Professor Krish Seetah receives a HAI (Human Centered Artificial Intelligence) seed grant

Congratulations to Professor Krish Seetah and his team on receiving the HAI (Human-Centered Artificial Intelligence) Seed Grant!

The HAI Seed Grant is awarded to exceptional scholars for their investigation into cutting-edge AI solutions to support or advance humanity, foster interdepartmental or interschool collaborations between faculty, postdocs, students, and staff, and present new, ambitious research that will help guide the future of AI. 

Professor Krish Seetah's project is titled Predicting malaria outbreaks: AI to learn, classify and predict across diverse paleo-demographic, climatic and genomic data.  The project seeks to predict the impact of malaria for the next 50-100yrs by employing evidence from the last 300yrs. Using AI tools to recognize patterns in transmission over time, our approach is the first to access vast, data-rich evidence on climate, land use, and human behavior from historic epidemics, alongside genetic evidence on human demography, and vector and parasite biology. Malaria threatens 3.5 billion people in ~97 countries. 90% of those affected live in Africa and children under five suffer the highest morbidity. Despite billions of dollars spent over decades-long efforts at eradication, prevalence is on the increase as is re-emergence is areas formerly under control. The problem is exacerbated because of resistance to pesticides and drugs, and the lack of a proven vaccine. Malaria will become a greater threat due to global warming, expanding urbanization and agriculture, and increased human mobility,  yet we lack the tools to predict transmission as a function of climatic, land-use and demographic factors.  How do multiple factors interact to exacerbate or mitigate outbreaks? Addressing this question is critical for policy to control malaria. Our models could guide disease prediction, providing evidence to help adjust policy for targeted intervention.

His research team includes Robert Dunbar (Earth System Science), Carlos Bustamante (Biomedical Data Science, Genetics), Giulio De Leo (Biology), Erin Mordecai (Biology), Desiree LaBeaud (Pediatrics - Infectious Diseases), Michelle Barry (CIGH), Bright Zhou (Medicine), David Pickel (Classics), and Hannah Moots (Anthropology).

For more information, please see https://hai.stanford.edu/news/hais-2019-seed-grant-awards.