dLab Scholars

dLab is delighted to introduce the Mahadia Tunga WiDS Fellowship, designed to empower aspiring female data scientists to pursue a Master’s degree in data science at the University of Dar es Salaam. This fellowship offers a unique opportunity to engage with global experts and take on real-world challenges in the field.

Since 2018, dLab has been granting up to five scholarships annually to exceptionally qualified candidates, enabling them to excel in the dynamic field of data science. This achievement has been made possible through collaboration with Women in Data Science Conference (WiDS), and the Data Collaboratives for Local Impact program (DCLI), with valuable support from PEPFAR funds. To date, dLab has provided scholarships to a total of 18 students, spanning the years from 2018 to 2022.

The scholarship covers tuition fees for two years.Tanzania Data Lab (dLab) aims to develop practical skills in advanced data analytics, visualization and other areas of data science sub-disciplines which are in high demand.

Scholarship award is subject to acceptance to the MSc in Data Science with UDSM CoICT, maintenance of good academic standing for the duration of the program, and an interest in contributing to saving lives and ending HIV/AIDS. If accepted, the applicant commits to participating in dLab activities and training throughout the program, and to at least 3 months of “in-resident” work at dLab in support of data science research and solutions related to health, gender equality and economic empowerment as contributors to ending the AIDS epidemic.

2022 (Mahadia Tunga WiDS Fellowship)

Suna Salum

Her research is on Temporal analysis of HIV incidences in Tanzania

Fatma Issa

Her research is on Prediction Of Cryptococcal Meningitis Among HIV-Infected Individuals in Tanzania

2021 (PEPFAR Scholarship & Mahadia Tunga WiDS Fellowship)

Mwantum Mmbaga

Her research is on Early detection of depression among people living with HIV-positive using machine learning techniques

Nurat Karamagi

Her research is on Predicting the HIV Positivity from Symptomatic Presentations at the Point of Service.

Simon Machera

His research is on the early detection of Tuberculosis cases, which is a co-morbid disease associated with HIV.

Rachel Butoto

Her research is on Improving the Performance for Prediction of the Risk for HIV-1 Drug Resistance Mutations among People Living with HIV in Sub-Saharan Africa.

2020 (PEPFAR Scholarship)

Brenda W. Mtenga

Brenda Walter Mtenga has expertise in economics and finance. Her research is on HIV drug adherence

Cylirus Kaijage

Cylirus has a BSc. In Applied Statistics

Joseph Kwagilwa

Joseph has a BSc. in Computer Science

Saida Nyasasi

Saida is a computer engineer. Her research is on assessing risk factors for invasive cervical cancer among women living with HIV/AIDS by using machine learning predictive techniques

2019 (PEPFAR Scholarship)

David Rugeihyamu

David Rugeihyamu has expertise in telecommunication engineering. He is researching on using social media to provide HIV/AIDS information to people aged of 15-49 years old

Meshack Mbeswa

With knowledge in official statistics, Meshack's research is on prediction of HIV drug resistance using socio-cultural, economic, health and economic factors

Mussa Josiah

As an expert in informatics, Mussa's research is focused on the effect of developing a random forest model to predict the progression of HIV in antiretroviral initiating patients in Tanzania

Mwanahamisi Suleiman

Mwanahamisi Suleiman is a telecommunication engineer. Through her research, she is studying the prediction of viral suppression in Adolescents living with HIV/AIDS using non-virological and non-immunological features

2018 (PEPFAR Scholarship)

Upendo Mchome

Upendo Mchome has a bachelor degree in Information System Management. Her research is on Antiretroviral Therapy dropout prediction model based on PLHIV-centric adherence predictors

Frida Fulgence

Frida Fulgence is an expert in IT and digital financial services. Her research is exploring the probabilistic graphical model for HIV prevalence prediction

Rodrick Kayombo

Rodrick Kayombo has experience in Computer Science, IT audit, and financial audit. Rodrick's research is looking into blockchain based framework for crowdsourcing medical data collection

George Motta

His research is on ``An approach for improving topic understanding and opinion mining from Kiswahili HIV/AIDS-related social media conversations``