Assistant Professor (Transitional)
Statistics and Probability, School of Mathematical Sciences
University of Nottingham
Yordan P. Raykov
Statistical Machine Learning
About me: With a team of researchers, I study problems in statistical machine learning focussing on interpretable ML and exploratory applications. My work lies at the intersection of statistics and computer science, with a particular focus on Bayesian nonparametrics and hierarchical generative models. Most of my applied work is in biomedical engineering, such as algorithms for digital health, precision medicine, and proteomics.
My brief bio: I discovered my love for algorithms at mathematics and informatics olympiads at my home, Bulgaria. In 2010, I came to the UK to do my BSc in mathematics at the University of Leicester. Fascinated by probabilistic modeling, I went on to do a PhD in machine learning at Aston University where I worked on scalable Bayesian nonparametric algorithms. Utilizing some of these algorithms, I then worked on solving some digital monitoring applications with ARM and then my postdoc partners from Radboudumc, UCB Pharma, John Hopkins, and Michael J Fox Foundation. After a short industry break working on protein prediction spin-off, I joined the Rolls Royce Digital Academy at Aston University. From September 2021, I have moved to the University of Nottingham where I am affiliated with the Horizon Institute for Digital welfare and the Statistics and Probability department.