Zhilin Zhang

About Me

Human-Computer Interaction; Artificial Intelligence; Web Science;

Social Computing; Crowdsourcing; Education; Accessibility

I am a 1st-year Computer Science PhD student at the University of Oxford, advised by Professor Sir Nigel Shadbolt and Dr Jun Zhao, working on the Ethical Web and Data Architecture (EWADA) project.

My research interests are broadly in Human-Computer Interaction (HCI). I study HCI to better understand and improve human interactions with AI and other complex algorithmic systems. I design and build computing systems to positively support users' online behaviors and interactions in a scalable and accessible way.

I received my B.S. and M.S., both in Computer Science, from the University of Illinois at Urbana-Champaign (UIUC), co-advised by Professor Lawrence Angrave and Professor Karrie Karahalios. I also worked with Professor ChengXiang Zhai in the Data and Information Systems Laboratory.

Please feel free to contact me at: zhilinzhang66@gmail.com

[Curriculum Vitae]   [Google Scholar]   [Oxford Page] 

Latest Updates

[06/2022]: A New Paper Accepted at Educational Technology Research and Development Journal

[07/2021]: Best Paper Awards at ASEE 2021

[05/2021]: Two New Papers Accepted at ASEE 2021 ​​

[05/2021]: A New Paper Accepted at SOUPS 2021​​

[01/2021]: Teaching Assistant CS225: Data Structures

[12/2020]: A New Paper Accepted at CHI 2021  ​​

[09/2020]: Best Paper Honorable Mention at ASEE 2020  

[08/2020]: Teaching Assistant CS410: Text Information Systems




Ethical Web and Data Infrastructure in the Age of AI (EWADA) is an ambitious 3-year programme funded by the Oxford Martin School (OMS). Its mission is to reform the concentration of power on the World Wide Web by developing and deploying new forms of technical and legal infrastructure.

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ClassTranscribe is a Microsoft sponsored online learning platform. I analyzed behavioral data of 1,894 users totaling more than 5 million interactions with the system to study students’ attitudes and behaviors towards caption-based video search. The results have been published at SIGCSE and ASEE.

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AI Autograder
AI Autograder

I used a grounded-theory approach to code the qualitative data from a 22-participant interview study. The results provided insights into students’ folk theories, interaction strategies, perceived accuracy, satisfaction and fairness towards the NLP-based grading system. The paper was published at CHI 2021.

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Privacy Probe
Strategic Instructional Innovations

Being motivated to promote equity for students with disabilities and accessible learning opportunities for all students, we conducted surveys and interviews across several large courses in engineering and computing at UIUC to identify course components that engage students with and without disabilities. The paper was published at ASEE 2021.

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I led the design and implementation of a 20-participant user study on an integrated friend-sourcing tool that helps visually impaired people with inaccessible web tasks to investigate users’ attitudes towards the tool, regarding friend-sourcing vs. crowd-sourcing, paid vs unpaid, privacy concerns, and impacts on their relationship. (SOUPS 2021)

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On-Device Interaction Mining
On-Device Interaction Mining

I designed and developed an Android app using the Android Accessibility Service to automatically record users’ interactions with other apps on the phone. The logged data include gestures, screenshots, and view hierarchies. The data was used to mine user habits and generate task shortcuts.

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(* = Equal Contribution)

Advancing Learnersourced Caption Editing for Video-Based STEM Education
Educational Technology Research and Development Journal - Full Paper [pdf]
Bhavya*, Si Chen*, Zhilin Zhang*, Tiffany Wenting Li, Yun Huang, Lawrence Angrave, ChengXiang Zhai

How Students Search Video Captions to Learn: An Analysis of Search Terms and Behavioral Timing Data
ASEE 2021 - Full Paper [pdf]
Zhilin Zhang*, Bhavya*, Lawrence Angrave, Ruihua Sui, Rob Kooper, Chirantan Mahipal, Yun Huang

A UDL-Based Large-Scale Study on the Needs of Students with Disabilities in Engineering Courses
ASEE 2021 - Full Paper [pdf]

3rd Best Paper Award & 2nd Best Diversity, Equity, and Inclusion Paper Award
Jenny Amos*, Zhilin Zhang*, Lawrence Angrave*, Hongye Liu*, Yiyin Shen

WebAlly: Making Visual Task-based CAPTCHAs Transferable for People with Visual Impairments
SOUPS 2021 - Full Paper [pdf]
Zhuohao Zhang, Zhilin Zhang, Haolin Yuan, Natã Barbosa, Sauvik Das, Yang Wang

Attitudes Surrounding an Imperfect AI Autograder
CHI 2021 - Full Paper [pdf]
Silas Hsu*, Tiffany Wenting Li*, Zhilin Zhang, Max Fowler, Craig Zilles, Karrie Karahalios

Improving Student Accessibility, Equity, Course Performance, and Lab Skills: How Introduction of ClassTranscribe is Changing Engineering Education

ASEE 2020 - Full Paper [pdf]

Best Diversity, Equity & Inclusion Paper Honorable Mention
Lawrence Angrave, Karin Jensen, Zhilin Zhang, Chirantan Mahipal, David Mussulman, Christopher Schmitz, Robert Baird, Hongye Liu, Ruihua Sui, Maryalice Wu, and Rob Kooper

Who Benefits? Positive Learner Outcomes from Behavioral Analytics of Online Lecture Video Viewing using ClassTranscribe

SIGCSE 2020 - Full Paper [pdf]

Lawrence Angrave, Zhilin Zhang, Genevieve Henricks-Lepp, Chirantan Mahipal

Attitudes, Behaviors, and Learning Outcomes from Using ClassTranscribe, a UDL-Featured Video-Based Online Learning Platform with Learnersourced Text-Searchable Captions

UIUC - Master's Thesis (2021)  [pdf]

Zhilin Zhang

What Benefits? Exploring the Influences of Student Behaviors in Video-Based Online Learning

UIUC - Undergraduate Senior Thesis (2020)

Zhilin Zhang

ClassTranscribe: Addressing the COVID Challenge and Promoting Better Equity in Education

CRA 2020 - Lightning Talk [video]

Zhilin Zhang, Lawrence Angrave


Contact Me

Please feel free to contact me at zhilinzhang66@gmail.com