	Department of Engineering Computational and Biological Learning Lab

University of Cambridge > Department of Engineering > Information Engineering > Computational and Biological Learning Lab > David Knowles

David A. Knowles

I'm a PhD student with Zoubin Ghahramani in the Machine Learning group of the Cambridge University Engineering Department. I'm the Roger Needham Scholar at Wolfson College, funded by Microsoft Research. My undergraduate degree comprised two years of Physics before switching to Engineering to complete an MEng with Zoubin. I took the MSc Bioinformatics and Systems Biology at Imperial College in 2007/8.
My research involves applying machine learning methods to data analysis problems in biology.
I'm involved with running the Cambridge University Statistics Clinic.
You can download my CV here. Here's a video of me and my friend Johan falling off cliffs on skis in Flaine, France.

Publications

[with abstracts]

Konstantina Palla, David A. Knowles and Zoubin Ghahramani (2012)
An Infinite Latent Attribute Model for Network Data
To appear: ICML 2012
Andrew Wilson, David A. Knowles and Zoubin Ghahramani (2012)
Gaussian Process Regression Networks
To appear: ICML 2012
David A. Knowles and Tom Minka (2011)
Non-conjugate Variational Message Passing for Multinomial and Binary Regression pdf
NIPS 2011
Supplementary material: pdf
Mehregan Movassagh, Mun-Kit Choy, David A. Knowles, Lina Cordeddu, Syed Haider, Thomas Down, Lee Siggens, Ana Vujic, Ilenia Simeoni, Chris Penkett, Martin Goddard, Pietro Lio, Martin Bennett, Roger Foo (2011)
Distinct epigenomic features in human cardiomyopathy url
Circulation, American Heart Association
David A. Knowles and Zoubin Ghahramani (2011)
Pitman-Yor Diffusion Trees pdf slides
Supplementary material: Sampling from the PYDT
27th Conference on Uncertainty in Artificial Intelligence (UAI)
David A. Knowles, Jurgen Van Gael, and Zoubin Ghahramani (2011)
Message Passing Algorithms for the Dirichlet Diffusion Tree pdf Code coming soon!
Conference on Artificial Intelligence and Statistics (AISTATS)
Extended version: pdf
Cornelia Schone, Anne Venner, David A. Knowles, Mahesh M Karnani, Denis Burdakov (2011)
Dichotomous cellular properties of mouse orexin/hypocretin neurons url
The Journal of Physiology
David A. Knowles and Zoubin Ghahramani (2011)
Nonparametric Bayesian Sparse Factor Models with application to Gene Expression modelling pdf url code
Annals of Applied Statistics
Daniel Glass, Leopold Parts, David A. Knowles, Abraham Aviv, and Tim D. Spector (2010)
No Correlation Between Childhood Maltreatment and Telomere Length url
In Biol Psychiatry. 2010 September 15; 68(6): Pages 21-22
Finale Doshi, David A. Knowles, Shakir Mohamed and Zoubin Ghahramani (2009)
Large Scale Non-parametric Inference: Data Parallelisation in the Indian Buffet Process. pdf
In NIPS 2009, 7-12 December 2009, Vancouver, BC, Canada.
Knowles, D. A. and Ghahramani, Z. (2007)
Infinite Sparse Factor Analysis and Infinite Independent Components Analysis. pdf
In 7th International Conference on Independent Component Analysis and Signal Separation (ICA 2007).
Lecture Notes in Computer Science Series (LNCS). Springer.

Workshop papers

David A. Knowles, Leopold Parts, Daniel Glass and John M. Winn
Inferring a measure of physiological age from multiple ageing related phenotypes. paper video
To appear at the NIPS workshop: From Statistical Genetics to Predictive Models in Personalized Medicine (NIPS PM 2011)
David A. Knowles, Leopold Parts, Daniel Glass and John M. Winn (2010)
Modeling skin and ageing phenotypes using latent variable models in Infer.NET. paper poster
Poster presented at: Predictive Models in Personalized Medicine Workshop, NIPS 2010, 6-11 December 2010, Vancouver, BC, Canada.
Knowles, D. and Holmes, S. (2009)
Statistical tools for ultra-deep pyrosequencing of fast evolving viruses. pdf video slides
Presented at: Computational Biology Workshop, NIPS 2009, 7-12 December 2009, Vancouver, BC, Canada.

Reports/Theses

Bayesian non-parametric models and inference for sparse and hierarchical latent structure (2012) pdf
PhD Thesis, University of Cambridge
Supervisor: Zoubin Ghahramani
Serial and Parallel Inference in Sparse Nonparametric Latent Factor Models applied to Gene Expression Modeling (2009) pdf
PhD First Year Report, Department of Engineering, University of Cambridge
Supervisor: Zoubin Ghahramani
Statistical tools for ulta-deep pyrosequencing of fast evolving viruses (2008) pdf
MSc Bioinformatics and Systems Biology, Imperial College London, Individual Project
Supervisor: Professor Susan Holmes, Stanford University
SBML-ABC: a package for data simulation, parameter inference and model selection, Group Report (2008) pdf
MSc Bioinformatics and Systems Biology, Imperial College London, Group Project
Supervisor: Professor Michael Stumpf
Infinite Independent Components Analysis (2007) pdf
MEng Information Engineering, Cambridge University, 4th year project
Supervisor: Professor Zoubin Ghahramani
Real Time Continuous Curvature Path Planner for an Autonomous Vehicle in an Urban Environment (2006) pdf
Summer Undergraduate Research Fellowship, Caltech. I was a member of Team Caltech, an entry into the DARPA Urban Challenge
Supervisor: Professor Richard Murray

Presentations

Diffusion trees as priors. This was a talk I gave about the Dirichlet diffusion tree and Pitman Yor diffusion tree at Collegio Carlo Alberto.
Inferring an individual's "physiological" age from multiple ageing-related phenotypes
I gave a talk at the Cambridge Statistics Initiative Special One-Day Meeting, which you can watch here. I also presented this work at the NIPS 2011 Personalised Medicine workshop: paper video
Variational methods for nonparametric Bayesian models
I gave a brief presentation at Microsoft Research summarising some attempts to use variational inference in nonparametric, particularly Dirichlet Process based, models. The slides are here.

Code

The Matlab code for infinite sparse factor analysis is available here. Please note that this is research code and as such is provided with no warranty and limited to no support.

Infer.NET

I'm a part-time developer and heavy user of Infer.NET. I recently wrote a blog post about some of the new features we've added in Infer.NET 2.4, check it out here.

Misc

Lagrangian duality

My last journal club was on convex optimisation. I think I finally got my head round Lagrangian duality, and hopefully came up with a reasonably intuitive explanation. My focus is on intuition rather than rigor, and is based almost entirely on Boyd and Vandenberghe's tome. I thought I should write this up while it's still fresh, so here you go:

Lagrangian Duality for Dummies

Binomial p-values

Regarding my work on 454 pyrosequencing error rates with Professor Holmes, I was asked about how to calculate a p-value for comparing two draws from a Binomial distribution to test the hypothesis that the number of substitutions seen in the sample is significantly greater than the number of substitutions seen in the control. There is actually no need to use the Poisson approximation, and the Binomial distribution very naturally takes care of varying coverage. I explain my approach here.

Emacs for Dummies

A few notes on using Emacs for Unix non-gurus.

Contact details

E-mail: dak33 at cam dot ac dot uk
Mail: Cambridge University Engineering Department, Trumpington Street, Cambridge CB2 1PZ, UK

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