Computer Laboratory

Ben Day

Picture of Ben Day

I'm a PhD student at the University of Cambridge Computer Laboratory and a member of the Artificial Intelligence and Computational Biology groups under the supervision of Prof. Pietro Lio'. I previously worked in the group whilst studying for my Masters in the Department of Physics.

My research interests are in novel Deep Learning architectures, particularly those that use recursive conditioning to enable self-understanding in learning systems and the application of graph based models to physics problems & non-Euclidean deep learning generally. I also work on taking a more scientific approach to building a 'theory of deep learning'. I supervise Masters student's research projects in both Computer Science and Physics and teach undergraduates.

When I'm not working I like to cook and garden. I can (technically) juggle three four balls and working on four five!

Publications

  • Cristian Bodnar, Ben Day & Pietro Liò (2019) Proximal Distilled Evolutionary Reinforcement Learning . Under review. [arXiv]
  • Ezra Webb, Ben Day , Helena Andres-Terre & Pietro Liò (2018) Factorised Neural Relational Inference for Multi-Interaction Systems . Poster presented at the Learning and Reasoning with Graph-Structured Representations workshop at ICML 2019. [arXiv, poster]
  • Enxhell Luzhnica, Ben Day & Pietro Liò (2019) On Graph Classification Networks, Datasets and Baselines . Accepted for oral presentation (1 of 3) at the Learning and Reasoning with Graph-Structured Representations workshop at ICML 2019. [arXiv, poster, talk, slides]
  • Enxhell Luzhnica, Ben Day & Pietro Liò (2019) Clique pooling for graph classification . Poster presented at the Representation Learning on Graphs and Manifolds workshop at ICLR 2019. [arXiv, poster]
  • Conor Sheehan, Ben Day & Pietro Liò (2018) Introducing Curvature to the Label Space [arXiv]

Talks

  • On Graph Classification Networks, Datasets and Baselines. 2019. Learning and Reasoning with Graph-Structured Representations workshop at ICML 2019 [talk, slides]; Computational Biology Group Talk.
  • Factorised Neural Relational Inference for Multi-Interaction Systems. 2019. Computational Biology Grou Talk.

Research Project Supervision

Part III Physics (Natural Sciences) Research Projects

Co-supervised with Prof Liò

  • Conor Sheehan (2018). Introducing Curvature to the Label Space . Project mark 78/100.
  • James Bernardi (2019). Physically Motivated Label Smoothing to Encode Human-Induced Segmentation Labelling Error
  • Jan Elsner (2019). Encoding Dynamics from Visual Data . Project mark 77/100
  • Ezra Webb (2019). Factorised Neural Relational Inference . Project mark 83/100 Tessella Prize for Best Computational Project

MPhil Computer Science Research Projects

Co-supervised with Prof Liò

  • Michelle Zheng (2018). . Machine Learning for Image Analysis of 3D Super-Resolution Microscopy. Project mark 82/100
  • Enxhell Luzhnica (2019). Best Project Prize
  • Cristian Bodnar (2019). Best Student Prize (Project & Coursework)

Teaching

  • Supervised Machine Learning with Real World Data Lent 2019
  • Supervised Foundations of Data Science Michaelmas 2019

Contact

Ben Day
Department of Computer Science and Technology
University of Cambridge
15 JJ Thomson Avenue
Cambridge CB3 0FD

Last updated 2019/09/14