Students

Learn more about Professor Bertsimas' current and past students.

Student News

My doctoral student Cynthia graduated today. Cynthia has done pioneering work on multimodal machine learning for the climate. Very proud of her! Starting in September she will be an assistant professor in New York university Abudhabi.

Kimberly Villalobos Carballo

Kim defended her doctoral thesis today. She is going to New York university as an assistant professor. Congratulations Kim! very proud of you!

Leonard Boussioux

My doctoral student Léonard Boussioux successfully defended his Ph.D. thesis at MIT today presenting his pioneering work on combining multimodal AI and Optimization. Very proud of you! With the committee members my colleagues Alexandre Jacquillat and Patrick Jaillet. Leonard is joining the Foster School of Business at the University of Washington, Seattle as an assistant professor. Congratulations Leonard!

Current Students

Graduated PhD Students

Adam Cheol Woo Kim

Predictive and Prescriptive Trees for Optimization and Control Problems, 2024

Multimodal Machine Learning for Climate Adaptation, 2024

Kimberly Villalobos Carballo

Integrating Optimization and Modern Machine Learning: Theory, Computation, and Healthcare Applications, 2024

Nicholas Johnson

Advances in Sparse and Low Rank Matrix Optimization for Machine Learning Applications, 2024

Suleeporn Sujichantararat

A Simulated Annealing Approach to Designing Optimal Decision Trees for Classification, Prescriptive, and Survival Analysis, 2023

Leonard Boussioux

Multimodality: Models, Algorithms, and Applications, 2023

Optimal Decision Making for Healthcare Operations: Models and Implementation, 2023

Vassilis Digalakis

Analytics under Variability, Volume, and Velocity with Applications to Sustainability and Healthcare, 2023

Global and Robust Optimization for Engineering Design, 2022

Driss Lahlou Kitane

Sparsity and Machine Learning, Theory and Applications, 2022

Data-driven Healthcare via Constraint Learning and Analytics, 2022

Stable Machine Learning, 2022

Algorithms for Large-scale Data Analytics and Applications to the COVID-19 Pandemic, 2022 (Finalist Edelman competition, 2022)

Ryan Cory-Wright

Integer and Matrix Optimization: A Nonlinear Approach, 2022 (1st Prize in Nicholson competition of INFORMS, 2020, best paper award among ORC students in 2020, 1st prize in student paper for INFORMS Computer Science Section, 2019

Ted Papalexopoulos

Multi-Objective Optimization for Public Policy, 2022

Agni Orfanoudaki

Novel Machine Learning Algorithms for Personalized Medicine and Insurance, 2021

Optimizing School Operations, 2021 (best paper award among ORC students in 2018)

Improving Efficiency and Fairness in Machine Learning: a Discrete Optimization Approach, 2021

Matthew Sobiesk

Machine Learning Algorithms and Applications in Health Care, 2021

Essays on Decision Making Under Uncertainty, 2021

Dynamic Optimization in the Age of Big Data, 2020 (2nd prize in Nicholson competition of INFORMS, 2017, best paper award among ORC students in 2019)

Algorithmic advancements in discrete optimization Applications to machine learning and healthcare operations, 2020 (1st Prize in Nicholson competition of INFORMS, 2020, best paper award among ORC students in 2020, 1st prize in student paper for INFORMS Computer Science Section, 2019, Honorable mention George Dantzig dissertation award 2020)

From Data to Decisions in Urban Transit and Logistics, 2020

Interpretable Machine Learning Methods with Applications to Health Care, 2020

Data-Driven Dynamic Optimization with Auxiliary Covariates, 2019

Colin Pawlowski

Machine Learning for Problems with Missing and Uncertain Data with Applications to Personalized Medicine, 2019

Nishanth Mundru

Predictive and Prescriptive Methods in Operations Research and Machine Learning: An Optimization Approach, 2019

Sebastien Martin

The Edge of Large-Scale Optimization in Transportation and Machine Learning, 2019 (best paper award among ORC students in 2018, George Dantzig dissertation award 2019, Transportation Thesis Prize, 2019)

Advances in Data-Driven Models for Transportation, 2019

Daisy Ying Zhuo

New Algorithms in Machine Learning with Applications in Personalized Medicine, 2018

Frans de Ruiter

Primal and dual approaches to adjustable robust optimization, 2018 (1st prize in Optimization for 2017 best student paper)

Optimal Trees for Prediction and Prescription, 2018 (best paper award among ORC students in 2016)

