I am an Assistant Professor in the Analytics and Operations Group at Imperial College Business School (ICBS) since July 2023, affiliated with the Imperial-X initiative on interdisciplinary AI/ML.
My research focuses on optimization, machine learning, statistics, and their application in business analytics. I am particularly interested in broadening the scope of optimization to address practical problems that current methods cannot solve to optimality. For instance, I have proposed a generalization of integer optimization that tackles rank constraints, which arise in product recommendation applications. Recently, I have worked on formulating the discovery phase of the scientific method as a convex optimization problem. I am also interested in leveraging optimization to support the transition to a low-carbon economy. For instance, we recently collaborated with OCP to develop a framework that guides a two billion USD investment in solar panels and batteries.
I have received an IBM Herman Goldstine Postdoctoral Fellowship (2022-23), the Nicholson Prize (2020), the INFORMS Data Mining Society Student Paper Award (2021), the INFORMS Computing Society Student Paper Award (2019), and the INFORMS Health Applications Society Pierskalla Award (2020). I have also been a finalist in the 2023 M&SOM practice-based research competition.
Before joining ICBS, I spent a year as a postdoctoral fellow at IBM Research (Cambridge, MA). I received my PhD in Operations Research from MIT in 2022, advised by Dimitris Bertsimas. Before joining MIT, I received a BE (1st class Hons) in Engineering Science from the University of Auckland.
R. Cory-Wright and A. Gómez, Submitted
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D. Bertsimas, R. Cory-Wright, S. Lo, and J. Pauphilet, Submitted
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R. Cory-Wright and J. Pauphilet
Major Revision, Operations Research
First place, 2024 INFORMS DMDA Workshop Paper Award (theoretical track)
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D. Bertsimas, R. Cory-Wright, J. Pauphilet, and P. Petridis
INFORMS Journal on Computing, accepted, 2024+
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R. Cory-Wright, C. Cornelio, S. Dash, B. El Khadir, and L. Horesh
Nature Communications, 15, 5922, 2024
Meet AI-Hilbert, a new algorithm for transforming scientific discovery (IBM Research Blogpost)
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D. Bertsimas, R. Cory-Wright, and V. Digalakis Jr.
Manufacturing & Service Operations Management, 2024
Finalist, 2023 Manufacturing & Service Operations Management Practice-Based Research Competition
Honorable Mention, 2023 MIT ORC Student Paper Competition (Digalakis)
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OCP's Green Investment Program
Imperial Business Article
D. Bertsimas, R. Cory-Wright, and N. A. G. Johnson
Journal of Machine Learning Research, 24(267):1-51, 2023
First place, 2021 INFORMS Data Mining Student Paper Award
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D. Bertsimas, R. Cory-Wright, and J. Pauphilet
Mathematical Programming, 202:47-92, 2023
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D. Bertsimas, R. Cory-Wright, and J. Pauphilet
Operations Research, 70(6):3321-3344, 2022
First place, 2020 INFORMS George Nicholson Paper Award
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D. Bertsimas, R. Cory-Wright, and J. Pauphilet
Journal of Machine Learning Research, 23(13):1-35, 2022
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D. Bertsimas and R. Cory-Wright
INFORMS Journal on Computing, 34(3): 1489-1511, 2022
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D. Bertsimas, R. Cory-Wright, and J. Pauphilet
SIAM Journal on Optimization, 31(3):2340-2367, 2021
First place, 2019 INFORMS Computing Society Student Paper Award
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ICS Newsletter
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D. Bertsimas et al.
Health Care Management Science, 24:253-272, 2021
First place, 2020 INFORMS Health Applications Society Pierskalla Paper Award
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NYT
R. Cory-Wright and G. Zakeri
Operations Research Letters, 48(3):376-384, 2020
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D. Bertsimas and R. Cory-Wright
Operations Research Letters, 48(1):78-85, 2020
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R. Cory-Wright, A. Philpott, and G. Zakeri
Operations Research Letters, 46(1):116-121, 2018
First place, 2016 ORSNZ Young Practitioner’s Prize
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R. Cory-Wright. Advised by: D. Bertsimas
Ph.D. Thesis, Massachusetts Institute of Technology, May 2022
MIT Libraries
Five-page Summary
Designed a new class which introduces machine learning in Python
Designed a new class which introduces computational problem-solving through the lens of algorithms and data structures in Python
Designed a new class introducing techniques for decision-making under uncertainty widely used in operations research. Includes stochastic optimization, robust optimization, and dynamic programming Lecture 1 Slides Lecture 2 Slides Lecture 3 Slides
Class which introduces students to theory and applications of linear, discrete, and nonlinear optimization