Wednesday, September 26th, 2018

3:00 p.m.

DeBartolo Hall Room 101

 

Dr. Sekou Lionel Remy

Research Scientist at IBM Research - Africa

 

 Sekou.jpeg - 464.04 kB

Novel Exploration Techniques (NETs) for Malaria Policy Interventions

The task of decision-making under uncertainty is daunting, especially for problems which have significant complexity. Healthcare policy makers across the globe are facing problems under challenging constraints, with limited tools to help them make data driven decisions. In this work we frame the process of finding an optimal malaria policy as a stochastic multi-armed bandit problem, and implement three agent based strategies to explore the policy space. We apply a Gaussian Process regression to the findings of each agent, both for comparison and to account for stochastic results from simulating the spread of malaria in a fixed population. The generated policy spaces are compared with published results to give a direct reference with human expert decisions for the same simulated population. Our novel approach provides a powerful resource for policy makers, and a platform which can be readily extended to capture future more nuanced policy spaces.

About Dr. Remy

Sekou L. Remy is a Research Scientist at IBM Research – Africa. A member of the healthcare team, he is excited about developing appropriate technologies which will transform Africa, and the world. Sekou loves learning, and is trained both in the Liberal Arts and Engineering. An proud alum of the Georgia Institute of Technology, and of Morehouse College (both in Atlanta, GA USA), Sekou has spent time learning and teaching at Clemson University, the University of Notre Dame, Spelman College, and at the University of Washington.