David E. Singh is Associate Professor of Computer Science at the Universidad Carlos III de Madrid which he joined in 2004. He obtained a B.Sc. in Physics (specializing in Electronics and Computing) in 1997 followed by an M.S. in High Performance Computing and Artificial Intelligence in 1999 and a Ph.D. in Physics in 2003. The PhD. topic was the development of run-time techniques for the automatic parallelization of irregular applications.
He is a member of the IEEE and ACM associations as well as the Academic Evaluation Committee for Computer Science and Engineering and Dual Bachelor in Computer Science and Engineering and Business Administration in Colmenarejo campus. He is also member of the UC3M’s Contract Evaluation Committee for the recruitment of new research assistants. His current research interests include:
- Computational epidemiology: parallel simulator that performs realistic stochastic simulations of the propagation of the COVID-19 virus across wide geographic areas.
- Performance optimization of parallel applications: leverage of runtime monitoring for optimization techniques of HPC applications on clusters and clouds. These techniques include: data reordering for improving the performance on shared memory architectures, providing malleability capacities to MPI parallel applications and reducing the communication overhead by means of compression.
- High performance I/O: improving the efficiency of parallel I/O by means of locality-aware techniques.
He is currently involved in several research projects including the coordination of the projects:
- Medium and Long-term Simulation of Covid-19 funded by the Instituto de Salud Carlos III.
- Multi-source and multi-method prediction to support COVID-19 policy decision making, which is funded by the Comunidad de Madrid with REACT-EU funds.
- Development of a tool for prediction of epidemiological scenarios and vaccination against COVID-19, funded by the Ministry of Health and Innovation.
He is also participating as researcher in the EU-funded projects European Regimen Acceleration for Tuberculosis (ERA4TB), Exascale Programming Models for Extreme Data Processing (ASPIDE) and Adaptive Multi-tier Intelligent Data Manager for Exascale (ADMIRE) as well as the Spanish-funded project New Methods in High-end and Edge Computing for Data Intensive Computing.
David E. Singh has participated as reviewer of the following journals: IEEE Transactions on Parallel and Distributed Systems, Journal of Supercomputing, International Journal of Parallel Programming, Scalable Computing: Practice and Experience, Simulation Modelling Practice and Theory, Computers & Electrical Engineering, and International Journal of High Performance Computing. He was also member of the Program Committee of the following conferences: HPCC2011, ISPA2012, HPCC2012, EUROMPI2013, ISPA2013, HPCC2013, ICA3PP2014, ISPA2014, EUROMPI2014, EUROPAR2014, C4BIO2014, CSE2014, CIT2015, ICA3PP2015, EUROMPI2015, EDUCON 2016, EUROMPI2016, CCGRID2017, EDUCON2017, EUROPAR2017, HPDC2017, ISPA2017, IJPP2018, ISPA2019, ICBDR2019, EUROPAR2020, PDP2021.