|
Research
My research interests are in responsible analytics and AI and data-driven optimization under uncertainty,
with applications in global supply chain management, FinTech, and healthcare.
Broadly speaking, my work has two main threads. The first is methodological:
building better tools – tools that are more efficient, fair, robust, or transparent – for decision-making.
The second is more applied: pairing data analytics and AI with incentives and contracts to address complex value
chain problems, with the overaching goal of improving efficiency while advancing equity and broader social and environmental goals.
|
Key areas of interest
Methodology: Methodological: optimization under uncertainty (robust optimization, data-driven optimization), fairness in analytics and AI
Application areas: global supply chain management (commodity supply chains, food systems),
FinTech (supply chain financing, asset management, risk management),
healthcare (chronic disease management, public policy)
The word cloud on the left, created from some of my papers’ abstracts, gives you perhaps the best five-second snapshot of what it is that I do…
|
Under Review
Journal Publications
“Climate Impacts of Digital Use Supply Chains” with L. Shi, A. Brandt, K. Mach, C. Field, M-J Cho, S. Chey, N. Ram, T. Robinson, B. Reeves, [ Environmental Research : Climate, vol. 3, 2024. ]
Other Publications
Peer-Reviewed Conference Papers (Selection)
Working Papers and Active Research
“An Operational View into Improving Farmer Welfare and Reducing Child Labor in Commodity Supply Chains,” with A. Calmon, A. Gernert, D.A. Iancu, L. Van Wassenhove.
“Inventory for Impact: Scalable Inventory Routing for Clean Cooking Access in Developing Economies,” with S. Camelo, M. Schiffer, S. Thoma.
“AI Solutions for Incentivizing Sustainable Protein Choices in Diets,” with A. Desir, D. A. Iancu, F. Vizzoto.
“The Price of Funding Inflexibility in Humanitarian Operations,” with T. Breugem, E. Gürserliler, L. N. Van Wassenhove.
Theses
|