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Wednesday, July 17, 2019
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Phd Fellows


Paul Mwaniki

Trainee Type:

PhD

Associated Institution:

University of Nairobi, Kenya. KEMRI-Wellcome Trust Research Programme, Kenya


Paul Mwaniki has a BSc. in Statistics from Maseno University and an MSc. in Medical Statistics from London School of Hygiene and Tropical Medicine. Paul has a keen interest in applying machine learning in medicine and particularly in low income settings. His PhD project aims at addressing challenges arising from small data sets while developing diagnostic and prognostic models in low income settings.

Supervisor(s):

  • Dr. Timothy Kamanu
  • Prof. René Eijkemans
  • Dr. Samuel Akech

Neema Mosha

Trainee Type:

PhD

Associated Institution:

National Institute for Medical Research-Mwanza,Tanzania, Stellenbosch University – Cape town, South Africa


Neema Mosha is a qualified Statistician, previously worked as a medical statistician at Mwanza Intervention Trials Unit (MITU)-Mwanza Tanzania and also as a faculty member in the department of epidemiology and biostatistics at the Kilimanjaro Christian Medical University College in Moshi, northern Tanzania. She has a science degree in statistics from the University of Dodoma (2011) and a master’s degree in epidemiology and applied biostatistics from Kilimanjaro Christian Medical University College (2014). She was a Demographic Health Survey (DHS) fellow in 2014 a programme that aims at increasing capacity of university faculty members from DHS survey countries and building a long-term institutional sustainability for universities to train students and faculty to use DHS survey data. Also she is a HIV Trust Scholarship Alumni (2014-2015) a short-term scholarships to health care professionals in developing countries that helps recipients learn skills and techniques which will add to their local department’s capacity in HIV treatment and prevention.

Supervisor(s):

  • Prof. Rhodrick Machekano, PhD
  • Prof. Jim Todd
  • Prof. Taryn Young, PhD

Mohanad Mohammed

Trainee Type:

PhD

Associated Institution:

School of Mathematics, Statistics, and Computer Science, University of KwaZulu-Natal


Mohanad Mohammed is a PhD fellow at the School of Mathematics, Statistics, and Computer Science, University of KwaZulu-Natal. He received his BSc from the University of Gezira, Sudan. He received three senate prize for the academic excellence from the Deanship of Academic Affairs, University of Gezira. He did his MSc at the University of KwaZulu-Natal, South Africa. From his MSc, he published a paper and he was awarded a prize of academic excellence owing to his outstanding performance during his MSc. His research focuses on cancer diseases diagnosis and prognosis using gene expression data and next-generation sequencing data via statistical and machine learning techniques. His current research focuses on combining the gene expression and next-generation sequence data (Omics data) for cancer prediction using Poisson Regression Model, Negative Binomial Linear Discriminant Analysis, and convolutional neural networks among other machine learning methods. His favorite way of spending free time is playing soccer, reading, and relaxing.

Supervisor(s):

  • Prof. Henry Mwambi
  • Prof. Bernard Omolo
  • Prof. Bob Gagnon

Alexander Kasyoki

Trainee Type:

PhD

Associated Institution:

University of KwaZulu Natal, South Africa


Alexander is a holder of Master of Science in Applied Statistics and Bachelor of Science in Mathematics and Computer Science from Jomo Kenyatta University of Agriculture and Technology (JKUAT), Kenya. His Master’s degree project focused on Statistical Models for Count data. His PhD research focuses on Statistical Methods for Covariate Measurement Error Correction in Observational Studies, with Application to Health and Nutrition Examination Data.

Supervisor(s):

  • Prof. Henry Mwambi
  • Dr.Oscar Ngesa
  • Dr. George Agogo

Ashenafi Argaw Yirga

Trainee Type:

PhD

Associated Institution:

University of KwaZulu-Natal, KwaZulu-Natal, South Africa


I completed my undergraduate in Statistics at Addis Ababa University, Honours in Statistics and MSc in Statistics (with Distinction) at the University of KwaZulu-Natal. Currently I am a PhD Candidate at the University of KwaZulu-Natal, South Africa. During my Master’s Program I have published one Paper (Yirga, A.A., Ayele, D.G. and Melesse, S.F., Application of Quantile Regression: Modelling Body Mass Index in Ethiopia, The Open Public Health Journal (2018) 11:221-233, https://benthamopen.com/FULLTEXT/TOPHJ-11-221) and second one have been accepted (Yirga, A.A., Mwambi, H.G, Ayele, D.G. and Melesse, S.F., 2018, Factors affecting child malnutrition in Ethiopia based on an ordinal response regression model, African Health Sciences Journal, 18.). This year my third paper is under review (Ashenafi Yirga, Sileshi Melesse, Dawit Ayele, Henry Mwambi, 2019, The use of complex survey design models to identify determinants of malnutrition in Ethiopia). My PhD’s project is focused on researching the acute HIV infection study. I would like to continue my career in the field of Biostatistics and Public health.

