Lecturers
Short bios of lecturers and teaching assistants are published here as their participation is confirmed.
Dr. Edna Milgo is a seasoned ICT expert with over 10 years of experience in Artificial Intelligence (AI), Machine Learning (ML), and Data Science (DS) specializing in AI design, ML algorithms and Stochastic Optimisation techniques. She is currently the head of the Department of Computing and Informatics, at the Open University of Kenya.
Her background includes teaching AI courses, leading AI research projects, capacity building, keynote speaking and AI consultancy. Recent projects include development of a population scoring model for targeted decision-making, predictive models in medical research and a bayesian ML based adaptive learning algorithm among others. Dr. Edna holds a Ph.D. in Artificial Intelligence from Vrije Universiteit Brussel - Belgium and a M.Sc in Information Security from Columbus State University - USA. She has published extensively in refereed journals and presented at international conferences.
Dr Charles Ndung’u Ndegwa is a physicist, dedicated educator, and AI researcher specializing in advanced machine learning and deep learning.
He holds a Ph.D. in Physics from the University of Nairobi, where he built a strong foundation in teaching computational physics and ML. Having recently completed a postdoctoral fellowship at LISN, CNRS, Université Paris-Saclay, his work bridges physics and AI-driven data analysis. He applies the full spectrum of machine learning techniques—from deep learning to anomaly detection—to solve complex, large-scale scientific challenges.
Dr Thomas Njoroge is a lecturer and head of the Department of Computing in the School of Computing and Informatics at Karatina University, specializing in artificial intelligence, agentic systems, and software engineering.
Thomas holds a PhD in information systems, specializing in artificial intelligence, and has experience in teaching, research, software development, and applied AI. He is a multiple grant winner, having secured research and innovation funding to support the development of technology-driven solutions. His research interests include AI and agentic systems, machine learning, natural language processing, intelligent automation, and AI-enabled decision-making. As a full-stack developer and AI researcher, he combines academic research with practical software engineering to develop intelligent systems for real-world applications. Thomas has published scholarly work in artificial intelligence and machine learning and has experience in cloud-based application development. His work focuses on advancing practical AI innovation, particularly in education, intelligent services, and other domains where emerging AI technologies can create meaningful societal impact.
Dr. Théo Santos is a postdoctoral researcher specializing in deep learning, machine learning, and data science, with a particular focus on their application to physics and the development of data-driven methodologies. His research interests include generative deep learning and its applications to scientific problems.
He holds a PhD in Physics from Université Claude Bernard Lyon 1, France, where his research focused on the use of generative deep learning — particularly generative adversarial networks — for inverse problems in astrophysics and geophysics, with an emphasis on image-processing applications. During his PhD, he also taught courses in geoscience, mathematics, computer science, and machine learning to geoscience students.
He is currently a postdoctoral researcher at the Institut de Ciències del Mar (Institute of Marine Sciences) in Barcelona, Spain. His current research focuses on generative, data-driven parametrization methods for recovering geodynamical structures in the Earth's mantle from seismic tomography.
Teaching assistants