Christopher Dolan

LECTURER IN THE DISCIPLINE OF OPERATIONS RESEARCH IN THE DEPARTMENT OF INDUSTRIAL ENGINEERING AND OPERATIONS RESEARCH

822 CEPSR S.W. Mudd
Mail Code: 4704
United States

Tel(212) 851-2132

Research Interests

Causal Inference, Survey Methodology, Machine Learning Fairness

Christopher Dolan joins the IEOR department in 2021 as a Lecturer. He teaches courses in data science, statistics, probability and business analytics. Prior to joining Columbia University, he worked in industry as a data scientist at Google and Hinge, and as a quantitative researcher at Bloomberg L.P. At Google, he helped build machine learning and optimization models that were used to manage global capacity planning for Google Cloud. He received his PhD from Columbia University in Statistics in 2017 and BA from New York University in 2008.

PROFESSIONAL EXPERIENCE

  • Lecturer in Discipline, Department of Industrial Engineering and Operations Research
  • Columbia University, 2021-Present
  • Hinge, 2019-2020
  • Bloomberg, LP, 2018-2019
  • Google, 2017-2018

SELECTED PUBLICATIONS

  • Dolan, C., Blanchet, J., Iyengar, G. & Lall, U. A model robust real options valuation methodology incorporating climate risk. Resources Policy 57, 81–87 (2018).
  • Blanchet, J., Dolan, C. & Lam, H. Robust rare-event performance analysis with natural non-convex constraints. in Proceedings - Winter Simulation Conference 2015-January, 595–603 (Institute of Electrical and Electronics Engineers Inc., 2015).