I'm an Assistant Professor in the Department of Computer Science, Purdue University. My primary research interests lie in the interdisciplinary field of social computing and crowdsourcing. I design and conduct large-scale online behavioral experiments to obtain a quantitative perspective on participants' behavior in social computing and crowdsourcing systems. Based on the empirical evidence from the behavioral data, I further work on designing realistic models, novel algorithms and effective interfaces to facilitate the development of more intelligent and sustainable systems. Recently, I become interested in using experimental approach to understand how human interact with and trust machine learning systems. My research broadly connects to the fields of artificial intelligence and applied machine learning, computational social science, human-computer interaction and behavioral economics.

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.


  • I'm looking for talented students to work with me! The best way to reach me is by email. (Prospective students: please mention and explain your interest in my work in your application.)
  • I will be the Doctoral Consortium Co-Chair for HCOMP 2019. Consider applying and stay tuned!
  • I gave a talk on peeking into the on-demand economy at ACM New York City in June 2018.
  • Our work on mapping the communication network among crowd workers has been covered by Nature!


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

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


Data Mining (CS 573)

Instructor, Spring 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.