QML4Africa Workshop
Quantum Machine Learning for Africa
22 August 2025, Deep Learning Indaba 2025
Kigali, Rwanda
Quantum Machine Learning for Africa
22 August 2025, Deep Learning Indaba 2025
Kigali, Rwanda
+ 100 Participant 8 Poster Presentation
Title: The potential and limitations of quantum machine learning
Abstract: Recent years have witnessed an incredible interest in the potential use of quantum computers for machine learning tasks. As of yet however, it remains unclear to what extent quantum computers can enable meaningful advantages over state-of-the-art classical methods, which have also seen significant progress in the last years. In this talk I will discuss evidence for- and against the use of a variety of different quantum algorithms for machine learning, with the goal of understanding both the challenges and opportunities in the field of quantum machine learning. I will start by examining the potential and limitations of near-term friendly quantum algorithms for generative modelling. Following this, I will shift the focus to supervised learning, and discuss the extent to which a widely-used class of quantum algorithms for classification problems can be dequantized.
Founder of Quantum Africa, Quantum Optimization, and Machine Learning Researcher at INSA Lyon. Holder of Master's + Engineering Degrees in Computer Science focused on Quantum Information. Her focus is on developing quantum machine learning algorithms and QUBO models for NP-Hard Optimization Problems, assessing different quantum and quantum-inspired solvers. Winner of the Arab Pionners Award in Quantum Computing. Leading Quantum Education African intiatives.
Dr. Aviwe Kohlakala is a Postdoctoral Research Intern in the Quantum Applications team at IBM Research Africa (South Africa lab). Aviwe’s background is rooted in a sturdy education in mathematics, with a focus in mathematical modelling and digital Science which involves areas such as digital image processing, computer vision, machine learning, and medical imaging.