UoN's Institute of Tropical and Infectious Diseases wins USD 5.5 Million grant
On September 13th 2023, Takeda Pharmaceuticals announced five new partnerships to its Global Corporate Social Responsibility (CSR) Program, which contributes to strengthening health systems in low- and middle-income countries. The five awards were given to institutions in five countries globally, of which, University of Nairobi, Kenya emerged as one of the two institutions in Africa to receive this prestigious award. The University of Nairobi was awarded JPY 793 million (Approx. USD 5.5 million) to create a pioneering, public health-focused machine learning and data science training program to strengthen the leadership pipeline and impact of women to improve health in their communities. The program will train and empower 800 underprivileged girls and young women across 6 regions in Kenya. By cultivating a diversified pool of data scientists, it will contribute to reducing biases and gender gaps in public health data and artificial intelligence and create a model for scale across the African continent.
The project, ENabling Girls in AI and Growing Expertise (ENGAGE) will be led by Prof. Julius Oyugi, Director Research, University of Nairobi Institute of Tropical and Infectious Diseases (UNITID) supported by Dr. Timothy Kamanu (DASCLAB), Department of Mathematics University of Nairobi, six other regional Kenyan Universities and University of California in San Francisco By equipping students with essential skills, the program opens doors to well-paying jobs in the fast-growing field of data science.
During the announcement Prof. Stephen Kiama, Vice Chancellor, UoN said, "University of Nairobi is excited to collaborate with Takeda to lead in the cultivation of a diverse, gender-balanced pool of data scientists by empowering and training underprivileged women so that we can address biases in public health data and machine learning and achieve better health outcomes,"
Prof. Oyugi, who will be leading this program said that the program which will target girls and young women from less privileged background will try to bridge the gender-based gap that currently exists among experts in machine learning and Artificial intelligence but also to leverage data-driven approaches to tackle public health challenges.
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