I am Haoting Zhang, a Postdoctoral Researcher at the National Heart and Lung Institute (NHLI), Imperial College London. My research mainly spans two areas. First, I am a part of the My Heart Counts UK programme and work on using real‑world physical activity and health data to support early diagnosis and long‑term monitoring of patients with pulmonary hypertension. Second, I work on developing machine learning methods for drug discovery. More generally, I am interested in developing interpretable and uncertainty-aware machine learning methods for healthcare applications, with an emphasis on improving their translational impact in clinical practice.
Previously, I completed my PhD as part of the 2020 cohort of the HDR UK–Turing Wellcome PhD Programme in Health Data Science, based at ML@CL in the Department of Computer Science and Technology, University of Cambridge. I was supervised by Carl Henrik Ek, Marta Milo, and Magnus Rattray. Prior to that, I studied Mathematics and Statistics as an undergraduate at St Hilda’s College, University of Oxford, followed by a Master’s degree in Machine Learning at UCL.
My interest lies in approaching healthcare challenges with probabilistic and/or generative models in machine learning. Such types of models have the potential to be utilised in healthcare because they provide routes to inserting prior knowledge, interpreting results and estimating uncertainty, which are all crucial aspects in healthcare applications. However, crucial gaps remain to be filled, and I am generally interested in tackling these challenges. More broadly, my research focuses on bridging the gap between machine learning for healthcare and its deployment in clinical practice.
Oh, and here is a photo of my cat:
