I'm an Assistant Professor in the Department of Computer Science, Purdue University. My research broadly connects to the fields of human-computer interaction, applied artificial intelligence and machine learning, computational social science, and behavioral sciences. I use both experimental and computational approaches to examine how to better utilize the wisdom of crowd to enhance machine intelligence (i.e., crowdsourcing and social computing), and how to better design intelligent systems that people can understand, trust and engage with effectively (i.e., human-AI interaction).
Prior to Purdue, I spent a year at Microsoft Research New York City as a postdoctoral researcher in the Computational Social Science group. I completed my Ph.D. in Computer Science at Harvard University, and received my bachelor degree from Tsinghua University, Beijing, China.
Publications
In most cases, my collaborators and I choose to have students as first authors and then determine the authorship alphabetically.
On the Support Vector Effect in DNNs: Rethinking Data Selection and Attribution
Syed Hasan Amin Mahmood, Ming Yin, and Rajiv Khanna
The 31st SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Toronto, Canada, August 2025. (Forthcoming)
Exploring the Cost-Effectiveness of Perspective Taking in Crowdsourcing Subjective Assessment: A Case Study of Toxicity Detection
Xiaoni Duan, Zhuoyan Li, Chien-Ju Ho, and Ming Yin
The Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Albuquerque, NM, April 29 - May 4, 2025.
From Text to Trust: Empowering AI-assisted Decision Making with Adaptive LLM-powered Analysis
Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu, Ziang Xiao, and Ming Yin
The 43rd ACM Conference on Human Factors in Computing Systems (CHI), Yokohama, Japan, April 26 - May 1, 2025.
Understanding the Effects of AI-based Credibility Indicators When People are Influenced by Both Peers and Experts
Zhuoran Lu, Patrick Li, Weilong Wang, and Ming Yin
The 43rd ACM Conference on Human Factors in Computing Systems (CHI), Yokohama, Japan, April 26 - May 1, 2025.
Towards Human-AI Deliberation: Design and Evaluation of LLM-Empowered Deliberative AI for AI-Assisted Decision-Making
Shuai Ma, Qiaoyi Chen, Xinru Wang, Chengbo Zheng, Zhenhui Peng, Ming Yin, and Xiaojuan Ma
The 43rd ACM Conference on Human Factors in Computing Systems (CHI), Yokohama, Japan, April 26 - May 1, 2025.
Best Paper Honorable Mention
Utilizing Human Behavior Modeling to Manipulate Explanations in AI-Assisted Decision Making: The Good, the Bad, and the Scary
Zhuoyan Li and Ming Yin
The 38th Annual Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2024.
How Does the Disclosure of AI Assistance Affect the Perceptions of Writing?
Zhuoyan Li, Chen Liang, Jing Peng, and Ming Yin
The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), Miami, FL, November 2024.
Does More Advice Help? The Effects of Second Opinions in AI-Assisted Decision Making
Zhuoran Lu, Dakuo Wang, and Ming Yin
The 27th ACM Conference on Computer-Supported Coopearitve Work & Social Computing (CSCW), San Jose, Costa Rica, November 2024.
supplementary materials
Mix and Match: Characterizing Heterogeneous Human Behavior in AI-assisted Decision Making
Zhuoran Lu, Syed Hasan Amin Mahmood, Zhuoyan Li, and Ming Yin
The 12th AAAI Conference on Human Computation and Crowdsourcing (HCOMP), Pittsburgh, PA, October 2024.
Designing Behavior-Aware AI to Improve the Human-AI Team Performance in AI-Assisted Decision Making
Syed Hasan Amin Mahmood, Zhuoran Lu, and Ming Yin
The 33rd International Joint Conference on Artificial Intelligence (IJCAI), Jeju, South Korea, August 2024.
supplementary materials
The Value, Benefits, and Concerns of Generative AI-Powered Assistance in Writing
Zhuoyan Li, Chen Liang, Jing Peng, and Ming Yin
The 42nd ACM Conference on Human Factors in Computing Systems (CHI), Honolulu, HI, May 2024.
