Computer Laboratory

Paul Scherer

Picture of Paul Scherer

I am a PhD student at the University of Cambridge Computer Laboratory under the supervision of Prof. Pietro Lio' and Dr. Mateja Jamnik as part of the Artificial Intelligence Group and the Computational Biology Group. I am generously funded through the W.D. Armstrong Studentship.

My research lies within the fields of information theory, machine learning, and biomedical informatics. My current research looks into developing learning algorithms applicable to irregular structured data such as graphs. Other research interests lie in developing generative models and the interpretation of their outputs. Previous research has focused on developing clustering algorithms on graphs, heterogenuous data integration, and data harmonization techniques.

Outside of working I enjoy motorcycling, camping, cooking, and reading basic maths.

Other Academic Projects

  • Conducting federated data analysis using DataSHIELD and R for epidemiology research (2016-2017).
  • Basic research into harmonization of heterogenuous epidemiological data (2016-2017)
  • Investigation into role privacy of multi-robot formations using generative adversarial networks (2018).
  • Currently developing an ABM-CA model of land use transformation for the Department of Land Economy at the University of Cambridge (2019).

Publications

  • Nikola Simidjievski, Cristian Bodnar, Ifrah Tariq, Paul Scherer, Helena Andres-Terre, Zohreh Shams, Mateja Jamnik, Pietro Liò Variational Autoencoders for Cancer Data Integration: Design Principles and Computational Practice (Submitted, PREPRINT available), 2019
  • S Pastorino, T Bishop, SR Crozier, C Granström, K Kordas, LK Küpers, EC O'Brien, K Polanska, KA Sauder, MH Zafarmand, RC Wilson, C Agyemang, PR Burton, C Cooper, E Corpeleijn, D Dabelea, W Hanke, HM Inskip, FM McAuliffe, SF Olsen, TG Vrijkotte, S Brage, A Kennedy, D O'Gorman, P Scherer, K Wijndaele, NJ Wareham, G Desoye, KK Ong Associations between maternal physical activity in early and late pregnancy and offspring birth size: remote federated individual level meta-analysis from eight cohort studies. BJOG, Volume 126, Issue 4, 2018.

Talks

  • Federated Data Analysis using DataSHIELD and R. 2017. University of Cambridge MRC Epidemiology Unit, Addenbrookes Hospital
  • Weighted Clustering Algorithms for Protein-Protein Interaction Networks 2016, University of Edinburgh

Teaching and Supervisions

  • Supervising 1B Artificial Intelligence Easter 2019

Contact

Paul Scherer
Department of Computer Science and Technology
University of Cambridge
15 JJ Thomson Avenue
Cambridge CB3 0FD

Last updated 2019/03/14