Stephen Emmott
HEAD OF COMPUTATIONAL SCIENCE
.
Head of Computational Science, Microsoft
Professor of Computational Science, University of Oxford
I established, and lead, Microsoft's Computational Science research and Microsoft Research's Computational Science Laboratory in Cambridge: a diverse team of first-rate scientists developing new thinking, new computational methods and new software tools across a range of highly interdisciplinary research programmes to tackle fundamental problems in science in areas of societal importance.
Brief Biography
I studied Biological Science at the University of York between 1984-87 and did my PhD. in Computational Neuroscience under Roger Watt at the Centre for Cognitive & Computational Neuroscience, University of Stirling. I then spent three years at AT&T Bell Laboratories in the USA first as a post-doctoral fellow, then as a permanent scientist conducting research into biological computation and biologically-inspired computing in Nobel Laureate Arno Penzias' Lab. At the age of 36 I established and led, as Chief Scientist, NCR’s Advanced Research Lab. I took up my current position in 2004 to lead Microsoft’s research in computational science, establishing the Computational Science Laboratory and Research Units of collaborating groups and scientists worldwide. My Lab has become recognised for our research into novel computational approaches to advance our understanding of complex natural systems. Since 2005 we have published over 150 scientific papers in areas spanning biological computation, programming biology using DNA strand displacement, immunology, neuroscience, developmental biology, ecology, climatology and conservation biology.
I also established Microsoft's European PhD Scholarship programme and Post-Doctoral Fellowship programme to support the development of a new generation of scientists. And in addition, established two joint-research institutes, in Trento (CoSBi) and at INRIA.
In 2004 I was appointed to the UK Government’s 10 Year Science & Innovation Strategy Committee. In 2005 I was appointed as scientific advisor to the Chancellor of the Exchequer. In 2008 I was appointed to the Finnish Ministerial Science Strategy Committee. In 2009 I was appointed by the UK Science Minister as a Trustee of The National Endowment for Science, Technology and the Arts. I am Professor of Computational Science at the University of Oxford and Visiting Professor of Intelligent Systems at University College London.
Research Interests
I am interested, fundamentally, in better understanding nature, from biochemistry to the brain to the biosphere, and in the development of a new framework --new ways of thinking, a new language, new kinds of computational methods, models and tools: A framework forming the foundations of a 'new kind' of natural science: a precise, predictive science of complex living systems integrating new theory, models and data. Advancing such a science will, in my view, be fundamental to our ability to address this century's most important and pressing challenges, and equally, will form the foundations of fundamental advances in computing, energy, materials, agriculture and medicine.
I am currently working, together with colleagues, on a broad range of scientific problems to try to make a contribution to this somewhat non-trivial endeavour. These include: Novel computational, statistical and mathematical methods (Bayesian, process-based, agent-based and multi-scale modelling); The fundamentals of biological computation and cellular decision-making; The rational design and implementation of novel biological function (Programming Life); What it is that the brain actually does, and how; Ecosystem structure and function; The Earth System, in particular biotic-abiotic coupling and feedback, and the consequences and risks of anthropogenic-based changes to Earth's Life Support system.
I am also passionate about, and involved in, producing a new generation of scientists, who might today be young children or PhD students, and who we might be able to turn into tomorrow's scientific leaders and discoverers.
"It's only by reaching for the impossible do you find out what's possible." (Weber)
"The formulation of a problem is often more important than its solution, which may be merely a matter of mathematical or experimental skill. To raise new questions, new possibilities, to regard old problems from a new angle, requires creative imagination, and marks real advance in science." (Einstein & Infeld, 1937)
"A scientist should be judged not by his (papers) prizes or other honours bestowed upon him, but by the quality of the people he has helped to produce. Let these works speak for themselves." (Brenner, 2001)
Publications
Books
Emmott, S. Information Superhighways. 1994. Academic Press.
S. Emmott, E. Shaprio, S. Rison, A. Phillips & A. Herbert (Eds.) Towards 2020 Science. 2006. Microsoft.
C. Priami, L. Cardelli & S. Emmott (Eds.) Transactions on Computational Systems Biology IV, 2006. Springer-Verlag, Berlin.
Treleaven, P. & Emmott, S. Intelligent Media. In: E.H.L. Aarts and J.L. Encarnação (Eds.) The Emergence of Ambient Intelligence, 2008. Springer.
Dalchau, N., Smith. M., Martin, S., Brown, J., Emmott, S., & Phillips, A. (2012). Towards the Rational Design of Synthetic Cells with Prescribed Population Dynamics. To Appear
Lakin. M. L., Youssef, S., Polo, F., Emmott, S., & Phillips, A. (2011). Visual DSD: A design and analysis tool for DNA strand displacement systems. Bioinformatics, October 7, 2011 doi:10.1093/bioinformatics/btr543
Dalchau, N., Phillips, A., Goldstein, L.D., Howarth, M., Cardelli, L., Emmott, S., Elliott, T. & Werner, J. M. (2011). A Peptide Filtering Relation Quantifies MHC Class I Peptide Optimization, PLoS Comput Biol 7(10): e1002144. doi:10.1371/journal.pcbi.1002144
Setty Y., Chen, C.C., Secrier. M., Skoblov, D., Kalamatianos, D., & Emmott, S. (2011). How Neurons Migrate: A Dynamic In-Silico Model of Neuronal Migration in the Developing Cortex. BMC Systems Biology, 5:154
Smith, M., Purves, D., Vanderwel, M., Lyutsarev, V. & Emmott, S (2011). A Fully Data-Constrained Benchmark Global Vegetation Model for Identifying Priority Sources of Uncertainty and Facilitating Rapid Model Refinement, American Geophysical Union Symposium, San Francisco 2011.
Stepney, S. & Emmott, S. (2006). Grand Challenges in Non-Classical Computation. International Journal of Unconventional Computing 1, 4-6.
Stepney, S. & Emmott, S. (2006). Harmony-Seeking Computation. International Journal of Unconventional Computing, 1, 12-17.
Soberon, J., Emmott, S., Ferguson, N., & Sato, T. (2006). Towards Understanding Earth’s Life Support Systems. In: S.Emmott et al (Eds.) Towards 2020 Science.
Czeperski, C. & Emmott, S., (2006). New Communities for New Kinds of Science. In: S. Emmott et al (Eds.) Towards 2020 Science.
Emmott, S. (2005). Trends in Biologically-Inspired Computation. In: International Workshop on Grand Challenges in Non-Classical Computing.
Emmott, S. & Watt, R. J. (1993). Computation and Psychophysics of the Processing of Text by the Visual System. Perception, 22, 62-63.
Emmott, S. & Watt, R. J. (1992). The Visual Processing of Text: Computational and Psychophysical Investigations. European Conference on Visual Perception (ECVP ’92).
Computational Science Lab
University of Oxford
Some recent stuff that may or may not be of interest:
Science
BBC 2: Joy of Stats
Nature Medicine
Royal Society: Open Science
Royal Society: Computational Frontiers
