RESEARCH
PROJECT STREAMS
Unmasking Sex Trafficking Supply Chains
In collaboration with the TellFinder Alliance, we have been exploring novel active learning approaches for uncovering trafficking risk in commercial sex supply chains using data from the deep web. Mapping deceptive recruitment to sex-sales allows for new views into risky geographical corridors that can be used to inform interventions, coordination strategies, and investigations. Learn more here.
Analyzing Responsible Sourcing Strategies
We investigate the spillover effects from ethical certification programs (e.g. Fair Trade) into companies' non-certified supply chains. We connect 6 different structured and unstructured datasets for a unique view of coffee supply chains. We find that companies certifying as low as 3% of their portfolios experience positive spillovers in the rest of their supply chain.
Responsible AI
In collaboration with PricewaterhouseCoopers, we are designing a set of tools, games, and training content on key concepts related to responsible AI. We are working towards evaluating how these different tools impact ethical decision making through behavioral experiments with practitioners. Our goal is to find effective, practical methods for instilling ethical concepts in the daily processes of an organization.
WORKING PAPERS & PUBLICATIONS
Ramchandani, P., Bastani, H., and Wyatt, E. Unmasking recruitment in sex trafficking supply chains with machine learning
Major Revision, M&SOM
1st Place, MSOM Student Paper Competition (2022)
1st Place, Service Science Best Student Paper Award (2021)
2nd Place, POMS Sustainable OM Student Paper Award (2022)
Finalist, Public Sector in OR Best Paper Award (2021)
People’s Choice Award, Early Career Sustainable OM Workshop (2022)
Ramchandani, P., Bastani, H., and Moon, K. Responsible Sourcing: The First Step Is the Hardest
R&R Management Science
People’s Choice Award, Early Career Sustainable OM Workshop (2020)
Ramchandani, P. and Bastani, H. “Multi-modal Active Learning for Network Discovery.”