Kenyan PhD student Tanya Leah Akumu has a deeply personal motivation for her data science and AI research – one that may, in the years to come, help improve outcomes for pregnant women and unborn children in rural communities around the world.
Currently, Tanya is collaborating with a technical team in Barcelona while also benefiting from a DDSA Visit Grant in Denmark. Her research focuses on how data science and advanced, digitalised health data – particularly from the Danish healthcare system – can be combined with insights from the Kenyan health system to improve maternal care and support safer births in rural areas globally.
“I know that this project is really needed,” she says.
Her visit to Denmark has been made possible through a collaboration with Professor Aasa Feragen of the Technical University of Denmark. During her three-month stay, Tanya is working closely with Aasa Feragen, as well as with Copenhagen Academy for Medical Education and Simulation (CAMES), and has access to advanced AI resources at the Pioneer Centre for Artificial Intelligence.
The DDSA Visit Grant is part of the DDSA Fellowship Programme, which provides funding for national and international bachelor’s and master’s students, PhD candidates, and postdoctoral researchers to spend time with new research groups in Denmark. The aim is to foster collaboration and lay the groundwork for future PhD or postdoctoral fellowship applications in partnership with Danish universities or research institutions.
The visits are mutually beneficial, according to Aasa Feragen:
“I have hosted several visiting researchers over the years, and we all learn from the experience. It also strengthens collaboration, for example with the university in Barcelona,” she says.
AI to support safer births in rural areas
Returning to Tanya’s project, the need for improved maternal care in rural areas is clear:
“In Kenya, hospitals are few and often located far from rural communities. If a pregnant woman experiences complications, she may hesitate to seek help. When she does, she often turns to local midwives, who may not have access to or training in using equipment such as ultrasound machines,” Tanya explains.
Her team is therefore developing a portable ultrasound device designed for ease of use in low-resource settings:
“If the device performs three vertical and horizontal scans across the abdomen, it can generate data on factors such as gestational age, the baby’s condition, and whether the mother is at risk. This is what we are currently working on. My time in Denmark is providing valuable new knowledge, and the goal is to test the solution in Kenya and eventually bring it to market,” she says.
A deeply personal motivation
Tanya’s academic background includes engineering studies. However, her strongest motivation is personal.
Her mother died when Tanya was just ten years old. Living in a rural Kenyan village, her mother was pregnant with her fourth child and passed away due to complications that could likely have been treated if identified earlier.
“I want to help pregnant women around the world. While this project initially focuses on rural areas in developing countries, I hope that the knowledge we generate can be expanded and provide valuable insights on a global scale,” Tanya says.