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.

2023 (Mahadia Tunga WiDS Fellowship)

team
Sophia Yahya Ahmed
Her research is on examining the impact of school resources and infrastructures on students' performance in government secondary schools in dar es salaam, tanzania.
team
Gladness Godfrey Mwandry
Her research is on Assessing the impact of Carbon Footprint of Plastic Bottles in Dar es Salaam, Tanzania with a Focus on Bottle Weight

2022 (Mahadia Tunga WiDS Fellowship)

team
Suna Salum
Her research is on Temporal analysis of HIV incidences in Tanzania
team
Fatma Issa
Her research is on Prediction Of Cryptococcal Meningitis Among HIV-Infected Individuals in Tanzania

2021 (PEPFAR Scholarship & Mahadia Tunga WiDS Fellowship)

team
Mwantum Mmbaga
Her research is on Early detection of depression among people living with HIV-positive using machine learning techniques
team
Nurat Karamagi
Her research is on Predicting the HIV Positivity from Symptomatic Presentations at the Point of Service.
team
Simon Machera
His research is on the early detection of Tuberculosis cases, which is a co-morbid disease associated with HIV.
team
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)

team
Brenda W. Mtenga
Brenda Walter Mtenga has expertise in economics and finance. Her research is on HIV drug adherence
team
Cylirus Kaijage
Cylirus has a BSc. In Applied Statistics
team
Joseph Kwagilwa
Joseph has a BSc. in Computer Science
team
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)

team
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
team
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
team
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
team
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)

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

Don't miss out, Stay updated