creating privacy nutrition labels won an honorable mention award!)
11/2021 πŸ“„ One paper is accepted to PETS 2022.
08/2021 πŸ† I am awarded the 2021 CyLab Presidential Fellowship.
07/2021 πŸ“„ One paper is accepted to IMWUT 2021.
06/2021 πŸ“„ One paper is accepted to TOCHI 2021.
06/2021 πŸ“„ One paper is accepted to the Special Issue β€œIoT for Fighting COVID-19” of Elsevier Pervasive and Mobile Computing (PMC) Journal.
04/2021 πŸ‘©β€βš–οΈ I started serving on the USENIX Security '22 Program Committee.
08/2020 πŸ“„ One paper is accepted to CSCW 2020.

Publications

The complete list of my publications can be found on my Google Scholar page.

C-PAK: Correcting and Completing Variable-length Prefix-based Abbreviated Keystrokes
TOCHI 2022 (to appear)
Tianshi Li, Philip Quinn, Shumin Zhai.

Understanding iOS Privacy Nutrition Labels: An Exploratory Large-Scale Analysis of App Store Data [preprint] [ACM Link]
CHI LBW 2022
Yucheng Li, Deyuan Chen, Tianshi Li, Yuvraj Agarwal, Lorrie Faith Cranor, Jason I. Hong.

Understanding Challenges for Developers to Create Accurate Privacy Nutrition Labels. [preprint] [ACM Link]
CHI 2022
Tianshi Li, Kayla Reiman, Yuvraj Agarwal, Lorrie Faith Cranor, Jason I. Hong.
πŸ… Best Paper Honorable Mention Award

Charting App Developers’ Journey Through Privacy Regulation Features in Ad Networks.
PETS 2022 (to appear)
Mohammad Tahaei, Kopo M. Ramokapane, Tianshi Li, Jason I. Hong, Awais Rashid

Understanding Privacy-Related Advice on Stack Overflow. [preprint]
PETS 2022 (to appear)
Mohammad Tahaei, Tianshi Li, Kami Vaniea.

Honeysuckle: Annotation-Guided Code Generation of In-App Privacy Notices [ACM link]
IMWUT 2021/ UbiComp 2021
Tianshi Li, Elijah B Neundorfer, Yuvraj Agarwal, Jason I. Hong

Alert Now or Never: Understanding and Predicting Notification Preferences of Smartphone Users. [ACM link]
TOCHI 2021
Tianshi Li, Julia Haines, Miguel Flores Ruiz de Eguino, Jason I. Hong, Jeffrey Nichols

What Makes People Install a COVID-19 Contact-Tracing App? Understanding the Influence of App Design and Individual Difference on Contact-Tracing App Adoption Intention. [Elsevier link] [arXiv preprint]
Special Issue β€œIoT for Fighting COVID-19” of Elsevier Pervasive and Mobile Computing (PMC) Journal.
Tianshi Li, Camille Cobb, Jackie (Junrui) Yang, Sagar Baviskar, Yuvraj Agarwal, Beibei Li, Lujo Bauer, Jason I. Hong.

How Developers Talk about Personal Data and What It Means for User Privacy: A Case Study of a Developer Forum on Reddit. [ACM link] [preprint] [5-minute talk]
CSCW 2020.
Tianshi Li, Elizabeth Louie, Laura Dabbish, Jason I. Hong.

Decentralized is not risk-free: Understanding public perceptions of privacy-utility trade-offs in COVID-19 contact-tracing apps. [arXiv preprint] [project website]
in arXiv preprint 2020.
Tianshi Li, Jackie (Junrui) Yang, Cori Faklaris, Jennifer King, Yuvraj Agarwal, Laura Dabbish, Jason I. Hong.

Analyzing the Role of General App Creators in Protecting the Privacy of Vulnerable Populations. [pdf]
CHI 2020 Workshop: Privacy and Power: Acknowledging the Importance of Privacy Research and Design for Vulnerable Populations.
Tianshi Li, Jason I. Hong.

Demystifying Complex Workload–DRAM Interactions: An Experimental Study. [arXiv preprint]
SIGMETRICS 2019.
Saugata Ghose, Tianshi Li, Nastaran Hajinazar, Damla Senol Cali, Onur Mutlu

Coconut: An IDE Plugin for Developing Privacy-Friendly Apps. [pdf] [project website] [talk slides] [news story] [demo video]
IMWUT 2018/ UbiComp 2019.
Tianshi Li, Yuvraj Agarwal, Jason I. Hong.

Using ECC DRAM to Adaptively Increase Memory Capacity [arXiv preprint].
in arXiv preprint 2017.
Yixin Luo, Saugata Ghose, Tianshi Li, Sriram Govindan, Bikash Sharma, Bryan Kelly, Amirali Boroumand, Onur Mutlu.

Understanding Latency Variation in Modern DRAM Chips: Experimental Characterization, Analysis, and Optimization. [pdf]
SIGMETRICS 2016.
Kevin K. Chang, Abhijith Kashyap, Hasan Hassan, Saugata Ghose, Kevin Hsieh, Donghyuk Lee, Tianshi Li, Gennady Pekhimenko, Samira Manabi Khan, Onur Mutlu.