I've recently completed my Ph.D. at John A. Paulson School of Engineering and Applied Sciences, Harvard University. Please visit my new homepage here.

During my graduate study at Harvard, I was a member of the EconCS group. I was very fortunate to be advised by Professor Yiling Chen. Before Harvard, I got my bachelor degree in Computer Software from Tsinghua University, Beijing, China. I also visited City University of Hong Kong as an exchange student in my junior year. .

Curriculum Vitae (updated November 2016)

News

I will be joining Purdue University as an Assistant Professor in the Department of Computer Science starting from Fall 2018. Before that, I will be a Postdoctoral Researcher at Microsoft Research New York City.

Research

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. My research broadly connects to the fields of artificial intelligence and applied machine learning, computational social science, human-computer interaction and behavioral economics.

Understanding the Crowd

I empirically examine who the crowd workers are and how they complete crowdwork using online behavioral experiments. These works have contributed to present a quantitative picture of the lives of crowd workers, who:

  • value social interactions (WWW'16)
  • desire more flexibility and autonomy (ongoing work)
  • display significant temporal variations (ongoing work)

Crowdsourcing Incentive Design

I study the problem of how to design incentives in crowdsourcing systems from multiple perspectives:

  • empirically understanding the human behavior in the presence of different incentives (AAAI'13, HCOMP'13, HCOMP'14, CHI'16)
  • quantitatively modeling the patterns in human behavior in reaction to incentives (IJCAI'15, HCOMP'16)
  • designing algorithms and interfaces towards more effective use of crowdsourcing incentives (IJCAI'15, CHI'16)

Online Experimentation for Behavioral Sciences Via Crowdsourcing

I use crowdsourcing platforms as a channel to get access to a large pool of diverse people who are willing to participate in scientific experiments. I conduct online experiments on crowdsourcing platforms to:

  • understand human behavior in various decision-making settings (AAMAS'15)
  • examine how experimenters should conduct and communicate the crowdsourced research in an appropriate way (ongoing work)

Publication

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.
[paper] [slides]

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
[paper]

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.
[paper] [slides]

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.
[paper] [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.
[paper] [slides]

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.
[paper] [slides]

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)
[paper] [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.
[paper] [slides] [poster]

Teaching

Introduction to Optimization: Models and Methods (AM 121)

Teaching fellow with Professor Yiling Chen, Spring 2013, Harvard University.

Intelligent Machines: Reasoning, Actions and Plans (CS 182)

Teaching fellow with Professor Barbara Grosz, Fall 2013 & Fall 2014, Harvard University.

Misc

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