Doctoral Alumni

Doctoral Alumni in Academic Placements

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Ashley Datta

Visiting Lecturer

Email: pd2511@columbia.edu
Doctoral Alumni, Doctoral Alumni in Academic Placements
Year Entered Ph.D. Program: Fall 2016
PhD in Statistics 2023
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Assistant Professor of Econometrics and Statistics, University of Chicago’s Booth School of Business

Nabaran Deb

Assistant Professor of Econometrics and Statistics, University of Chicago’s Booth School of Business

Doctoral Alumni, Doctoral Alumni in Academic Placements
https://nabarund.github.io/
PhD in Statistics 2022
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Assistant Professor, University of Wisconsin-Madison

Rishabh Dudeja

Assistant Professor, University of Wisconsin-Madison

Doctoral Alumni, Doctoral Alumni in Academic Placements
https://stat.wisc.edu/staff/dudeja-rishabh/
PhD in Statistics 2021
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Assistant Professor, School of Engineering and Applied Science, Princeton University

Adji Bousso Dieng

Assistant Professor, School of Engineering and Applied Science, Princeton University

Doctoral Alumni, Doctoral Alumni in Academic Placements
https://www.cs.princeton.edu/people/profile/ad6725
PhD in Statistics 2020

Career Highlights:

  • Generative modeling branch of machine learning expert
  • The first Black female faculty member in the history of SEAS and the first Black faculty member ever in the Department of Computer Science (COS) at Princeton University
  • AI Researcher at Google Brain

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Senior Lecturer, Department of Industrial Engineering & Operations Research in Columbia Engineering, Columbia University

Christopher Dolan

Senior Lecturer, Department of Industrial Engineering & Operations Research in Columbia Engineering, Columbia University

Doctoral Alumni, Doctoral Alumni in Academic Placements
PhD in Statistics 2018
Website
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Doctoral Alumni in Industry Placements

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Principal Data Scientist, Code for America

Vincent Dorie

Principal Data Scientist, Code for America

Doctoral Alumni, Doctoral Alumni in Industry Placements
PhD in Statistics 2014

Developer of statistics software with an emphasis on Bayesian nonparametrics, causal inference, and mixed models.

Focused on not-for-profit work and using data for the public good.


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