I am a research assistant professor at the Toyota Technological Institute at Chicago. My research interests lie in statistical machine learning, particularly in developing methodology for evaluation of human (e.g., admissions, grading, hiring, peer review) and algorithms (e.g., A/B testing). I draw inspirations from psychology to build human behavioral models, develop algorithms with theoretical guarantees, conduct crowdsourcing experiments, and implement policy changes that make real-world impacts.

Previously, I was a President’s postdoctoral fellow in the School of Industrial and Systems Engineering (ISyE) and the Algorithms and Randomness Center (ARC) at Georgia Institute of Technology, working with Ashwin Pananjady and Juba Ziani. I received my Ph.D. in the School of Computer Science at Carnegie Mellon University, advised by Nihar Shah. I received my B.S. in Electrical Engineering and Computer Sciences from UC Berkeley.

Email: jingyanw [at] ttic.edu

Room: 427

For students: If you are interested in visiting TTIC and working with me during the summer, please apply to the visiting student program.

Research Overview
The goal of my research is to develop theoretical foundations for principled evaluation paradigms that model, collect, and aggregate human evaluation data. I draw inspirations from psychology to build human behavioral models, develop algorithms with theoretical guarantees, conduct crowdsourcing experiments, and implement policy changes that make real-world impacts. Specifically, I consider two types of evaluation tasks: (1) evaluation of people and human work; (2) evaluation of models and algorithms.
Real-world impacts: I extend my insights from research to real policy improvements in practice. For example, we compile the data and evaluate the gender distribution in award-winning papers in 16 top computer science conferences in the past 10 years, which shows prominent differences across conferences. We also consider the biases caused by alphabetical ordering in scientific publication. Taking cognizance of this bias arising from alphabetical ordering, many institutions (such as the Machine Learning Department at CMU) has randomized the ordering for listing personnel. The debiasing algorithm that I have developed is also currently deployed in practice with grant review agencies.
Preprints
Journal Publications and Under Review
Peer-Reviewed Conference Publications
Teaching
Misc
I play the violin with the Chicago Metropolitan Symphony Orchestra.

During my time in Atlanta, I played with the Atlanta Community Symphony Orchestra. We performed free concerts in the Atlanta metro area.