I build causal models to predict and explain task outcomes, particularly tasks that involve subjective opinions. The models that I build concern three topics: (1) how to aggregate conflicting opinions, (2) decide if more opinions are necessary about the same or different items, and (3) who should we ask for further opinions.
- Theory: Decision Theory, Voting, Utility theory, and Prospect theory.
- Probabilistic Models: Causal Inference, Reinforcement Learning, Multi-Armed Bandits, Bayesian Inference, Markov Models, and Bayesian Optimization.
- Empirical research: Quasi-experimental and Observational studies, Survival analysis, Analysis of covariance, Time series, and Sensitivity analysis.
- Application domains: Crowdsourcing, Software Debugging, Self-Adaptive Systems, and, more recently, Comments from Q&A sites or News sites
- Tools/Languages: R, Python, Java, Scala
I am grateful to have the opportunity to work with many brilliant graduate and undergraduate students in individual and group research projects. Follow some of recent projects that I have coordinated: