Sebastián Souyris

Sebastián Souyris

Sebastián Souyris

Assistant Professor of Supply Chain and Analytics
Lally School of Management, Rensselaer Polytechnic Institute (RPI)

My research addresses challenges and the means of achieving environmental and human sustainability, combining data-driven optimization, machine learning, and artificial intelligence. I have developed analytic solutions for sustainability, energy, healthcare, logistics, media, and sports, with work published in Operations Research, Production and Operations Management, the European Journal of Operational Research, and the INFORMS Journal on Applied Analytics.

I am an INFORMS Franz Edelman Laureate, a finalist of the EURO Excellence in Practice Award and of the INFORMS Innovative Applications in Analytics Award, and a prizewinner of the INFORMS Revenue Management and Pricing Practice Award.

Sebastián Souyris

Selected publications

Production and Operations Management2023

Informational value of visual nudges during crises: Improving public health outcomes through social media engagement amid COVID-19

With A. Ivanov, Z. Tacheva, A. Alzaidan and A. C. England. 32, 2400–2419.

https://doi.org/10.1111/poms.13982
European Journal of Operational Research2014

Branch-and-Price and Constraint Programming for Solving a Real-Life Technician Dispatching Problem

With C. E. Cortés, M. Gendreau, L. M. Rousseau and A. Weintraub. 238(1), 300–312.

https://doi.org/10.1016/j.ejor.2014.03.006

All publications.

Current research and working papers

2026FCAT · PI

Closing the retirement-savings gap

Behavioural heterogeneity meets conversational AI: a personalized agent for retirement-savings decisions. Fidelity Center for Applied Technology University Research Award.

2025CRAFT · PI

Drivers of volatility in energy commodity markets

Identifying what moves volatility in energy commodities, with the Center for Research toward Advancing Financial Technologies at Stevens and RPI.

Major revisionM&SOM

Accelerating residential solar adoption

A dynamic structural model of the household adoption decision, used to compare rebate designs. A rebate offered for a limited period generates more adoption than a prolonged, costlier one.