Peguy Kem-Meka Tiotsop Kadzue

Peguy is a Ph.D. student in Data Science at Quantum Leap Africa (QLA) and a DeepMind fellow. His research interests include Topological Data Analysis, Machine Learning, Climate Science, Quantum Computing, and Algebraic Topology. His Ph.D. research project focuses on Quantum Topological Graph Neural Networks. Before joining QLA, Peguy was a teaching assistant in data science at the University of Ngaoundere in Cameroon from 2019 to 2022. While assisting students during this period, he wrote a good review article on Topological Data Analysis (TDA) for time series data. Prior to this teaching position, he completed his Master’s Degree in Mathematical Sciences at the African Institute for Mathematical Sciences (AIMS) in Cameroon in 2019.

Peguy is passionate about combining topological methods and machine learning to solve real-world problems. He was awarded a small grant in 2022 to pursue a project whose goal was to use TDA to provide a machine learning pipeline for short-term prediction of extreme climate changes which may impact agricultural activity. As part of this project, Peguy and his collaborators wrote a paper on the topological characterization of climate change, which is currently under review.