5 Questions with the IDEaS Leadership Team

David Sherrill; Regents' Professor, Associate Director of IDEaS and  Director, Center for High Performance Computing

David Sherrill; Regents' Professor, Associate Director of IDEaS and

Director, Center for High Performance Computing

This week we introduce David Sherrill, Regents’ Professor in the School of Chemistry & Biochemistry with a joint appointment in the School of Computational Science & Engineering. Sherrill is also Associate Director of IDEaS and the Director of the Center for High Performance Computing at Georgia Tech.

1. What is your field of expertise and what questions, or challenges sparked your current research?

My expertise is in quantum chemistry, which is the application of quantum mechanics to problems in chemistry.  I had the great fortune to participate in a summer research program in this area as an undergraduate, and I loved its intersection of physics, chemistry, math, and computer simulation.  I am especially interested in interactions between molecules, which is relevant for solvation, crystal structures, biomolecular structure, and drug binding.  It is an area that is surprisingly hard to model, and requires high-level quantum chemistry techniques.

2. How does the field of Data Science and Engineering intersect with/impact/enhance your research?

I specialize in generating large datasets that can be used to parameterize or test approximate models.  The advent of modern machine-learning methods has allowed my group to develop very fast models of intermolecular interactions that are tremendously faster than the quantum chemistry computations that would otherwise be required to achieve a similar accuracy.

3. Why is the field of Data Science and Engineering important to the development of Georgia Tech’s broader research strategy?

Data science, machine learning, and high performance computing have enabled breakthroughs in numerous difficult research areas.  They are becoming ubiquitous components of 21st century research.

4. What are the global and social benefits of the research you and your team conduct?

Our work on machine learning models of intermolecular interactions is being used by pharmaceutical companies for improved modeling of drug binding, which will hopefully help speed up the drug discovery process.

5. What are your plans on engaging a wider GT faculty pool with IDEaS research?

Georgia Tech has a strong collaborative spirit, and many faculty in science and engineering whose research would benefit from the latest advances in data science and high performance computing.  At the same time, many of those advances are being created by GT researchers in computing.  Through IDEaS, I hope to connect more of these researchers and to foster new collaborative efforts.

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Christa M. Ernst