Integrated Robust and Adaptive Methods in the Heating Oil Industry, 2018

Martin Copenhaver

Sparsity and robustness in modern statistical estimation, 2018 (best paper award among ORC students in 2015)

From Data to Decisions in Healthcare: An Optimization Perspective, 2017

An Analytics Approach to Problems in Health Care, 2017

A Robust Optimization Approach to Online Problems, 2017

Advances in Robust and Adaptive Optimization: Algorithms, Software, and Insights, 2016 (best paper award among ORC students in 2016)

Data, Models and Decisions in Large-Scale Stochastic Optimization Problems, 2016

Regression under a modern optimization lens, 2015

John Silberholz

Analytics for Improved Cancer Screening and Treatment, (winner of the William Pierskalla award in 2013 for best paper in Health care), 2015

Stochastic Analysis via Robust Optimization, (best paper award among ORC students in 2012, finalist in the Nicholson competition in 2012), 2015

From data to decisions through new interfaces between optimization and statistics (best paper award among ORC students in 2013, finalist in the Nicholson competition in 2013), 2015

Data-driven models for uncertainty and behavior (best paper award among ORC students in 2013, finalist in the Nicholson competition in 2013), 2014

Personalized diabetes management, 2013 (winner of the William Pierskalla award in 2013 for best paper in Health care)

Chaithanya Bandi

Tractable stochastic analysis in high dimensions: a robust optimization approach, 2013 (best paper award among ORC students in 2012, finalist in the Nicholson competition in 2012)

Matthew Fontana

Optimal routes for electric vehicles facing uncertainty, congestion and energy constraints, 2013

Integer optimization methods for machine learning, 2012

Michael Frankovich

Air traffic flow management at airports: A unified optimization approach, 2012

A tractable optimization framework for air traffic flow management addressing fairness, collaboration and stochasticity. 2012

Decomposition methods for large scale stochastic and robust optimization problems, 2011

Applications of robust optimization to queueing and inventory systems, 2011

Nikolaos Trichakis

Fairness in operations: from theory to practice, 2011 (winner of the second prize of George Dantzig Best thesis award, 2011)

Advances in power systems: robustness, adaptability and fairness, 2011

Multi-stage adjustable robust optimization, with applications in inventory and revenue management, 2010 ( rst prize in student paper competition in Optimization Section of INFORMS, 2009)

Apostolos Fertis

A robust optimization approach to statistical estimation problems, 2009

Optimization under moment, robust, and data-driven models of uncertainty, 2009

David Czerwinski

Assessing quality of health care, 2008

Dmitriy Katz-Rogozhnikov

Algorithmic issues in queueing systems and combinatorial counting problems, 2008

Margret Bjarnadottir

A data driven approach to health care: applications using claims data, 2008

Analysis of employee stock options and guaranteed withdrawal benefits for life, 2008 ( rst prize in student paper competition in Financial Services Section of INFORMS, 2007)

Nonconvex robust optimization, 2007

Constantine Caramanis

Adaptive optimization, 2006

Risk and robust optimization, 2006 (2nd prize in Nicholson competition of INFORMS, 2005)

Michele Aghassi

Robust Optimization, game theory and variational inequalities, 2005

A robust optimization approach to supply chains and revenue management, (first prize in Nicholson competition of INFORMS, 2003), 2004

Karthik Natarajan

Probabilistic Combinatorial Optimization: Moments, Semide nite Programming and Asymptotic Bounds, (Honorable mention in Nicholson competition of INFORMS, 2003), Singapore-MIT-Alliance, 2004

Robust optimization, 2004 (2nd prize in Nicholson competition of INFORMS, 2002 and 2nd prize in Nicholson competition of INFORMS, 2004), 2004

Adaptive and dynamic models in marketing, 2003

A Lagrangean decomposition method for dynamic optimization and its applications, 2003

Natasha Busheva

Finance without price dynamics, 2003

An Integer programming approach to data mining, 2003

Pricing and revenue management in a network environment, 2003 (2nd prize in Nicholson competition of INFORMS, 2003)

Dessi Pachamanova

A robust optimization approach to nance, 2002

Approximate dynamic programming for integer programming problems, 2000

A stochastic control approach for multiclass queueing networks, 1999 (honorable mention in Nicholson competition of INFORMS, 2000)

The bottleneck phenomenon in transportation systems, 1999

Applications of optimization in probability, nance and revenue management, 1999, (honorable mention in Nicholson competition of INFORMS, 1999)

