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Director: Professor Matthew Lease ACM Distinguished Member • AAAI Senior Member Publications • Datasets & Software • Slides 1616 Guadalupe Ste 5.202 |
Overview: Our research spans artificial Intelligence (AI) modeling and human-computer interaction (HCI) design. We create novel datasets, build AI models, and evaluate model performance and end-user impacts. When automated AI falls short, we design human-in-the-loop approaches supported by AI model explanations and creative user interfaces. To promote fair AI, we design better ways to annotate data without bias and modeling techniques to mitigate dataset biases. We conduct fundamental research, applied to real-world problems that matter, as part of UT Austin's Good Systems Grand Challenge to design responsible AI technologies. One theme of ongoing work is automated, human-in-the-loop, and human-safe practices to safeguard the information environment online against threats such as hate speech, extremism, and foreign influence. As part of the NSF-Simons AI Institute for Cosmic Origins (CosmicAI), we are also working to accelerate scientific discovery with AI.
Research Areas:
Crowdsourcing & Human Computation (HCOMP) •
Fair & Explainable AI •
Information Retrieval (IR) •
Natural Language Processing (NLP)
Current PhD Students
Chi-Yang (Ethan) Hsu (iSchool) [scholar, LinkedIn]
Gauri Kambhatla (Computer Science) [scholar, LinkedIn]
Houjiang Liu (iSchool) [scholar, LinkedIn]
Yiheng (Sam) Su (iSchool) [scholar, LinkedIn]
Some recent publications and talks:
Some Research Awards 🏆
Ripon Saha, Matthew Lease, Sarfraz Khurshid, and Dewayne Perry.
Improving Bug Localization using Structured Information Retrieval.
In IEEE/ACMConference on Automated Software Engineering (ASE), pages 345-355, 2013.
Houjiang Liu, Anubrata Das, Alexander Boltz, Didi Zhou, Daisy Pinaroc, Matthew Lease, and Min Kyung Lee. Human-centered NLP Fact-checking: Co-Designing with Fact-checkers using Matchmaking for AI. Proceedings of the ACM on Human-Computer Interaction, 2024. Presented at the 28th ACM Conference on Computer Supported Cooperative Work (CSCW). Honorable Mention. [ pdf | preprint ]
Ruijiang Gao, Maytal Saar-Tsechansky, Maria De-Arteaga, Ligong Han, Min Kyung Lee, Wei Sun and Matthew Lease. Robust Human-AI Collaboration with Bandit Feedback. The Conference on Information Systems and Technology (CIST), 2022. Best Student Paper award. [ preprint | conference-website ]
Mucahid Kutlu, Tyler McDonnell, Tamer Elsayed, and Matthew Lease. Annotator Rationales for Labeling Tasks in Crowdsourcing. Journal of Artificial Intelligence Research (JAIR), 69:143--189, 2020. Award Winning Papers Track. [ pdf | blog-post | data | conference-website ]
Soumyajit Gupta, Mucahid Kutlu, Vivek Khetan, and Matthew Lease. Correlation, Prediction and Ranking of Evaluation Metrics in Information Retrieval. In Proceedings of the 41st European Conference on Information Retrieval (ECIR), pages 636--651, 2019. Best Student Paper award. [ news | pdf | data | sourcecode | slides | preprint ]
Tyler McDonnell, Matthew Lease, Mucahid Kutlu, and Tamer Elsayed. Why Is That Relevant? Collecting Annotator Rationales for Relevance Judgments. In Proceedings of the 4th AAAI Conference on Human Computation and Crowdsourcing (HCOMP), pages 139--148, 2016. Best Paper Award. [ news | pdf | blog-post | data | slides ]
Hyun Joon Jung and Matthew Lease. A Discriminative Approach to Predicting Assessor Accuracy. In Proceedings of the 37th European Conference on Information Retrieval (ECIR), pages 159--171, 2015. Samsung Human-Tech Paper Award: Silver Prize in Computer Science. [ pdf | news ]
Some Demos
Li Shi, Nilavra Bhattacharya, Anubrata Das, Matthew Lease, and Jacek Gwizdka. The Effects of Interactive AI Design on User Behavior: An Eye-tracking Study of Fact-checking COVID-19 Claims. In Proceedings of the 7th ACM SIGIR Conference on Human Information, Interaction and Retrieval (CHIIR), pages 315--320, 2022. [ pdf | demo | sourcecode | video | poster | preprint ]
