Lecturer (= Assistant Professor)
School of Informatics
University of Edinburgh
Office: IF 3.26
Voice (W): +44 (0) 131 651 5634
at Google Scholar|
10 funded PhD positions available in Data Science! Consider studying for a PhD in the new Centre for Doctoral Training in Data Science. Application deadline (first round): 27 January 2014
Computer systems not only process more data than ever before, but are also a source of data, in particular, data that concern their own operation. My research aims at new statistical machine learning methods designed to handle data about the operation and performance of large-scale computer systems. The ultimate goal is to improve techniques for developing, managing, and debugging computer systems. I believe that this is a rich source of applications that make fundamentally new demands on learning algorithms, encouraging the development of new machine learning methods.
Also, I maintain an interest in natural language processing, including structured prediction methods, conditional random fields, and graphical modeling approches to NLP.
Although these applications are disparate, they are connected by an underlying statistical methodology. I tend toward approaches based on probabilistic models whose parameters or structure can be estimated from data, often relying on techniques for approximate inference in graphical models.
My position is funded through the Scottish Informatics and Computer Science Alliance.
My full list of publications is available. Or you might be interested in these recent highlights:
Mining Source Code Repositories at Massive Scale using Language Modeling. Miltos Allamanis, Charles Sutton. In Working Conference on Mining Software Repositories (MSR). 2013.
[ .pdf ]
Word Storms: Word Storms: Multiples of Word Clouds for Visual Comparison of Documents. Quim Castella, Charles Sutton. 2013.
[ .pdf ]
Multiple-source Cross Validation. Krzysztof Geras, Charles Sutton. In International Conference on Machine Learning (ICML). 2013.
[ .pdf ]
An Introduction to Conditional Random Fields. Charles Sutton, Andrew McCallum. Foundations and Trends in Machine Learning 4 (4). 2012.
Finally, I have a collection of brief, tutorial-style research notes.
Here are some software, Web apps, and iDevice apps that I enjoy using.
Also, I have a list of random software tips I have collected.