Supervisor(s):

  • Dr Sileshi Fanta Melesse
  • Prof Henry Mwambi
  • Dr Dawit Getnet Ayele

Ola Jahanpour

Trainee Type:

PhD

Associated Institution:

Kilimanjaro Christian Medical University College-Tanzania


Ola has a degree in Medicine from the Catholic University of Health and Allied Sciences. While she was honored to attend to sick people, she felt she could do more help by preventing diseases. This then took her into public health and research field. Ola did her Master’s in Epidemiology and Applied Biostatistics at the Kilimanjaro Christian Medical University College. Her research work has been mostly in maternal and new-born health, focusing on using mixed models. Currently, she is working on her PhD where she will develop small area models

Supervisor(s):

  • Dr. Michael Mahande
  • Prof. Jim Todd
  • Prof. Henry Mwambi
  • Dr. Okango Elphas

Zvifadzo Matsena-Zingoni

Trainee Type:

PhD

Associated Institution:

The University of Witwatersrand, South Africa


Zvifadzo Matsena-Zingoni is a holder of BSc degree in Biochemistry and Statistics, and MSc in Biostatistics from the University of Zimbabwe. Currently in 3rd year of her PhD in Biostatistics with The University of Witwatersrand, she is focusing “Monitoring HIV disease progression among adults ART patients in Zimbabwe: Multistate Markov Models” employing both frequentist and Bayesian models. This is critical in in understanding the ART outcomes patterns after ART service decentralization, transitions patterns of patients in the process of recovery, spatial distribution of ART outcomes across the country and the cost effectiveness of ART from the patient perspective. Not only has Zvifadzo provided Biostatistics consultancy in HIV/AIDS, she has collaborated in other public health fields including cancer, malaria and schistosomiasis leading to a couple of peer reviewed journal papers. As an esteemed Biostatistician, what she likes best about her work is the challenge and the indepth thinking associated with it. Her carrier goals is to continue in infectious disease modelling research, teach students and acquire new knowledge everyday

Supervisor(s):

  • Professor Tobias F. Chirwa, PhD
  • Professor Jim Todd, PhD
  • Professor Eustasius Musenge, PhD

Memory Chitema

Trainee Type:

PhD

Associated Institution:

Associated Institution: John Hopkins Programs for International education in Gynecology and Obstetrics (JHPIEGO)


Memory Chitema completed her undergraduate degree in Statistics and Biology at the University of Malawi, Chancellor College. She has worked with various Non-Governmental organizations all focused within the health sector. The health division provides her with a sense of accomplishment as she ably provides evidence based results within the various projects she has been apart of. Providing assistance to the community brings her satisfaction as can ably see how lives are saved and changed for the better. She is inspired by how public health interventions informed by relevant statistical data have reduced the morbidity and mortality of various range of diseases. In further pursuit of her dreams, she is currently enrolled in a Master of Science degree in Biostatistics at the University of Malawi, Chancellor College. She believes that this program will increase her practical competence as a researcher. She says the field of Biostatistics is exciting to her as it has made major contributions to the current biological experimental designs ranging from collection, summarization and analysis of data.


Glory Chidumwa

Trainee Type:

PhD

Associated Institution:

University of the Witwatersrand, Johannesburg, South Africa


Glory Chidumwa holds a BSc (Statistics and Mathematics, University of Zimbabwe - 2014) and a Masters in Biostatistics (Wits University - 2017). He is one of the first four (4) fellows to receive funding for biostatistics masters training from the Wellcome Trust (UK) under the Sub-Saharan Africa Consortium for Advanced Biostatistics training (SSACAB) at Wits University in 2016. His PhD will explore interactions between nine (9) chronic NCDs using data from the WHO Study on Global Ageing and Adult Health (SAGE) Wave 1 and Wave 2 in South Africa, with some aspects of generalized structural equation modelling (GSEM) and multilevel temporal Bayesian networks.

He has worked as a data scientist for MRC/Wits DPHRU and the Centre of Excellence in Human Development at Wits University. Currently, he works as a biostatistics consultant at the Wits Faculty of Health Sciences research office, where he provides statistical support in medicine for both students and faculty staff. His interest is in statistical aspects of longitudinal and cluster randomized trials as well as SEM.

Supervisor(s):

  • Prof Jonathan Levin
  • Prof Lisa Micklesfield
  • Dr Lisa J Ware
  • Dr Innocent Maposa

Zelalem Dessie

Trainee Type:

PhD

Associated Institution:

University of KwaZulu-Natal, Durban, South Africa


Zelalem Dessie completed his undergraduate and Masters of science in Applied statistics at the University of Hawassa, Ethiopia. His master’s project was Stochastic Modeling of HIV/AIDS Evolution. However, through work in modeling of HIV/AIDS evolution, he came to recognize that his knowledge is still limited in advanced statistical modeling. Therefore, he plant to further an advanced study of Biostatistics to learn more and also to put his knowledge into a higher standard, so that he could be a well-equipped and professional researcher. His PhD project is Modelling of Longitudinal Ordinal Computing Risk in application to HIV/AIDS.

Supervisor(s):

  • Prof. Temesgen Zewotir
  • Prof. Henry Mwambi
  • Prof Delia North

Halima Twabi

Trainee Type:

PhD

Associated Institution:

University of Malawi, Chancellor College, Zomba, Malawi


Halima Twabi is a Biostatistician by profession and a Lecturer in Statistics at the University of Malawi, Chancellor College. She is a PhD Student in Biostatistics under the same University. Her research interest is on developing and applying survival, longitudinal and causality models on Health and Epidemiology data. Her current research looks at identifying statistical methods that can be used to study causal inference on multiple outcomes when using longitudinal observational data. The research addresses complex causal problems public health specialists and clinicians face when investigating efficacy of a treatment on several outcomes, or effect of an intervention on several measured outcomes in situations where public health complexity is not characterized by a single outcome measure on data that is observational and readily available.

Supervisor(s):

  • Professor Samuel Manda
  • Professor Dylan Small