Professor Chih-Ling Tsai Elected as AAAS Fellow

Award Recognizes Contributions to Innovation, Education and Scientific Leadership

Distinguished Professor Chih-Ling Tsai, holder of the Robert W. Glock Endowed Chair in Management, with Miriam Glock, who established the chair.

A pioneering expert in applying statistics in business and the sciences, Professor Chih-Ling Tsai has been elected as a fellow by the American Association for the Advancement of Science, crediting his contributions to statistical theory and application.

Founded in 1848, the AAAS is the world’s largest general scientific society. It honored its 347 new fellows at the AAAS annual meeting held in February in Washington, D.C., acknowledging their scientifically or socially distinguished efforts to advance science or its applications.

Tsai joined three other UC Davis faculty named AAAS fellows this year: Peter A. Barry, Xi Chen and Jan W. Hopmans.

A post on the School’s Facebook page about Tsai’s AAAS fellowship drew many congratulatory replies and likes. “I am grateful for your warm comments,” Tsai wrote back. “Without the consistent and strong support from Deans, colleagues, staffs, students, and alumni, I do not think that I have a chance to be elected as a fellow of AAAS. I deeply appreciate everyone and will keep on giving it my best shot.”

“Without the consistent and strong support from Deans, colleagues, staffs, students, and alumni, I do not think that I have a chance to be elected as a fellow of AAAS. I deeply appreciate everyone and will keep on giving it my best shot.”

Tsai holds the Robert W. Glock Endowed Chair in Management, and UC Davis MBA students have named him teacher of the year several times. He also is a fellow of the American Statistical Association.

UC Davis has honored Tsai with the title of Distinguished Professor, the highest campus-level professional faculty title.

Tsai’s research fields includes regression analysis, model selection, high-dimensional data, time series and biostatistics, and he has published more than 100 papers during his career.

His current work is in the extremely competitive field of high dimensional data analysis, in particular when the number of variables in a dataset is greater than the sample size. Where typical statistical methods become less effective with a higher number of variables, Tsai’s methods can effectively identify the most important information in a dataset with a large number of variables.

The statistical model Tsai helped develop can be applied to many fields, including business, biological science, computer science and social science.



Leave a Reply