Operations, Information & Technology

Our focus in the operations, information, and technology area is on the management of systems, processes, and networks.

Examples include health care systems, product design and manufacturing processes, supply networks, information systems, energy and environmental systems, homeland security systems, and social networks. We employ methods from the fields of operations research, game theory, econometrics, computer science, probability and statistics, and exploit the growing availability of data.

Recent Journal Articles in Operations, Information & Technology

Zhengli Wang, Franklin Dexter, Stefanos Zenios
Journal of Clinical Anesthesia. December
2020, Vol. 67

Study Objective

The coronavirus disease 2019 (COVID-19) pandemic impacts operating room management in regions with high prevalence (e.g., >1.0% of asymptomatic patients testing positive). Cases with aerosol producing procedures are...

Kuang Xu, Yuan Zhong
Operations Research. November
2020, Vol. 68, Issue 6, Pages 1698–1715

We propose a general framework, dubbed stochastic processing under imperfect information, to study the impact of information constraints and memories on dynamic resource allocation. The framework involves a stochastic processing network...

Kuang Xu, Se-Young Yun
Mathematics of Operations Research. November
2020, Vol. 45, Issue 4, Pages 1258–1288

We study the effect of imperfect memory on decision making in the context of a stochastic sequential action-reward problem. An agent chooses a sequence of actions, which generate discrete rewards...

Basak Kalkanci, Erica Plambeck
Manufacturing & Service Operations Management. November
2020, Vol. 22, Issue 6, Pages 1107–1286

Problem definition: Under what conditions and how can a buying firm, by committing to publish a list of its suppliers and/or the identities and violations of terminated suppliers, increase its...

Imke Mayer, Erik Sverdrup, Tobias Gauss, Jean-Denis Moyer, Stefan Wager, Julie Josse
Annals of Applied Statistics. September
2020, Vol. 14, Issue 3, Pages 1409–1431

Missing attributes are ubiquitous in causal inference, as they are in most applied statistical work. In this paper we consider various sets of assumptions under which causal inference is possible...

Faculty in Operations, Information & Technology

Associate Professor
Associate Professor
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Professor (by courtesy)
Associate Professor
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Professor Emeritus
Associate Professor
Professor
Professor
Professor Emeritus
Professor
Professor Emeritus
Professor (by courtesy)
Assistant Professor
Assistant Professor
Assistant Professor
Professor
Associate Professor
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Associate Professor
Professor