Lecturer in Predictive Analytics and Director of the FinTech PhD Programme
Roles and Responsibilities
- Director of the Domain-Driven Machine Learning Lab
- Director of the PhD Programme in Financial Technology
- Advisory Board Chair of the Centre for Data, Culture and Society
Background
Ben is a Lecturer in Predictive Analytics and joined the Business School from a previous McWilliams Fellowship at Carnegie Mellon University and the Pittsburgh Supercomputing Center in the United States. Ben served as a Review Panelist for the NASA Science Mission Directorate, the US Department of Energy's Office of Science Graduate Student Research, and the UK Engineering and Physical Sciences Research Council and Science and Technology Facilities Council, gave invited talks for the ExCALIBUR programme on high-performance computing led by the Met Office along with the UK Atomic Energy Authory and other UKRI Research Councils, and worked in the UK's investment management sector as a Research Engineer for Machine Learning.
Additional memberships include the Centre for Statistics at the School of Mathematics, the Centre for Financial Innovations at the Edinburgh Futures Institute and the Scottish Centre for Crime and Justice Research. Ben holds a PhD in Astrophysics and an MSc in Artificial Intelligence from the University of Edinburgh, as well as an accreditation as a Professional Statistician from the American Statistical Association and a Fellowship of the Higher Education Academy.
Research Interests
Ben’s research is centred on artificial intelligence and addresses domain challenges using machine learning, statistical inference and high-performance computing. With a strong focus on interdisciplinary collaborations and technology transfer between fields, this covers impactful applications and the problem-driven development of new methods. Current research projects include generative modelling for market microstructure in high-frequency trading, privacy-preserving techniques in central bank data disclosure, consumer behaviour in markets driven by self-identity, and spatio-temporal analysis for policy-making in crime reduction.
Prospective PhD students with interests in, broadly, machine learning and statistics as well as their application are welcome to reach out with their CV and a research proposal. This includes applications to other fields, provided a student secures a second supervisor who acts as a domain expert for the respective area, as well as students with a background in other numerate disciplines looking to change fields and joint supervisions with other schools at the university.
Ben is also available as a mentor for the current iteration of Marie Skłodowska-Curie Actions (MSCA) Postdoctoral Fellowships.