Thalia Chryssikou

Multiperiod portfolio optimization in the presence of transaction costs, 1998

Stability and performance of multiclass queueing networks, 1997

Stochastic and dynamic models for air traffic flow management, 1997 (1st prize in Transportation Dissertation of INFORMS, 1997, 2nd prize in Dantzig award, 1997)

Constructing approximation algorithms via linear programming relaxations: primal dual and randomized rounding techniques, 1996 (honorable mention in Nicholson competition of INFORMS, 1996)

Ioannis Paschalidis

Large deviations in high speed communication networks, 1996 (2nd prize in Nicholson competition of INFORMS, 1997)

Continuous linear programming: Theory, algorithms and applications, 1995

Gina Mourtzinou

An axiomatic approach to queueing systems, 1995 (2nd prize in Nicholson competition of INFORMS, 1996)

A market approach to air traffic control, 1995

Optimal resource allocation in a dynamic and stochastic environment: a mathematical programming approach, 1995

Optimization of queueing networks: a linear control approach, 1995

Optimal policies for stochastic and dynamic vehicle routing problems, 1994

Dynamic and network e ects in airline yield management, 1994

Carolyn Haibt-Norton

Topics in discrete optimization, 1993

Michael Peterson

Transient congestion phenomena in air transportation, 1992

Ground holding strategies for a network of airports in air tra c control, 1992 (2nd prize in Transportation dissertation competition, 1992)

Garrett van Ryzin

Dynamic vehicle routing problems, 1991 (2nd prize in Transportation dissertation competition of INFORMS, 1992, honorable mention in Nicholson competition of INFORMS, 1991)

Daisuke Nakazato

Transient distributional results in queues with applications to queueing networks, 1990

Probabilistic and worst case analysis of LP relaxations for a class of connectivity problems, 1990 (Tucker prize of Mathematical Programming Society, 1991, 2nd prize in Nicholson competition of INFORMS, 1991)

Graduated Postdoctoral Students

Bartolomeo Stellato

John Silberholrz

Angelos Georghiou

Ebrahim Nasrabadi

Christopher Maes

Eugene Perevalov

Graduated Masters Students

Prescriptive Methods for Adaptive Learning, 2020

School Choice: A Discrete Optimization Approach, 2020

Supply chain network strategy for consumer medical device introduction, 2016

Zachary Sanders

Multi-target tracking via mixed integer optimization, 2016

Kevin Rossillion

Optimized Air Asset Scheduling Within a Joint Air Operations Center, 2015

Christina Epstein

An Analytics Approach to Hypertension Treatment, 2014

Jonathan Paynter

Optimized Border Interdiction, 2014

Nicholas Jernigan

Robust Multi-modal, Multi-period, Multi-commodity Transportation: Models and Algorithms, 2014

Addressing the Fog of War in Reconnaissance Operations: A Robust Optimization Approach, 2013

Dynamic planning for underwater unmanned vehicles, 2013

An Analytics Approach to Designing Clinical Trials for Cancer”, 2013 (winner of the William Pierskalla award in 2013 for best paper in Health care)

Computational experiments for local search algorithms for binary and mixed integer optimization, 2010

Patterns of heart attacks, 2010

Polynomial policies in supply chain networks, 2010

Thai Dung Nguyen

Application of robust and inverse optimization in transportation, 2010

Van Vinh Nguyen

Fairness and optimality in trading, 2010

Robust option pricing - an epsilon arbitrage approach, 2009

Optimizing the operations of the emergency department at the Beth Israel Hospital via simulation, 2008

Robust optimization applications, 2008

A robust optimization approach to network equilibrium, 2007

Optimal bounds for American options, 2006

A robust optimization approach to optimization of queueing networks, 2006

Cheong Foong Soon

Hedging Strategy and Effect of Transaction Costs for American Options in an Incomplete Market, Singapore-MIT-Alliance, 2002

Constantine Caramanis

Bounds on linear partial differential equations via semidefinite optimization, 2001

A discrete optimization approach to classification, Singapore-MIT-Alliance, 2001

Pricing in a competitive environment: a learning approach, 2000

Constantine Tsiligakis

Portfolio construction through mixed integer programming, 1999

Supply chain management: an approximate dynamic programming approach, 1998

Multiperiod portfolio optimization: Feynmann diagrams and approximate dynamic programming, 1998

Stochastic inventory and distribution problems, 1993

Ioannis Paschalidis

Bounds for multiclass queueing networks, 1992

Optimal cash allocation in bank branches, 1991

Algorithms for the 0-1 integer programming problem, 1991

A computational approach to probabilistic routing problems, 1989