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.
Science is the driver of our times. And though much progress has been made in science over the past fifty years, we still urgently need to make fundamental advances in science in areas of societal importance. But in every one of these areas, barriers continue to exist to making such progress. The goal of Computational Science at Microsoft is to overcome these barriers.
Some of our most important outstanding scientific challenges are: Understanding the scale, extent and consequences of current and future climate change; Understanding the extent and consequences of current and future loss of species, biodiversity and ecosystem structure and function; How to feed a global population of 10 Billion or more; How to power a planet of 10 Billion people or more; Developing the ability to predict, prevent, manage a global pandemic; Understanding how cells and multi-cellular systems work, and why and how dysfunction (disease) occurs; Understanding the brain; Understanding how the immune system works.
I have been fortunate to be able to establish a unique team and Lab and focus on developing new ways to tackle these problems. Principally, by developing a new kind of natural science, new kinds of computational methods and scientific (software) tools to underpin such a science, and a new generation of new kinds of scientists able to spearhead it. And to do so in a Laboratory that constantly asks new questions, looks at problems from new angles, and challenges prevailing scientific and technological thinking.
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 (to 2010). 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 & the Arts. I am Professor of Computational Science at the University of Oxford, Visiting Professor of Intelligent Systems at University College London and a Dinstinguished Fellow of The National Endowment for Science, Technology & the Arts.
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)
Peer-Reviewed Scientific Publications
Smith, M., Palmer, P., Purves, D., Vanderwel, M., Joppa, L., Calderhead, B., Bishop, C., & Emmott, S (2012). Enabling Actionable Projections of the Earth System (To Appear)
M. J. Smith, M. C. Vanderwel, V. Lyutsarev, S. Emmott, and D. W. Purves (2012). The Climate Dependence of the Terrestrial Carbon Cycle including Parameter and Structural Uncertainties (To Appear)
Dalchau, N. Smith, M., Martin, S., Brown, J., Emmott, S., & Phillips, A (2012). Towards the rational design of synthetic cells with prescribed population dynamics. Journal of the Royal Society Interface.
Smith, M., Palmer, P., Purves, D., Vanderwel, M., Lyutsarev, V., Joppa, L., Calderhead, B., Bishop, C., & Emmott, S (2012). What does science need to do to deliver truly actionable projections? American Geophysical Union Science-Policy Conference, Washington DC, 30th April-3rd May
M. J. Smith, D. W. Purves, M. C. Vanderwel, V. Lyutsarev, and S. Emmott. (2012). Towards accounting for all known sources of uncertainty in earth system models: fully data-constraining a global terrestrial carbon model, European Geophysical Union Annual Congress, Vienna, 22-27th April.
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.
Emmott, S. Information Superhighways. 1994. Academic Press.
S. Emmott, E. Shaprio, S. Rison, A. Phillips & A. Herbert (Eds.) Towards 2020 Science. 2006.
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.