Best Paper Honorable Mention
"Are You Really Sure?": Understanding the Effects of Human Self-Confidence Calibration in AI-Assisted Decision Making
Shuai Ma, Xinru Wang, Ying Lei, Chunhan Shi, Ming Yin, and Xiaojuan Ma
The 42nd ACM Conference on Human Factors in Computing Systems (CHI), Honolulu, HI, May 2024.
The Effects of Group Composition and Dynamics on Collective Performance
Abdullah Almaatouq, Mohammed Alsobay, Ming Yin, and Duncan J. Watts
Topics in Cognitive Science (topiCS), 16(2), April 2024.
Enhancing AI-Assisted Group Decision Making through LLM-Powered Devil’s Advocate
Chun-Wei Chiang, Zhuoran Lu, Zhuoyan Li, and Ming Yin
The 29th ACM Conference on Intelligent User Interfaces (IUI), Greenville, SC, March 2024.
supplementary materials
Do Crowdsourced Fairness Preferences Correlate with Risk Perceptions?
Chowdhury Mohammad Rakin Haider, Chris Clifton, and Ming Yin
The 29th ACM Conference on Intelligent User Interfaces (IUI), Greenville, SC, March 2024.
Decoding AI's Nudge: A Unified Framework to Predict Human Behavior in AI-assisted Decision Making
Zhuoyan Li, Zhuoran Lu, and Ming Yin
The 38th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, February 2024.
supplementary materials
Synthetic Data Generation with Large Language Models for Text Classification: Potential and Limitations
Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu, and Ming Yin
The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), Singapore, December 2023.
Strategic Adversarial Attacks in AI-assisted Decision Making to Reduce Human Trust and Reliance
Zhuoran Lu, Zhuoyan Li, Chun-Wei Chiang, and Ming Yin
The 32nd International Joint Conference on Artificial Intelligence (IJCAI), Macao, China, August 2023.
supplementary materials
The Effects of AI Biases and Explanations on Human Decision Fairness: A Case Study of Bidding in Rental Housing Markets
Xinru Wang, Chen Liang, and Ming Yin
The 32nd International Joint Conference on Artificial Intelligence (IJCAI), Macao, China, August 2023.
supplementary materials
How Does Value Similarity Affect Human Reliance in AI-Assisted Ethical Decision Making?
Saumik Narayanan, Guanghui Yu, Chien-Ju Ho, and Ming Yin
The 6th AAAI/ACM Conference on AI, Ethics, and Society (AIES), Montreal, Canada, August 2023.
Interactive Concept Learning for Uncovering Latent Themes in Large Text Collections
Maria Leonor Pacheco, Tunazzina Islam, Lyle Ungar, Ming Yin, and Dan Goldwasser
Findings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL), Toronto, Canada, July 2023.
Are Two Heads Better Than One in AI-Assisted Decision Making? Comparing the Behavior and Performance of Groups and Individuals in Human-AI Collaborative Recidivism Risk Assessment
Chun-Wei Chiang, Zhuoran Lu, Zhuoyan Li, and Ming Yin
The 41st ACM Conference on Human Factors in Computing Systems (CHI), Hamburg, Germany, April 2023.
supplementary materials
Watch Out for Updates: Understanding the Effects of Model Explanation Updates in AI-Assisted Decision Making
Xinru Wang and Ming Yin
The 41st ACM Conference on Human Factors in Computing Systems (CHI), Hamburg, Germany, April 2023.
Who Should I Trust: AI or Myself? Leveraging Human and AI Correctness Likelihood to Promote Appropriate Trust in AI-Assisted Decision-Making
Shuai Ma, Ying Lei, Xinru Wang, Chengbo Zheng, Chuhan Shi, Ming Yin, and Xiaojuan Ma
The 41st ACM Conference on Human Factors in Computing Systems (CHI), Hamburg, Germany, April 2023.
Modeling Human Trust and Reliance in AI-assisted Decision Making: A Markovian Approach
Zhuoyan Li, Zhuoran Lu, and Ming Yin
The 37th AAAI Conference on Artificial Intelligence (AAAI), Washington, DC, February 2023.
supplementary materials
Oral Presentation
Effects of Explanations in AI-Assisted Decision Making: Principles and Comparisons
Xinru Wang and Ming Yin
ACM Transactions on Interactive Intelligent Systems (TiiS), 12(4), December 2022.
