How can data‑driven optimization models be adapted to the changing needs of decision makers?
Daria Terekhov
 Associate Professor
 Department of Mechanical, Industrial and Aerospace Engineering
 dynamic scheduling4
 scheduling8
 inverse optimization
 optimization10
 operations research17
 queueing theory2
 healthcare operations management4
 constraint programming
 linear programming3
 integer programming4
 algorithm design28
 cost estimation2
 combinatorial optimization6
 hybrid algorithms
 stochastic analysis13
 regression estimation2
 math education7
 engineering education12

Vašek Chvátal
discrete mathematics, betweenness, brain functions

Denis Pankratov
theoretical computer science, algorithm design, analysis of algorithms

Brigitte Jaumard
autonomic networking, graph theory, operations research

Hossein Hashemi Doulabi
healthcare optimization, stochastic optimization, integer programming

Ivan Contreras
transportation systems, networks, large scale optimization

Ali Akgunduz
aviation industry, air traffic control, greener aviation

Farnoosh Naderkhani
conditionbased maintenance, stochastic analysis, quality management

Dongyu Qiu
networks, network performance evaluation, wireless networks

Chun Wang
distributed/parallel systems, esupply chains, scheduling

Mingyuan Chen
operations research, industry 4.0, remanufacturing

Onur Kuzgunkaya
supply chains, reconfigurable manufacturing, risk management

Masoumeh KazemiZanjani
operations research, optimization under uncertainty, supply chains

Nadia Bhuiyan
aviation industry, product development, operations research

Jia Yuan Yu
data science, decision theory, machine learning

Ali Nazemi
water security, climate change, coupled humanwater systems

Andrew Delong
machine learning, deep learning, genomics