2020 LSA Collegiate Fellow (Statistics)
Starting at the University of Michigan in Fall 2021.
Yixin Wang works in the fields of Bayesian statistics, machine learning, and causal inference. Her research interests lie in the intersection of theory and applications. She completed her PhD in statistics at Columbia working with David Blei and her undergraduate in mathematics and computer science at the Hong Kong University of Science and Technology.
One thread of Dr. Wang's research is designing fair machine learning algorithms that automate decision-making while reliably repairing historical discriminations. In addition to theoretical correctness, machine learning algorithms are often required to be fair in order to be deployed in practice. To this end, she is designing algorithms that operationalize equal opportunity and affirmative action in college admissions and loan decisions using counterfactual predictions.
Her research centers around developing practical and trustworthy machine learning algorithms for large datasets that can enhance scientific understandings and inform daily decision-making.
Research Area Keyword(s):
Bayesian statistics, machine learning, causal inference