The Effects of AI-based Credibility Indicators on the Detection and Spread of Misinformation under Social Influence
Zhuoran Lu, Patrick Li, Weilong Wang, and Ming Yin
The 25th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), Online, November 2022.
Best Paper Award
Understanding the Microtask Crowdsourcing Experience for Workers with Disabilities: A Comparative View
Amy Rechkemmer and Ming Yin
The 25th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), Online, November 2022.
Understanding Decision Subjects' Fairness Perceptions and Retention in Repeated Interactions with AI-Based Decision Systems
Meric Altug Gemalmaz and Ming Yin
The 5th AAAI/ACM Conference on AI, Ethics, and Soceity (AIES), Oxford, UK, August 2022.
Towards Better Detection of Biased Language with Scarce, Noisy, and Biased Annotations
Zhuoyan Li, Zhuoran Lu, and Ming Yin
The 5th AAAI/ACM Conference on AI, Ethics, and Soceity (AIES), Oxford, UK, August 2022.
How Does Predictive Information Affect Human Ethical Preferences?
Saumik Narayanan, Guanghui Yu, Wei Tang, Chien-Ju Ho, and Ming Yin
The 5th AAAI/ACM Conference on AI, Ethics, and Soceity (AIES), Oxford, UK, August 2022.
A Holistic Framework for Analyzing the COVID-19 Vaccine Debate
Maria Leonor Pacheco, Tunazzina Islam, Monal Mahajan, Andrey Shor, Ming Yin, Lyle Ungar, and Dan Goldwasser
The Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Seattle, WA, July 2022.
When Confidence Meets Accuracy: Exploring the Effects of Multiple Performance Indicators on Trust in Machine Learning Models
Amy Rechkemmer and Ming Yin
The 40th ACM Conference on Human Factors in Computing Systems (CHI), New Orleans, LA, April 30 - May 6, 2022.
supplementary materials
Best Paper Award
Will You Accept the AI Recommendation? Predicting Human Behavior in AI-Assisted Decision Making
Xinru Wang, Zhuoran Lu, and Ming Yin
The ACM Web Conference (WWW), Online, April 2022.
The Influences of Task Design on Crowdsourced Judgement: A Case Study of Recidivism Risk Evaluation
Xiaoni Duan, Chien-Ju Ho, and Ming Yin
The ACM Web Conference (WWW), Online, April 2022.
A Computer Vision Approach for Estimating Lifting Load Contributors to Injury Risk
Guoyang Zhou, Vaneet Aggarwal, Ming Yin, and Denny Yu
IEEE Transactions on Human-Machine Systems, 52(2), April 2022.
Exploring the Effects of Machine Learning Literacy Interventions on Laypeople's Reliance on Machine Learning Models
Chun-Wei Chiang and Ming Yin
The 27th ACM Conference on Intelligent User Interfaces (IUI), Online, March 2022.
Video-based AI Decision Support System for Lifting Risk Assessment
Guoyang Zhou, Vaneet Aggarwal, Ming Yin, and Denny Yu
IEEE International Conference on Systems, Man, and Cybernetics (SMC), Online, October 2021.
Task Complexity Moderates Group Synergy
Abdullah Almaatouq, Mohammed Alsobay, Ming Yin, and Duncan J. Watts
Proceedings of the National Adademy of Sciences (PNAS), 118(36), September 2021.
Accounting for Confirmation Bias in Crowdsourced Label Aggregation
Meric Altug Gemalmaz and Ming Yin
The 30th International Joint Conference on Artificial Intelligence (IJCAI), Online, August 2021.
You'd Better Stop! Understanding Human Reliance on Machine Learning Models under Covariate Shift
Chun-Wei Chiang and Ming Yin
The 13th ACM Web Science Conference (WebSci), Online, June 2021.
