Charlesquin Kemajou Mbakam

My academic journey began at the University of Dschang in Cameroon, where I earned a Master’s degree in Applied Mathematics in 2015. During this time, I worked on the mathematical modelling and simulation of the life cycle of Plutella xylostella, developing an early interest in using mathematics to understand real-world problems.

In 2020, I completed a second Master’s degree in Artificial Intelligence through the African Master’s in Machine Intelligence (AMMI) programme in Rwanda. My research focused on semi-blind inverse problems in imaging, introducing me to the intersection of statistical modelling, machine learning, and computational imaging. Motivated by these challenges, I went on to pursue a PhD in Statistics and Machine Learning at Heriot-Watt University in Edinburgh, supervised by Professors Marcelo Pereyra and Jean-François Giovannelli. My doctoral research explored how statistical methods and deep learning can be combined to develop efficient and reliable solutions to imaging inverse problems.

I am currently a Research Associate at Heriot-Watt University, Edinburgh. My research lies at the intersection of Bayesian inference, generative AI, and computational imaging, with a particular interest in trustworthy AI, uncertainty quantification, and image and video restoration. I am especially interested in developing methods that combine the mathematical foundations of statistical inference with the flexibility of modern generative models. My goal is to build imaging systems that are not only accurate and computationally efficient, but also reliable, interpretable, and capable of expressing uncertainty in their predictions.