Nigerian-born researcher Jane Odum wins $30,000 in Google-sponsored contest
A Nigerian-born researcher and doctoral candidate from the University of Georgia’s Franklin College of Arts and Sciences, Jane Odum has developed a mobile-first artificial intelligence platform to improve disease surveillance
A Nigerian-born researcher and doctoral candidate from the University of Georgia’s Franklin College of Arts and Sciences, Jane Odum has developed a mobile-first artificial intelligence platform to improve disease surveillance in low-resource settings.
Odum’s tool, called EpiCast, earned first place and $30,000 in a Google-sponsored MedGemma Impact Challenge.
According to UGA Media Relations, the competition invites developers to build human-centered AI applications that tackle complex health care problems. More than 850 teams entered the competition.
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Born and raised in Nigeria, memories of two outbreaks, Ebola and COVID-19, came back to Odum when the MedGemma Impact Challenge was announced.
She wanted to build a tool that would help community health workers speak in their own native languages while also monitoring symptoms across their regions.
EpiCast lets community health workers describe patient symptoms in their own language; the system then converts this input into structured clinical data aligned with global health standards.
It identifies likely symptoms, assigns severity levels, and maps cases to standardized diagnostic codes within seconds. The result is a tool that connects informal clinical observations with formal surveillance systems, supporting earlier detection of outbreaks and faster public health response.
“Waiting even small amounts of time per patient can disrupt workflow in a busy clinic,” Odum said. “If the system is not fast and reliable, it will not be used.”
Unlike many traditional AI systems that rely on cloud computing, EpiCast runs directly on a mobile device. Odum optimized advanced medical language models to function offline, reducing processing time from minutes to seconds and removing the need for reliable internet connectivity.
“Early detection is everything in outbreak response. If we can capture signals at the community level in real-time, we can change the course of an epidemic.” Odum said.
