I am interested in efficient
methodologies and statistical uncertainty quantification for Monte Carlo computation, predictive
modeling and data-driven optimization. My current
·Monte Carlo methods
·Uncertainty quantification, calibration, data
assimilation for simulation and optimization models
·Data-driven robust and stochastic optimization
·Extremal and rare-event estimation
·Machine learning, particularly risk evaluation of
In the past year I have also been
working with the New York City Fire Department (FDNY) to enhance the 911
patient delivery system in NYC, including the design and launch of an
incident-to-hospital load balancing algorithm to curb hospital overloads in
response to COVID. Some info in Columbia Engineering Magazine
New York Hospital Association.
Supports from the following funding sources are gratefully acknowledged:
·National Security Agency (NSA) Young Investigator
Grant H98230-13-1-0301. Title: “Design of Robust Methodologies for Efficient
Simulation and Sensitivity Analysis for Stochastic Systems”. Duration: Sep
2013-Jun 2014. Role: PI.
·National Science Foundation (NSF) CMMI-1400391/1542020.
Title: “A Sensitivity Approach to Assessing Model Uncertainty for Stochastic
Systems”. Duration: Jul 2014-Jun 2017. Role: PI.
·National Science Foundation (NSF)
CMMI-1436247/1523453. Title: “Collaborative Research: Modeling and Analyzing
Extreme Risks in Insurance and Finance”. Duration: Sep 2014-Aug 2017. Role: PI
(lead-PI: Jose Blanchet, PI: Qihe Tang).
“Data-driven Methods in Simulation Modeling and Optimization for Large-scale
Dynamic Systems”. Duration: Nov 2015-Oct 2017. Role: co-PI (PI: Hyun-Soo Ahn, co-PI: EunshinByon).
·UM Mobility Transformation Center (MTC). Title:
“Development of Evaluation Approaches and the Certificate System for Automated
Vehicles Based on the Accelerated Evaluation”. Duration: May 2016-Dec 2017. Role:
PI (co-PI: David LeBlanc).
·Adobe Faculty Research Award 2016. Title: “Scalable
Dynamic Optimization in Online Marketing Campaigns”. Role: PI.
·National Science Foundation (NSF)
CMMI-1653339/1834710. Title: “CAREER: Optimization-based Quantification of
Statistical Uncertainty in Stochastic and Simulation Analysis”. Duration: May
2017-Apr 2022. Role: PI.
·National Science Foundation (NSF) IIS-1849280.
Title: “Collaborative Research: Unsupervised Rare Event Learning – With
Applications on Autonomous Vehicles”. Duration: Feb 2019-Jan 2022. Role: PI
(lead-PI: Ding Zhao).
·Google and Tides Foundation. Title: “EMS Resource
Deployment Modeling” (with New York City Fire Department). Duration: Jan
2020-Jan 2022. Role: co-PI (PI: Andrew Smyth).
·JPMorgan Chase Faculty Research Award 2020. Title:
“Calibrating Large-Scale Simulation Models via Distributionally
Robust Optimization”. Duration: May 2020-Aug 2021. Role: PI.
·Columbia Urban Technology Pilot Award. Title:
“Optimizing Emergency Response during a Pandemic in Urban Environments”.
Duration: Sep 2020-Sep 2021. Role: co-PI (PI: Andrew Smyth, co-PI: Jay Sethuraman).
·Associate Editor, Operations Research, 2015-
·Associate Editor, INFORMS Journal on Computing, 2016-
·Editorial Board, Stochastic
·Editorial Board, Journal
of Applied Probability / Advances in Applied Probability, 2020-
·Associate Editor, Manufacturing and Service Operations Management, 2021-
·Associate Editor, Operations Research Letters, 2021-
·Alexandrina Goeva (BU
Stat; co-advised with Eric Kolaczyk), graduated 2017.
First position: Post-doc, Broad Institute of MIT and Harvard.
·Clementine Mottet (BU
Stat), graduated 2017. First position: TripAdvisor.
·AmirhosseinMeisami (UM IOE;
co-advised with Mark van Oyen), graduated 2018. First position: Adobe.
·Hospital load balancing: A data-driven approach to
optimize ambulance transports during the COVID-19 pandemic in New York City,
with E. M. Dolan, N. E. Johnson, T. R. Kepler, E. Lelo
de Larrea, S. Mohammadi, A.
Olivier, A. Quayyum, E. Sanabria,
J. Sethuraman, A. W. Smyth and K. S. Thomson.
Finalist, INFORMS Doing
Good with Good OR Competition 2021