Neena Imam, Ph.D.

Peter O’Donnell Jr. Director, O’Donnell Data Science and Research Computing Institute | 214-768-6713 | Ford Hall for Research & Innovation, Suite 106


Neena Imam is the inaugural Director of the O’Donnell Data Science and Research Computing Institute (DSRCI) at Southern Methodist University (SMU), a position key to the university’s commitment to data-focused education and next-gen computational research. Before joining SMU, Neena Imam served as the Director of Strategic Researcher Engagement at NVIDIA corporation, the industry-leader in GPU computing and AI/ML research. In this role, Neena worked with academic researchers to enable GPU-accelerated and AI/ML applications development. Before NVIDIA, Neena served as a distinguished scientist and the Director of Research Collaboration in the Computing and Computational Sciences Directorate at Oak Ridge National Laboratory (ORNL). At ORNL, Neena performed research in HPC, as well as next-generation microelectronics and Post Moore computing.  Neena is the author/co-author of many scientific articles, served as an invited speaker and panelist at many conferences, and is active in professional organizations to promote research and education in HPC and AI.

Neena holds a Doctoral degree in Electrical Engineering from Georgia Institute of Technology, with Master's and Bachelor's degrees in the same field from Case Western Reserve University and California Institute of Technology, respectively. Neena also served as the Science and Technology Fellow for Senator Lamar Alexander in Washington D.C. (2010-2012).

Rob Kalescky

Robert Kalescky, Ph.D.

Principal Scientist, O’Donnell Data Science and Research Computing Institute | 214-768-3070  


Dr. Robert Kalescky has been an HPC Applications Scientist at SMU since 2015. As the HPC Applications Scientist, he provided consultations for the parallelization, performance optimization, and scaling of research codes for use on SMU's HPC clusters, from ManeFrame I and II to currently the NVIDIA DGX SuperPOD and M3.  He received his Bachelor of Science in Chemical Engineering from Texas Tech University in 2006, his Master of Science in Chemistry from the University of Texas at Dallas in 2009, and his Ph.D in Chemistry from SMU in 2014.  His chemical research career has spanned a wide breadth of length and time scales including some of the most accurate quantum chemical calculations published for several small molecules, large scale classical molecular dynamics simulations of nanoparticles and proteins, and ab initio molecular dynamics simulations of extremely porous materials as molecular sieves. Additionally, he has been working on the development of computationally efficient machine-learned functionals for density functional theory simulations. In 2020, he was awarded the SMU President’s Award for Innovation for his work assisting in the safe return of students to campus during the COVID-19 pandemic.

Lauren Gilmore

Lauren Gilmore

Senior Program Specialist, O’Donnell Data Science and Research Computing Institute | 214-768-6030 | 106 Ford Hall