Associate Professor of Statistics
Adjunct Associate Professor of Computer Science
Indiana University, Bloomington

Myles Brand Hall E210C
Bloomington, IN 47405


Daniel McDonald is Associate Professor of Statistics and Adjunct Associate Professor of Computer Science at Indiana University, Bloomington. His research interests involve the estimation and quantification of prediction risk, especially developing methods for evaluating the predictive abilities of complex dependent data. This includes the application of statistical learning techniques to time series prediction problems in the context of economic forcasting, as well as investigations of cross-validation and the bootstrap for risk estimation.

Daniel did his undergraduate studies at Indiana University where he received two bachelors degrees: a Bachelor of Science in Music with a concentration in cello performance from the Jacobs School of Music and a Bachelor of Arts in economics and mathematics. Prior to graduate school, he worked as a Research Associate at the Federal Reserve Bank of St. Louis. He received his Ph.D. from Carnegie Mellon University in statistics where he was named graduate student of the year for 2012 and received the Umesh Gavasakar Memorial Thesis Award for his dissertation “Generalization Error Bounds for State Space Models.” In 2017, he was a recipient of the Indiana University Trustees Teaching Award. In 2018, he received an NSF CAREER award. His work has also been supported by grants from the Institute for New Economic Thinking.

Recent news

2019 November

Talk on Chopin’s Mazurka Op. 68 No. 3 at Simon Fraser University. Slides are viewable here.

2019 August

I gave an interview to Prof. Bruce Solomon for the IU Mathematics Alumni Newsletter.

2019 August

At JSM 2019, I agreed to play basketball with Rob and Ryan Tibshirani and Dave Zhao. Dave tried valiantly to make up for my lack of skills, but our team was no match for the Tibshiranis. We did make the cover of the 2019 October issue of AMSTATNEWS.

2019 July

Manuscript on “Compressed and penalized linear regression” accepted at JCGS.

2019 May

Lei Ding successfully defended her dissertation proposal.

2019 May

I gave a talk on Trend Filtering at the TTIC/UChicago CS Machine Learning Seminar.

2019 May

Preprint of my project on Musical expression with switching Kalman filters is available.

Daniel J. McDonald © 2019. All rights reserved.

Powered by Hydejack v8.5.1