Laboratory for Artificial Intelligence and Human-Centered Computing (AI&HCC), University of Texas at Austin The University of Texas at Austin     The University of Texas at Austin   The University of Texas at Austin

Laboratory for Artificial Intelligence and Human-Centered Computing (AI&HCC)

group photo

Director: Professor Matthew Lease

ACM Distinguished MemberAAAI Senior MemberAmazon Scholar

PublicationsDatasets & SoftwareSlides

1616 Guadalupe Ste 5.202
Austin, TX 78701-1213
Campus box: D8600
Room: UTA 5.520 • 5th floor map
Lab Phone: (512) 232-1189
Director's Phone: (512) 471-9350

Hook 'em Horns!

One-page Lab Flyer

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. A theme of ongoing work is content moderation: automated, human-in-the-loop, and human-safe practices to curb disinformation, hate speech, and polarization online.

Research Areas: Crowdsourcing & Human Computation (HCOMP) • Fair & Explainable AI • Information Retrieval (IR) • Natural Language Processing (NLP)

Some recent publications and talks:

  • Label aggregation and agreement: WebConf20, KDD21, WebConf22, JAIR23
  • Annotation task design: JAIR20 (award), CSCW21, Frontiers22, HCOMP23(x2), IUI24
  • Human-centered fact-checking: UIST18, CHIIR22, ACL22, IPM23
  • Hate speech detection: NeurIPS21, iConference22, WebConf23
  • Human-AI teaming: BHCC20, AIES21, IJCAI21, CIST22 (award), HHAI23
  • Information Retrieval Evaluation: CIKM18, SIGIR18, ECIR19 (award), ICTIR20, NeurIPS21, iConf22, ECIR23
  • Bias & Fairness: NeurIPS21, UAI22, WebConf23, HCOMP23
  • Supporting content moderators: HCOMP20, CHI21 (See also: CS News, instagram and twitter)

PhD Students

Alex Braylan (Computer Science) [scholar, LinkedIn]
Anubrata Das (iSchool) [scholar, LinkedIn]
Soumyajit Gupta (Computer Science) [scholar, LinkedIn]
Gauri Kambhatla (Computer Science) [scholar, LinkedIn]
Houjiang Liu (iSchool) [scholar, LinkedIn]
Yiheng (Sam) Su (iSchool) [LinkedIn]

Masters Students

Selected Research & Demos

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. [conference-website]

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. [ bib | pdf | demo | sourcecode | video | poster | tech-report ]

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. [ bib | pdf | demo | blog-post | sourcecode | video | slides ]

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. [ bib | 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 | bib | pdf | data | sourcecode | slides | tech-report ]

An Thanh Nguyen, Aditya Kharosekar, Aditya Kharosekar, Saumyaa Krishnan, Siddhesh Krishnan, Elizabeth Tate, Byron C. Wallace, and Matthew Lease. Believe it or not: Designing a Human-AI Partnership for Mixed-Initiative Fact-Checking. In Proceedings of the 31st ACM User Interface Software and Technology Symposium (UIST), pages 189--199, 2018. [ bib | pdf | demo | sourcecode | video | slides ]

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 | bib | 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.bib | pdf | news ]

Selected Talks: Videos and Slides (videos link is most current content)

Panel: Fair & Transparent AI: Lessons from UT Austin's Good Systems Grand Challenge (April 20, 2021)
Talk: Reducing Psychological Impacts of Content Moderation Work. UT Austin's Good Systems: Future of Work seminar series (Feb. 8, 2021)
Talk: Toward Safer Content Moderation and Better Supporting Complex Annotation Tasks Delft University speaker series on "Crowd Computing & Human-Centered AI" (The Academic Fringe Festival (Nov. 23, 2020)
Interview: Curbing misinformation, with help from the Micron Foundation (November 4, 2019)
Panel: Army Mad Scientist Day -- Ethics & the Future of AI Innovation (April 25, 2019)

Selected News


Venelin Kovatchev (scholar, LinkedIn), 2022, Lecturer, School of Computer Science, College of Engineering and Physical Sciences at the University of Birmingham
Mucahid Kutlu (scholar), 2018, Asst. Professor, Dept. Computer Engineering, TOBB University of Economics and Technology

Ph.D. Students
Md. Mustafizur Rahman (LinkedIn), 2021, Microsoft
An Thanh Nguyen, 2020
Ye Zhang, 2019, Google
Hyunjoon Jung, 2015, Adobe

Masters Students
Utkarsh Mujumdar (iSchool). Thesis: Designing a Multi-Perspective Search System Using Large Language Models and Retrieval Augmented Generation. Winner: Dean's Choice Award.
Yian Wong (Computer Science). Thesis: Exploring Multiple Perspectives to Mitigate Cognitive Biases through an Integrated Interface to Language Model.
Sooyong Lee (Computer Science). Thesis: Multi-Task Learning for Hate Speech Detection.
Yiheng (Sam) Su, 2023. Thesis: Wrapper Boxes for Increasing Model Interpretability via Example-based Explanations.
Sukanya Thapa, 2023. 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

Undergraduate Students (selected)
Didi Zhou, 2022, Google. Thesis: Leveraging Annotator Rationales for Active Learning with Transformers. See also: CS Dept. news article (Dec. 14, 2022).
Qiwei (Renee) Li, 2019, Michigan PhD Program. Thesis: Clickbait and Emotional Language in Fake News