Professor Neil Lawrence
Registration is open for the next Gaussian Process Summer School will be in Sheffield from Monday 13th January to Wednesday 15th January 2014 (so it's really a winter school).
We are also hosting a 1-day workshop on Gaussian Processes for Spatiotemporal Modelling on Thursday 16th January 2013. It will directly follow the Winter School.
MASAMB 2014 is being hosted by the group in Sheffield. With Nicolo Fusi we will also organise a colocated workshop on statistical genetics and a one day workshop showcasing Sheffield computational biology.
With James Hensman, Joaquin Quinonero Candela and Tianshi Gao, Neil is organising a NIPS workshop on Probabilistic Models for Big Data.
Moving on: September 2013, two researchers from the group are moving on to faculty jobs this month, Nicolas Durrande has returned to France and Ciira Maina has taken a position at Dedan Kimathi University of Technology.
In June we held a Gaussian Process Summer School in Sheffield.
Neil is Tutorials Chair for NIPS 2013. We've got a great line up of tutorials, available here.
In Computer Science Neil leads the Machine Learning Research Group. In Neuroscience he leads the Computational Biology Research Group. His research interests are in probabilistic models with applications in computational biology and personalized health.
Our CommunityML project is about teaching machine learning locally. This includes talks in schools on machine learning related subjects and a mentoring scheme, where local school students spend time in the lab mentored by one of our PhD students. Last year Nicolo Fusi mentored Adam Watts (Notre Dame High School), who used Python to analyse publication records using topic models and this year Max Zwiessele is working with Tim Slater of Airbus to mentor Jake Johnson (King Edward's School) who is looking at the aerodynamics of cycling with Python and Gaussian processes. Neil also taught on the department's Headstart Summer School and will teach in our upcoming Cutler's Ambassador's programme. You can also see a video of Neil's inaugural lecture (targeted at a general audience) here.
As well as working to bring understanding of machine learning to our local community, the group does a lot of work in the machine learning community to spread ideas and trigger debate, this includes organizing workshops (we will organize 4 in 2014) and summer schools (we will organize two in 2014) as well as teaching on summer schools, reviewing papers, editing journals etc..
discipulus est prioris posterior credulitatis
-Neil Lawrence 2013 (modified, probably incorrectly, from Publilius Syrus c 50 BC)
They say that Understanding ought to work by the rules of right reason. These rules are, or ought to be, contained in Logic; but the actual science of Logic is conversant at present only with things either certain, impossible, or entirely doubtful, none of which (fortunately) we have to reason on. Therefore the true Logic for this world is the Calculus of Probabilities, which takes account of the magnitude of the probability (which is, or which ought to be in a reasonable man's mind). This branch of Math., which is generally thought to favour gambling, dicing, and wagering, and therefore highly immoral, is the only ‘Mathematics for Practical Men’, as we ought to be.
—James Clerk Maxwell in a letter to Lewis Campbell, circa July 1850
pluralitas non est ponenda sine neccesitate
-William of Ockham
The law that entropy always increases, holds, I think, the supreme position among the laws of Nature. If someone points out to you that your pet theory of the universe is in disagreement with Maxwell's equations — then so much the worse for Maxwell's equations. If it is found to be contradicted by observation — well, these experimentalists do bungle things sometimes. But if your theory is found to be against the second law of thermodynamics I can give you no hope; there is nothing for it but to collapse in deepest humiliation.
—Sir Arthur Stanley Eddington, The Nature of the Physical World (1927)
Three Phase Oil Data
The three phase oil data used to be hosted by Aston, but the site seems to be down. I use this data a lot so I've put this site up on the data.
Neil's inaugural lecture was on 6th September 2012 at 17:15 in St George's Church Lecture Theatre at the University of Sheffield. The title was ‘Life the Universe and Machine Learning’. More details and an abstract can be found here.
Machine Learning as Engine Design
This year Neil taught Machine Learning and Adaptive Intelligence (COM6509 and COM4509) module and he was also the staff contact for COM3310 taught by Malcolm Beattie. For information (via Tony Cowling who was staff contact last year) on COM3310 see here.
CVPR 2012 GP Tutorial
Review of Our Edited Book
A review of the volume on "Learning and Inference in Computational Systems Biology" (edited with Mark Girolami, Magnus Rattrayand Guido Sanguinetti) has been published by Ernst Wit in Biometrics. A further review has been published by Terence Speed in The Quarterly Review of Biology (not open access unfortunately).
A blog post containing personal thoughts on machine learning and Computer Science degrees.
I'll be giving three lectures at the Machine Learning Summer School in La Palma. The details of the lectures are available here.
If you are interested in integrating MATLAB or Octave code into LaTeX, then you might be interested in MATweave. This is a solution for keeping the code you used to create your figures in your LaTeX file.
We've just appointed two post-doctoral research positions associated with our new group in Sheffield.
From 1st August 2010 Neil will be taking up a new position as a collaborative Chair between the departments of Neuroscience and Computer Science at the University of Sheffield. Neil will be based in the Sheffield Institute of Translational Neuroscience. Neil will be joined there by his colleague Magnus Rattray. We will co-lead research groups in machine learning and computational biology.
An edited volume on "Learning and Inference in Computational Systems Biology" is out with MIT Press. Neil edited it with Mark Girolami, Magnus Rattray and Guido Sanguinetti. on Learning in Computational and Systems Biology. It originally emerged from our PASCAL Thematic Programme and the follow on workshops. The MIT Press sites here.
In Autumn 2011, with Trevor Cohn, Neil taught the Machine Learning and Adaptive Intelligence (COM6509 and COM4509) module and the Introduction to Bioengineering Module (FCE101). See also his Lecture Notes (campus only) page for more details.
AISTATS 2010 in Europe!
For the first time the AISTATS conference was held in Europe. It took place in Sardinia from May 13th-15th 2010. Further European AISTATS are planned for 2012, 2014 etc.. Neil was General Chair for the meeting and Yee Whye Teh and Mike Titterington were the Program Chairs.
Interspeech 2009 Tutorial
For details of an Interspeech tutorial on probabilistic dimensionality reduction see here.
If you are interested in doing a PhD in Machine Learning you can apply to our research group.
Neil has a number of PhD projects available:
ICML 2008 Tutorial
For details of an ICML tutorial on probabilistic dimensionality reduction see here.
Neil helped out Cédric Archambeau, Ian Roulstone, John Shawe-Taylor and Andrew Stuart in organising Approximate Inference in Stochastic Processes and Dynamical Systems.
Neil helped out Joaquin Quiñonero Candela, Masashi Sugiyama and Anton Schwaighofer in organising a NIPS workshop on "Learning when Test and Training Inputs Have Different Distributions". See the associated book from MIT Press.
Neil started the JMLR Workshop and Conference Proceedings series and I'm currently the series editor.
From October 10th 2011 until he resigned (effective October 10th 2013) Neil was an Associate Editor-in-Chief for IEEE TPAMI.
Neil is an associate editor for JMLR.
Nicholas Durrande ( BioPreDyn Project, with Magnus
Former PhD Students
Alfredo Kalaitzis (viva 3/5/13: now Post-doctoral researcher at UCL with Ricardo Silva, thesis)
Computational Health Informatics