Anubrata Das, Brandon Dang, and Matthew Lease. Fast, Accurate, and Healthier: Interactive Blurring Helps Moderators Reduce Exposure to Harmful Content. In Proceedings of the 8th AAAI Conference on Human Computation and Crowdsourcing (HCOMP), pages 33--42, 2020. [ pdf | demo | blog-post | sourcecode | video | slides ]
Some News
How Researchers Navigate Accountability, Transparency, and Trust When Using AI Tools in Research (July 24, 2026)
iSchool Researchers Bring Open-Source AI, Fairness, and Accountability to ACM FAccT 2026 (June 25, 2026)
To Spot Toxic Speech Online, Try AI: A new tool helps balance accuracy with fairness toward all groups in social media (June 5, 2025)
Dr. Lease Wins Two “Test of Time” Awards in 2024 (December 13, 2024)
Using AI to Combat Misinformation and Disinformation. Move 37 Podcast: Conversations with Leaders Shaping the AI Revolution. (October 22, 2024)
Good Systems, Great Policy (August 9, 2024)
Looking Forward: Good Systems Leaders & Partners on Opportunities and Challenges in Ethical AI (September 5, 2023)
Recent honors and awards for Amazon scientists (additional coverage of AAAI Senior Member award, Amazon (April 20, 2023)
Announcement of AAAI Senior Member Status (January 3, 2023)
Recent honors and awards for Amazon scientists (additional coverage of ACM Distinguished Member award, Amazon, December 23, 2022)
Exploring Annotator Rationales for Active Learning with Transformers (UTCS, Dec. 14, 2022)
ACM Honors 2022 Distinguished Members (ACM, December 7, 2022)
Exploring Methods to Improve the Psychological Wellness of Content Moderators (UTCS, March 7, 2022)
An American gig work app was accused of working for Russia. Why? (NBC News, March 3, 2022)
Texas Researchers Pivot to Covid-19 (September 25, 2020)
TACC Covid-19 Twitter Dataset Enables Social Science Research about Pandemic (May 4, 2020)
Good Systems research on misinformation & fair AI (July 29, 2019)
Misinformation grant from Micron Foundation (May 29, 2019)
Press: Austin Statesman article Russian bots and the Austin bombings: Can fact-checking offset division, misinformation? (March 28, 2018). Read about our AI + Crowd system for checking online claims (AAAI 2018).
ALUMNI 🎓
Past Postdocs
Venelin Kovatchev (scholar, LinkedIn), 2022, Lecturer, School of Computer Science, College of Engineering and Physical Sciences at the University of Birmingham
Mucahid Kutlu (scholar, LinkedIn), 2018, Assistant Professor, Dept. of Computer Science and Engineering, Qatar University
Past Ph.D. Students
Anubrata Das (iSchool) [scholar, LinkedIn], 2025
Soumyajit Gupta (Computer Science) [scholar, LinkedIn], 2025
Md. Mustafizur Rahman (iSchool), 2021, Microsoft
An Thanh Nguyen (Computer Science), 2020
Ye Zhang (Computer Science), 2019, Google
Hyunjoon Jung (iSchool) [LinkedIn], 2015, Adobe
Past Masters Students
Utkarsh Mujumdar (iSchool), 2023, Autonomize AI. Thesis: Designing a Multi-Perspective Search System Using Large Language Models and Retrieval Augmented Generation. 🏆 Winner: Dean's Choice Award.
Yian Wong (Computer Science), 2023, CenterPoint Energy. Thesis: Exploring Multiple Perspectives to Mitigate Cognitive Biases through an Integrated Interface to Language Model.
Sooyong Lee (Computer Science), 2023, UMass CS PhD Program. Thesis: Multi-Task Learning for Hate Speech Detection.
Yiheng (Sam) Su (Computer Science), 2023, iSchool PhD Program. Thesis: Wrapper Boxes for Increasing Model Interpretability via Example-based Explanations.
Sukanya Thapa (iSchool), 2023, Lazaza. Thesis: Enhancing Worker Management and Supporting External Tasks in Crowdsourced Data Labeling.
(2019-2022 to be posted...)
Vivek Pradhan, 2018, Earthmetry
Tyler McDonnell, 2017, SparkCognition
Ivan Oropeza, 2015, Google
Haofeng Zhou, 2015, Facebook
Shruti Bhosale, 2014, Facebook
Hohyon Ryu, 2012, OXOpolitics
Aashish Sheshadri, 2014, PayPal
Donna Vakharia, 2014, PayPal
Past Undergraduate Students (selected)
Qiwei (Renee) Li, 2019, Michigan PhD Program. Thesis: Clickbait and Emotional Language in Fake News
