Dr Ali Gooya is a Lecturer in Computer Science in the School of Computing, University of Leeds. He earned his PhD from the University of Tokyo in medical image analysis in 2007, and joined University of Pennsylvania as a post-doc research associate to develop machine learning methods for medical vision. He has won multiple prestigious fellowships including, Japan Society for Promotion of Science JSPS-PDRA (2008), JSPS short-term invitational (2020), and FP7 Marie-Curie IIF fellowship (2014). He has been also awarded an EPSRC New Investigator Grant as PI (EP/S012796/1), two Cancer Research UK sandpit awards, and an Innovate UK KTP application (as Co-PI).
Ali Gooya’s research interest broadly lies in the intersection of the machine learning, computer vision and medical imaging and consists of probabilistic deep learning, reinforcement learning, with the target applications in cancer image analysis, computer aided decision support systems, prediction and marker discovery, statistical inference on populations, and computational anatomy. His research vision is to aspire unsupervised machine learning for AI in the healthcare, as expert annotations in this particular field are sparse. He is particularly experienced in creating methodologically innovative deep Bayesian frameworks, often involving rigorous mathematical modelling, as evidenced by his publications in IEEE TPAMI as the first author.