Description:
For more than 15 years, Milind Tambe’s team has been focused on AI for social impact, deploying end-to-end systems in areas of public health, conservation and public safety. In this talk Tambe will highlight the results from these 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, he 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, he will highlight results from earlier projects on HIV prevention and others. In terms of conservation, he will highlight efforts for protecting endangered wildlife in national parks around the globe. To address challenges of ML+optimization common to all of these applications, Tambe’s team has advanced 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, the ultimate goal is to facilitate local communities and non-profits to directly benefit from advances in AI tools and techniques.
Guest Speaker Bio:
Milind Tambe is Gordon McKay Professor of Computer Science and Director of Center for Research in Computation and Society at Harvard University; concurrently, he is also Principal Scientist and Director for “AI for Social Good” at Google Research. He is recipient of the IJCAI John McCarthy Award, AAAI Feigenbaum Prize, AAAI Robert S. Engelmore Memorial Lecture Award, AAMAS ACM Autonomous Agents Research Award, INFORMS Wagner prize for excellence in Operations Research practice and MORS Rist Prize. He is a fellow of AAAI and ACM. For his work on AI and public safety, he has received Columbus Fellowship Foundation Homeland security award and commendations and certificates of appreciation from the US Coast Guard, the Federal Air Marshals Service and airport police at the city of Los Angeles.
