John Williams

John R. Williams, Professor of Information Engineering, Civil and Environmental Engineering, and Engineering Systems Director, MIT

Professor Williams holds a BA in physics from Oxford University, an M.Sc. in physics from UCLA, and a Ph.D. from Swansea University. His area of specialty is large scale computer analysis applied to both physical systems and to information.

Professor Williams is internationally recognized in the field of computational algorithms for large-scale particle simulators and has authored two books and over 100 publications. For the past eight years, his research has focused on architecting of large scale distributed simulation systems. He teaches graduate courses on Modern Software Development and on Web System Architecting.

Presently Professor Williams is Director of MIT's Auto-ID Laboratory and has strong involvement in the MIT Geonumerics group.

Selected Publications

1. Holmes D. W., Williams, J. R., and Tilke, P, “Smooth particle hydrodynamics simulations of low Reynolds number flows through porous media” International Journal for Numerical and Analytical Methods in Geomechanics Volume 35, Issue 4, pages 419–437, March 2011
2. Holmes D. W., Williams, J. R., Tilke, P and Leonardi, C., ” Characterizing flow in oil reservoir rock using SPH: Absolute permeability”, International Journal for Numerical and Analytical Methods in Geomechanics, Volume: 61, Issue: 7, Pages: 1-6
3. Holmes D. W., Williams, J. R., Tilke, P and Leonardi, C., “Parallel Computation Particle Methods for Multi-Phase Fluid Flow with Application Oil Reservoir Characterization”, PARTICLE-BASED METHODSComputational Methods in Applied Sciences, 2011, Volume 25, 113 134, DOI: 10.1007/978-94-007-0735-1_6
4. Leonardi, C. R., Holmes, D. W., Williams, J. R. and Tilke, P. (2011) Scalable distribution of lattice Boltzmann simulations on multicore systems. In preparation.
5. Holmes, D. W., Williams, J. R., Tilke, P. and Leonardi, C. R. (2011) Implementing particle based numerical methods on multi-core. Journal of Computational Physics.
6. Williams, J. R., Herrero, S., Leonardi, C., Chan, S., Sanchez, A., Aung, Z., Large In-Memory Cyber-Physical Security-Related Analytics via Scalable Coherent Shared Memory Architectures, Presented at IEEE Symposium Series on Computational Intelligence – SSCI 2011, Paris, France April 11-15, 2011
7. Leonardi, C. R., Holmes, D. W., Williams, J. R. and Tilke, P. (2011) Simulation of flow in oil reservoirs using smoothed particle hydrodynamics, lattice Boltzmann methods and multi-core parallelism.2ndInternational Conference on Particle-Based Methods (Particles 2011), Barcelona, 26-28 October 2011.
8. Leonardi, C. R., Holmes, D. W., Williams, J. R. and Tilke, P. (2011) A multi-core numerical framework for characterizing flow in oil reservoirs.19th High Performance Computing Symposium at the SCS Spring Simulation Multi-Conference (HPC 2011 at SpringSim ‘11), Boston, 4-7 April 2011. Awarded Best Overall Paper at the SCS Spring Simulation Multi-Conference (SpringSim ’11) Awarded Best Paper in the 19th High Performance Computing Symposium at SpringSim ‘11
9. Williams, J.R., “Sensemaking, Big Data and Geospatial Visualization”, Geospatial Cyber-Physical Supply Chain Summit 2011, Cardiff, UK. 20-23 March 2011.
10. Aung, Z., John R. Williams, Abel Sanchez, Mohamed Toukhy, and Sergio Herrero , Towards Accurate Electricity Load Forecasting in Smart Grids, The Fourth International Conference on Advances in Databases, Knowledge, and Data Applications, DBKDA 2012, February 29 – March 5, 2012 – Saint Gilles, Reunion Island
11. Aung, Z., J. Williams, A. Sanchez, M. Toukhy, and S. Herrero-Lopez, “Towards accurate load forecasting in smart power grids,” submitted to The 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Kuala Lumpur, Malaysia, May 2012.
12. Arenas-Martínez, M., S. Herrero-Lopez, A. Sanchez, J. Williams, P. Roth, P. Hofmann, and A. Zeier, “A comparative study of data storage and processing architectures for the smart grid,” in Proceedings of the First IEEE International Conference on Smart Grid Communications, pp. 285-290, 2010.
13. Aung, Z., J. Williams, A. Sanchez, M. Toukhy, and S. Herrero-Lopez, “Towards accurate load forecasting in smart power grids,” submitted to The 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Kuala Lumpur, Malaysia, May 2012.
14. Faisal, M. A., Z. Aung, J. Williams, and A. Sanchez, “Securing advanced metering infrastructure using two-layered intrusion detection system,” to be submitted to The 11th International Conference on Developments in Power System Protection – Protecting the Smart Grid, Birmingham, UK, April 2012.
15. Li, D., Z. Aung, J. Williams, and A. Sanchez, “Efficient authentication scheme for data aggregation in smart grid with fault protection,” submitted to IEEE Journal on Selected Areas in Communications, Special Series on Smart Grid Communications, 2011.
16. Li, D., Z. Aung, J. Williams, and A. Sanchez, “Efficient authentication scheme for data aggregation in smart grid with fault tolerance and fault diagnosis,” accepted for publication at The 2012 IEEE Power and Energy Society Conference on Innovative Smart Grid Technologies, Washington D.C., USA, January 2012.
17. Li, D., Z. Aung, S. Sampalli, J. Williams, and A. Sanchez, “Privacy preservation for smart metering data via accountable group key scheme,” submitted to IEEE Transactions on Smart Grids, Special Issue on Computational Intelligence Applications in Smart Grids, 2011.
18. Williams, J., S. Herrero-Lopez, C. Leonardi, S. Chan, A. Sanchez, and Z. Aung, “Large in-memory cyber-physical security-related analytics via scalable coherent shared memory architectures,” in Proceedings of the IEEE Symposium on Computational Intelligence in Cyber Security, pp. 1-9, 2011.