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.


In most cases, my collaborators and I choose to have students as first authors and then determine the authorship alphabetically.

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, Ming Yin.
The Web Conference (WWW), Taipei, April 2020. (Forthcoming)

Understanding the Skill Provision in Gig Economy from a Network Perspective: A Case Study of Fiverr

Keman Huang, Jinhui Yao, 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, 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, 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.

Peeking into the On-Demand Economy: Crowd Behavior and Incentive Design

Ming Yin.
Ph.D. Dissertation, School of Engineering and Applied Sciences, Harvard University, June 2017.

Predicting Crowd Work Quality under Monetary Interventions

Ming Yin and Yiling Chen.
The 4th AAAI Conference on Human Computation and Crowdsourcing (HCOMP), Austin, TX, October 30 - November 3, 2016.
slides · dataset

Curiosity Killed the Cat, but Makes Crowdwork Better

Edith Law, Ming Yin, Joslin Goh, Kevin Chen, Michael Terry and Krzysztof Z. Gajos.
The 34th ACM Conference on Human Factors in Computing Systems (CHI), San Jose, CA, May 2016.
Best Paper Honorable Mention

The Communication Network Within the Crowd

Ming Yin, Mary L. Gray, Siddharth Suri and Jennifer Wortman Vaughan.
The 25th International World Wide Web Conference (WWW), Montreal, Canada, April 2016.
slides · dataset

Bonus or Not? Learn to Reward in Crowdsourcing

Ming Yin and Yiling Chen.
The 24th International Joint Conference on Artificial Intelligence (IJCAI), Buenos Aires, Argentina, July 2015.
slides · poster

Human Behavior Models for Virtual Agents in Repeated Decision Making under Uncertainty

Ming Yin and Yu-An Sun.
The 14th International Conference on Autonomous Agents & Multiagent Systems (AAMAS), Istanbul, Turkey, May 2015.

Monetary Interventions in Crowdsourcing Task Switching

Ming Yin, Yiling Chen and Yu-An Sun.
The 2nd AAAI Conference on Human Computation and Crowdsourcing (HCOMP), Pittsburgh, PA, November 2014.

Task Sequence Design: Evidence on Price and Difficulty

Ming Yin, Yiling Chen and Yu-An Sun.
The 1st AAAI Conference on Human Computation and Crowdsourcing (HCOMP), Palm Springs, CA, November 2013. (Work in Progress track)
slides · poster

The Effects of Performance-Contingent Financial Incentives in Online Labor Markets

Ming Yin, Yiling Chen and Yu-An Sun.
The 27th Conference on Artificial Intelligence (AAAI), Bellevue, WA, July 2013.
slides · poster


Human-Centered Computing (CS 590-HCC)

Instructor, Spring 2020, Purdue University.

Data Mining (CS 573)

Instructor, Spring 2019 & Fall 2019, 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.


I'm an avid photographer. Check out some of my pictures here.