Dr. Robert Kalescky

Dr. Robert Kalescky#

About#

Dr. Robert Kalescky is the Principal Computational Scientist at The Answer Project (TAP Sciences) in Dallas, Texas, where he leads the selection and application of the computational methods, datasets, AI/ML approaches, and molecular simulations used to generate and prioritize drug-development hypotheses, and translates those methods into scalable, production-grade discovery workflows. Since 2021 he has also been an Adjunct Professor of Data Science in the Department of Statistics and Data Science at SMU.

He was previously the Principal Scientist of the O’Donnell Data Science and Research Computing Institute at SMU from May 2024 to May 2025, and prior to that 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 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. His current work centers on computational drug design — structure-based molecular modeling, binding free energies, and graph-based and generative machine learning models for molecular property and activity prediction — alongside the development of scalable machine learning surrogates for quantum chemical methods. 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.

Research Interests#

  • Computational drug design and discovery: structure-based molecular modeling, binding free energies, and mechanistic hypothesis generation

  • Application of graph-based and generative models to accelerate early-stage drug discovery and molecular property and activity prediction

  • Development of scalable machine learning surrogate models for quantum chemical methods

  • High-performance implementation of deep learning architectures for analyzing large simulation and experimental datasets

  • Data-driven design and screening of functional materials for separations, catalysis, and nano-reactor applications

  • Optimization of end-to-end in silico discovery workflows for cheminformatics and materials science on GPU-accelerated and distributed HPC platforms

Experience#

Principal Computational Scientist – May 2025 to Present
The Answer Project (TAP Sciences)
Dallas, Texas

Adjunct Professor of Data Science – January 2021 to Present
Department of Statistics and Data Science
Southern Methodist University, Dallas, Texas

Principal Scientist – May 2024 to May 2025
O’Donnell Data Science and Research Computing Institute
Southern Methodist University, Dallas, Texas

HPC Applications Scientist – May 2015 to May 2024
Research and Data Science Services
Office of Information Technology
Center for Research Computing (Previously)
Southern Methodist University, Dallas, Texas

Postdoctoral Fellow – January 2014 to May 2015
Advising Professor: Dr. Peng Tao
Southern Methodist University, Dallas, Texas

Doctor of Philosophy in Chemistry Candidate – August 2009 to December 2013
Advising Professors: Dr. Elfi Kraka and Dr. Dieter Cremer
Computational and Theoretical Chemistry Group (CATCO)
Southern Methodist University, Dallas, Texas

Master of Science in Chemistry Candidate – August 2007 to May 2009
Advising Professor: Dr. Steven Nielsen
University of Texas at Dallas, Dallas, Texas

Education#

Doctor of Philosophy in Chemistry
Theoretical and Computational Chemistry
Southern Methodist University, Dallas, Texas
August 2009 to May 2014
Description of the Strength of Chemical Bonds Utilizing Local Vibrational Modes

Master of Science in Chemistry
Theoretical and Computational Chemistry
University of Texas at Dallas, Dallas, Texas
August 2007 to May 2009
Area Per Ligand as a Function of Nanoparticle Radius: A Theoretical and Computer Simulation Approach

Bachelor of Science in Chemical Engineering, Minors in Mathematics and Chemistry
Texas Tech University, Lubbock, Texas
August 2001 to May 2006
Prairie Grass Ethanol Production Pilot Plant Facility and Optimization

Project Management Certificate
Southern Methodist University, Dallas, Texas
December 2023

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