Senior Associate, KICP
Director of the Computational Science Division and Interim Deputy Director of the High Energy Physics Division, Argonne National Laboratory
Salman Habib is the Director of Argonne’s Computational Science (CPS) Division. He holds a joint position in Argonne’s Physical Sciences and Engineering (PSE) Directorate, the Kavli Institute for Cosmological Physics at the University of Chicago, and the Northwestern Argonne Institute of Science and Engineering (NAISE).
Salman Habib received his Ph.D. from the University of Maryland and did his undergraduate work at the Indian Institute of Technology, Delhi, India. He was a postdoc at the University of British Columbia, and later, a postdoc and staff member in the Theoretical Division at Los Alamos National Laboratory before moving to Argonne in 2011.
My research interests cover the broad sweep of classical and quantum dynamical systems, from field theories to particles, and from the largest scales to the smallest. Specifically — moving from larger to smaller scales — I have worked on problems in cosmology, astrophysics, accelerator physics, condensed matter physics, atomic and quantum optics, quantum measurement, and particle physics. Some of my more general interests include quantum dynamics of open systems, nonlinear dynamics and nonequilibrium statistical mechanics, stochastic ODEs and PDEs, and advanced statistical methods and machine learning. Although most of my work has been theoretical, I am also involved in experimental and observational projects.
For the last three decades (doesn’t seem that long!) I have been very interested in the intelligent application of parallel supercomputers to attacking physics problems. This has led to algorithm and code development in a variety of fields and on a variety of platforms, beginning with the Connection Machines in the early 1990’s and leading on to the current pre-exascale systems such as Summit at Oak Ridge and getting ready for the exascale systems Aurora and Frontier (at Argonne and Oak Ridge, respectively).
More recently I have become involved in efforts — with cosmology as the primary arena — to apply advanced statistical methods to complex inference problems where the datasets are very large (with small statistical uncertainties) and the forward model predictions involve supercomputer calculations. I am a member of the Dark Energy Spectroscopic Instrument (DESI) and the Large Synoptic Survey Telescope Dark Energy Science Collaboration (LSST DESC). I am also a science team collaborator on the SPHEREx all-sky spectral survey, selected by NASA for launch on the 2023/2024 timeframe.