QLA welcomes Cohort 2 Ph.D. Students for a Research Visit

Ten Ph.D. students, whose work spans fields from quantum topology to machine learning and climate science, are currently on a research visit at Quantum Leap Africa. This is the second cohort of students to be admitted into the Ph.D. in Data Science program at QLA.

Coming to QLA from Cameroon, Rwanda, Cote d’Ivoire, Benini, and Nigeria, these students have been invited for a period of two months to fully immerse themselves in QLA’s scientific community and share ideas about the research they are each working on. 

Given the structure of our Ph.D. programs, the students are funded through QLA but have their research work carried out in partner universities and research institutions across Africa and globally. These research visits at QLA provide the students with a unique opportunity to learn from experts in their respective fields, broaden their knowledge base, and gain valuable experience in conducting research. It is also an opportunity for the students to collaborate with each other, exchange ideas and gain insight into the future of their research.      

While on his first-time visit to QLA, Péguy Kem-Meka Tiotsop Kadzue (hyperlink this to his profile under “People”) from Cameroon narrates his experience of finding a research environment whose goals align with his career aspirations. “Joining QLA enabled me to develop my Ph.D. project on Quantum Topological Graph Neural Networks and Applications”, he said. In addition, Péguy mentioned that QLA has offered him special training that gave him the foundation for a successful research career in data science. During this visit to QLA, he has learned about “Generative Models in Machine learning”. He also learned about the “Kernel Method in Machine Learning” and “Simulation-Based Inference”. These are fantastic machine-learning methods that he was not familiar with.

“None of our Ph.D. students are in the same country, even if they are, they are in different institutions”, said the Manager, Scientific Programs Molly Mutesi (hyperlink this to her profile under people). “The purpose of these visits is to have the students in the same place, work together, and stimulate collaboration since they are mostly working on different but related topics”. 

Irene Uwerikowe (hyperlink to her profile under people) from Nigeria is studying the analysis of parent-child interaction videos to identify patterns of different interaction types using machine learning tools. Her approaches are relevant to Jeremiah Ayock Ishaya’s (hyperlink) research which focuses on measuring responsive caregiving using machine learning. 

We believe that collaborations between researchers from different universities can also lead to new insights and discoveries. These research visits are thus an excellent opportunity for the students to expand their networks and develop important professional relationships with their peers in academia.