18 June 2020

On the 8th of June Edward Kanuti Ngailo defended his thesis, the first PhD defense via Zoom ever at the Department of Mathematics at Linköping University. “It was actually very nice” says, now doctor, Ngailo.

Dr. Edward Ngailo with his two supervisors Martin Singull and Dietrich von Rosen.
Dr. Edward Ngailo with his two supervisors Martin Singull and Dietrich von Rosen.

Edward Ngailo, is a so-called sandwich PhD student, funded by Sida, Styrelsen för Internationellt Utvecklingssamarbete, through International Science Programme (ISP). He has spent time alternately at the department of Mathematics (MAI) at Linköping University and his home university, University of Dar es Salaam in Tanzania. He has been living in Linköping, Sweden since 2018 and has during that time produced two more papers and now also successfully defended his thesis.

The title of Dr. Ngailo's thesis within the subject of probability theory and statistics is: "Contributions to linear discriminant analysis with applications to growth curves".

How can your work be applied, in layman's terms if possible?

Edward Ngailo nailing his PhD thesis. Nailing the thesis is a typical Swedish tradition which is done about 3 weeks before the PhD defence.Edward Ngailo nailing his PhD thesis. Nailing the thesis is a typical Swedish tradition which is done about 3 weeks before the PhD defence.

– Usually in medical research several decisions or identification of problems are based on examinations which involve measurements taken over time. For example, we may be interested in identifying whether a tumor is a benign (non cancerous) tumor or a malignant (cancerous) tumor based on measurements. In this kind of situation, the challenge is to construct a decision rule based on these measurements that can be used to classify between healthy subjects (non cancerous) and patients (cancerous). For this purpose, classification methods can be used and there are many different techniques. The one that I use in my work is linear discriminant analysis.

How was it, defending your thesis via Zoom?

– It was actually very nice. We have been using Zoom in many courses since we moved to distance mode. I got used to do presentations and have also been discussing a lot with my supervisors over Zoom, so when it came to the defense, it was very familiar.

With his thesis defended Edward will now return to his home country of Tanzania, strengthening the research capacity in mathematics.

– I will teach, especially mathematical statistics courses, at the University of Dar es Salaam. I will also be doing research and supervision. It’s important to keep the fire burning so to speak, especially when it comes to research. You do research, get results and come up with new things.

How has your time in Sweden been?

– I have really enjoyed my time here with studies and research but also the weather. It’s a little bit different from what you get in East Africa and I enjoy that very much. Especially snow, I really like that.

What do you think about the bilateral research collaboration?

– It’s good that we can acquire quality education, good knowledge and a certain set of skills here and take that back to our countries. I really hope that this program will continue to strengthen capacity building at our side.

Publications

2021

Farrukh Javed, Stepan Mazur, Edward Ngailo (2021) Higher order moments of the estimated tangency portfolio weights Journal of Applied Statistics, Vol. 48, p. 517-535 (Article in journal) Continue to DOI

2020

Edward Ngailo, Dietrich von Rosen, Martin Singull (2020) Linear discriminant analysis via the Growth Curve model and restrictions on the mean space
Edward Ngailo, Dietrich von Rosen, Martin Singull (2020) Approximation of misclassification probabilities in linear discriminant analysis with repeated measurements
Edward Kanuti Ngailo (2020) Contributions to linear discriminant analysis with applications to growth curves

2019

Taras Bodnar, Stepan Mazur, Edward Ngailo, Nestor Parolya (2019) Discriminant analysis in small and large dimensions Theory of Probability and Mathematical Statistics, Vol. 100, p. 24-42 (Article in journal)

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