Nuniyat Kifle Abebe, MSc, BSc
Primary Appointment
Lecturer, Addis Ababa University, School of Information Technology and Engineering, African Studies Center, Ethiopia
she/her/hers
Equitable AI for multilingual and low-resource healthcare settings
Nuniyat Kifle Abebe’s global health focus centers on the development and evaluation of AI systems for equitable healthcare in low-resource and multilingual settings. She is particularly interested in how data quality, representation, and contextual differences shape the fairness, reliability, and real-world impact of AI-driven health solutions. Her interests in global health equity align with the Center’s themes of empowering women, strengthening systems for health, addressing social and environmental determinants of health, and developing technical solutions. Abebe’s research examines how data quality, representation, and socio-technical factors influence the effectiveness and equity of AI-driven health solutions across different populations and environments.
Contact Information
nunika@umich.eduCountry Focus
Ethiopia
Thematic Priorities
Empowering women
Social and environmental determinants of health
Strengthening health systems
Technical solutions
Health Equity Focus
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Data science
Artificial intelligence, large language models, machine learning
Findable, accessible, interoperable, reuseable (FAIR) principles & ethical, legal, social implications (ELSI)
Gender equity
Gender and politics
Women's rights
Women's leadership in global health research
Workplace equity
Maternal morbidity and mortality
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Sexual and reproductive health
Circumcision
Family planning
Social justice and equity
Access to care
Activism and advocacy
Eliminating poverty
Economic development
Financing
Population Focus
Immigrants
Underserved/vulnerable
Women
Publications
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