Integrating ML+Optimization: Driving Social Impact in public health and conservation

For more than 15 years, my team and I have been focused on AI for social impact, deploying end-to-end systems in areas of public health, conservation and public safety. In this talk, I will highlight the results from our deployments for social impact in public health and conservation, as well as required innovations in integrating machine learning and optimization. First in terms of public health, I will present recent results from our work in India with the world’s two largest mobile health programs for maternal and child care that have served millions of beneficiaries. Additionally, I will highlight results from earlier projects on HIV prevention and others. In terms of conservation, I will highlight efforts for protecting endangered wildlife in national parks around the globe. To address challenges of ML+optimizaton common to all of these applications, we have advanced the state of the art in decision focused learning, restless multi-armed bandits, influence maximization in social networks and green security games. In pushing this research agenda, our ultimate goal is to facilitate local communities and non-profits to directly benefit from advances in AI tools and techniques.