Human Reliance on Machine Learning Models When Performance Feedback is Limited: Heuristics and Risks
Zhuoran Lu and Ming Yin
The 39th ACM Conference on Human Factors in Computing Systems (CHI), Yokohama, Japan, May 2021.
Are Explanations Helpful? A Comparative Study of the Effects of Explanations in AI-Assisted Decision-Making
Xinru Wang and Ming Yin
The 26th ACM International Conference on Intelligent User Interfaces (IUI), College Station, TX, April 2021.
Motivating Novice Crowd Workers through Goal Setting: An Investigation into the Effects on Complex Crowdsourcing Task Training
Amy Rechkemmer and Ming Yin
The 8th AAAI Conference on Human Computation
and Crowdsourcing (HCOMP), Hilversum, Netherlands, October 2020.
Best Paper Award
Does Exposure to Diverse Perspectives Mitigate Biases in Crowdwork? An Explorative Study
Xiaoni Duan, Chien-Ju Ho, and Ming Yin
The 8th AAAI Conference on Human Computation
and Crowdsourcing (HCOMP), Hilversum, Netherlands, October 2020.
Crowdsourcing Detection of Sampling Biases in Image Datasets
Xiao Hu, Haobo Wang, Anirudh Vegesana, Somesh Dube, Kaiwen Yu, Gore Kao, Shuo-Han Chen, Yung-Hsiang Lu, George Thiruvathukal, and Ming Yin
The Web Conference (WWW), Taipei, April 2020.
Understanding the Skill Provision in Gig Economy from a Network Perspective: A Case Study of Fiverr
Keman Huang, Jinhui Yao, and Ming Yin
The 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), Austin, TX, November 2019.
Discovering Biases in Image Datasets with the Crowd
Xiao Hu, Haobo Wang, Somesh Dube, Anirudh Vegesana, Kaiwen Yu, Yung-Hsiang Lu, and Ming Yin
The 7th AAAI Conference on Human Computation
and Crowdsourcing (HCOMP), Skamania Lodge, WA, October 2019. (Work in Progress track)
Leveraging Peer Communication to Enhance Crowdsourcing
Wei Tang, Chien-Ju Ho, and Ming Yin
The Web Conference (WWW), San Francisco, CA, May 2019.
Understanding the Effect of Accuracy on Trust in Machine Learning Models
Ming Yin, Jennifer Wortman Vaughan, and Hanna Wallach
The 37th ACM Conference on Human Factors in Computing Systems (CHI), Glasgow, UK, May 2019.
Best Paper Honorable Mention
Does Stated Accuracy Affect Trust in Machine Learning?
Ming Yin, Jennifer Wortman Vaughan, and Hanna Wallach
The 3rd ICML Workshop on Human Interpretability in Machine Learning (WHI), Stockholm, Sweden, July 2018.
Running Out of Time: The Impact and Value of Flexibility in On-Demand Crowdwork
Ming Yin, Siddharth Suri, and Mary L. Gray
The 36th ACM Conference on Human Factors in Computing Systems (CHI), Montreal, Canada, April 2018.
slides
Teaching
Human-Computer Interaction (CS 475)
Instructor, Spring 2025, Spring 2021, Purdue University.
Data Mining (CS 573)
Instructor, Spring 2019, Fall 2019, Fall 2020, Fall 2021, Fall 2023 & Fall 2024, Purdue University.
Human-AI Interaction (CS 592-HAI)
Instructor, Spring 2024, Purdue University.
Introduction to Artificial Intelligence (CS 471)
Instructor, Fall 2022, Purdue University.
Human-Centered Computing (CS 590-HCC)
Instructor, Spring 2020, Purdue University.
Crowdsourcing and Social Computing (CS 590-CSC)
Instructor, Fall 2018, Purdue University.
Intelligent Machines: Reasoning, Actions and Plans (CS 182)
Teaching fellow with Professor Barbara Grosz, Fall 2013 & Fall 2014, Harvard University.
Introduction to Optimization: Models and Methods (AM 121)
Teaching fellow with Professor Yiling Chen, Spring 2013, Harvard University.
Misc
I'm an avid photographer. Check out some of my pictures here.