Published: June 10, 2022
As the host of this podcast, I am in a unique position to hear first-hand from people who are having an incredible impact on the world in such an amazing variety of ways, which in my role, I then have the pleasure of sharing with our listeners. While each episode of the podcast communicates an important discovery or significant impact, it’s seemed like a number of recent episodes, at least in my eyes and ears, have captured stories of the impact of O.R. and analytics that regardless of whether you have a background in these fields, are pretty inspiring.
From reducing poaching to help revitalize populations of wild tigers, to helping teach AI to think more like we do, to helping craft better policies to protect and better serve some of our most vulnerable dialysis patients, to interviews featuring the 2022 Franz Edelman Award finalist teams, these episodes have shared stories of brining together skilled people from a variety of fields, organizations and backgrounds to collaborate on addressing significant problems across the globe.
And I’m excited to share that today’s episode, is no exception. Joining me is Ayan Mukhopadhyay, a research scientist with Vanderbilt University and one of the recipients of the 2021 Google AI for Social Good Impact Scholar Award. Ayan is involved in a number of projects that are having a significant positive impact on the world around us, but today we’ll be talking in particular about his work with HelpMum, a non-profit organization based in Nigeria dedicated to improving the lives of African mothers and children.
Even when families do know about the importance of immunization, they often times lack money to travel to health clinics. So more than 50% of the families we analyzed as part of this project earn less than $25 (U.S.) a month, which makes it really hard for them to spend money on transportation. So as part of this project, together with HelpMum’s advisory board, we designed four interventions to increase immunization uptick.
Interviewed this episode:
Ayan Mukhopadhyay is a research scientist at Vanderbilt University, USA. His research interests include multi-agent systems, robust machine learning, and decision-making under uncertainty. Prior to this, Ayan was a post-doctoral research fellow at the Stanford Intelligent Systems Lab at Stanford University, where he was awarded the 2019 CARS post-doctoral fellowship by the Center of Automotive Research at Stanford (CARS). Before joining Stanford, he was a Ph.D. student at Vanderbilt University’s Computational Economics Research Lab. His thesis was nominated for the Victor Lesser Distinguished Dissertation Award 2020. Ayan is particularly interested in applying artificial intelligence and analytics to real-world problems, especially ones that have societal impacts. His current work focuses on designing decentralized decision-making systems for emergency response, developing resource allocation approaches to increase vaccination uptake, understanding how crowdsourced reports can be used to infer emergency scenarios, optimizing para-transit routing, and trying to understand how to tackle wildfires and heatwaves. He is one of the recipients of the “Google AI for Social Good Impact Scholar” award (2021).
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Contat Ayan Mukhopadhyay at firstname.lastname@example.org.