Accepted and Under Review

1.   Interpretable Operations Research for High-Stakes Decisions: Designing the Greek COVID-19 Testing System. with Hamsa Bastani, Kimon Drakopoulos.
Under Review.
[Abstract]   [SSRN]
**Finalist, 2021 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research (Winner to be announced at INFORMS )**

2.   Debiasing In-Sample Policy Performance for Small-Data, Large-Scale Optimization. with Michael Huang and Paat Rusmevichientong.
Under Review.
[Abstract]   [SSRN]   [arXiv:2107.12438]

3.   Efficient and Targeted COVID-19 Border Testing via Reinforcement Learning. with Hamsa Bastani, Kimon Drakopoulos.
Under Review.
[Abstract]   [SSRN]   [Open-Source Code for Algorithm]
**Finalist, 2021 Pierskalla Best Paper Competition (Winner to be announced at INFORMS!)**
**Finalist in the Post-Pandemic Supply-Chain and Healthcare Management Conference's Best Paper Competition**
**Spotlight Presentation at the Reinforcement Learning for Real-Life Workshop (ICML 2021)**

4.   Data-Pooling in Stochastic Optimization. with Nathan Kallus.
Management Science (Published online 27 March 2021) .
[Abstract]   [10.1287/mnsc.2020.3933]   [SSRN]   [Open-Source Code]

5.   The Value of Personalized Pricing. with Adam Elmachtoub and Michael Hamilton.
Management Science (Published online 5 April 2021) .
[Abstract]   [10.1287/mnsc.2020.3821]   [SSRN]   [Open-Source Code]
**Finalist in the 2018 INFORMS Service Science Best Paper Award**
**Accepted in The 15th Conference on Web and Internet Economics (WINE), 2019**

6.   Small-Data, Large-Scale Linear Optimization. with Paat Rusmevichientong.
Management Science (Published online 1 July 2020) .
[Abstract]   [10.1287/mnsc.2019.3554]   [SSRN]   [Open-Source Code]

7.   Maximizing Intervention Effectiveness. with Brian Rongqing Han, Song-Hee Kim, and Hyung Paek.
Management Science (Published online May 2020) .
[Abstract]   [10.1287/mnsc.2019.3537]   [SSRN]
**Finalist in the 2018 Pierskalla Best Paper Award**
**Finalist in the 2018 POMS College of Healthcare and Operations Management (CHOM) Best Paper Competition**

8.   Near-Optimal Bayesian Ambiguity Sets for Distributionally Robust Optimization.
Management Science (Mar. 2019) .
[Abstract]   [10.1287/mnsc.2018.3140]   [Optimization Online]   [Open-Source Code]

9.   Data-Driven Robust Optimization. with Dimitris Bertsimas and Nathan Kallus.
Mathematical Programming (Feb. 2017) .
[Abstract]   [10.1007/s10107-017-1125-8]   [Open-Source Code]
**Finalist in the 2013 George Nicholson Student Paper Prize**

10.   Robust Sample Average Approximation. with Dimitris Bertsimas and Nathan Kallus.
Mathematical Programming (Jun. 2017) .
[Abstract]   [doi:10.1007/s10107-017-1174-z]
**Winner of the 2013 MIT Operations Research Center Best Student Paper Award**

11.   A Comparison of Monte Carlo Tree Search and Mathematical Optimization for Large Scale Dynamic Resource Allocation. with Dimitris Bertsimas, John D. Griffith, Mykel Kochenderfer, Velibor Misic, and Robert Moss.
European Journal of Operations Research (Dec. 2017) .
[Abstract]   [doi:10.1016/j.ejor.2017.05.032]

12.   Data-Driven Estimation in Equilibrium Using Inverse Optimization. with Dimitris Bertsimas and Ioannis Ch. Paschalidis.
Mathematical Programming (Sep. 2014) .
[Abstract]   [doi:10.1007/s10107-014-0819-4]   [arXiv:1308.3397]   [Open-Source Code]

13.   A Course on Advanced Software Tools for Operations Research and Analytics. with Iain Dunning, Angela King, Jerry Kung, Miles Lubin and Jon Silberholz.
INFORMS Transactions on Education (Jan. 2015) .
[Abstract]   [ited.2014.0131]   [Open-Source Code/Materials]

14.   Inverse Optimization: A New Perspective on the Black-Litterman Model. with Dimitris Bertsimas and Ioannis Ch. Paschalidis.
Operations Research (Nov. 2012) .
[Abstract]   [doi:10.1287/opre.1120.1115]