Simon Provost

Motivated by an eclectic curiosity for Computer Science and an aptitude for innovation. Simon pursued a B.Sc. in software engineering and dual M.Sc. degrees in advanced computer science and machine learning between his native France and the United Kingdom, where he decided to launch his research career. This academic path propelled him into the exciting world of research, where he found himself primarily due to the ability to press the boundaries of what is possible by uncovering previously uncharted areas and influencing the world's direction. His multifaceted experience, spanning agile startups, R&D divisions in larger corporations, and research laboratories, has honed his current expertise and placed him at the forefront of machine learning innovations for the future landscape.

Today, by synergising research and machine learning during his Ph.D. journey under the supervision of Prof. Alex. A. Freitas at the University of Kent, Simon aspires to unravel uncharted areas and transform the way Computer Science is currently perceived, while also, fortifying the open-source research community with powerful software engineering and robust systems.

Simon's research focuses on the design of cutting-edge automated machine learning systems (AutoML) that explore and exploit hitherto undiscovered classification domains in clinical and everyday settings. Situations where machine learning has not been a primary focus, but where advanced optimisation paradigms—Bayesian Optimisation, Evolutionary Algorithms, and (Multi-)Armed Bandits- can accelerate and improve the detection of patterns and the insights we can generate to improve human well-being.

In pursuit of his Ph.D. in the direction of empowering the AI Applied Medicine community, Simon also directs the open-source development of two robust, strongly-typed Python libraries with the primary goal of offering versatile applications for industries spanning from healthcare to finance. E.g., One of Simon's recent Open-Source Software contributions was towards the OpenML Lab at Eindhoven University of Technology initiatives.

• Data Mining (/ Machine Learning) and Knowledge Discovery, with an emphasis on the development of new automated machine learning (AutoML) systems that cover previously undiscovered novel classification domains (tabular-data context).
• Applications of classification methods in the Life Sciences, mainly in the Biology of Ageing, but also in Pharmaceutical Sciences and Risk-Based adjustment in Healthcare.
• Supervised machine learning and Automated Machine Learning.
• Bayesian Optimisation, Evolutionary algorithm, Multi-Armed Bandits.

Primarily, Simon teaches AI-based courses at the School of Computing. Simon is also enrolled as a teaching assistant for courses that combine programming and AI. Lastly, Simon is also teaching e-Health based courses where Machine Learning is presented and analysed as a candidate towards healthcare-based challenges.

Simon is interested in applying ML and AutoML in industry, such as the Healthcare sector, where he conducts active and regular research as a freelancer for the National Hospital Services of the United-Kingdom (NHS) to assist clinicians in improving the patient journey through early-diagnosis prediction with risk-adjustment machine learning models. Simon is eager to discuss additional initiatives with any industry or lab that could benefit from his collaboration and assistance.