Scholar
J. Gregory Pauloski
Google Scholar ID: rek2K4EAAAAJ
NVIDIA (formerly at ANL and UChicago)
Citations & Impact
Citations
2,990
H-index
12
i10-index
15
Publications
20
Co-authors
0
Publications
Resume
Academic Achievements
- Doctoral Dissertation: 'Programming the Continuum: Towards Better Techniques for Developing Distributed Science Applications' [June 2025]. The abstract mentions introducing new techniques for programming distributed science applications deployed across the computing continuum.
Research Experience
- Worked at Apple, Google, and the Texas Advanced Computing Center. Research areas include:
- - Distributed Systems: Designing new programming paradigms that decouple communication from application design to enable multiple data movement methods.
- - Scalable Deep Learning: Exploring new techniques for improving deep learning training time and scalability.
- - AI for Science: Training large transformer-based language models on broad scientific literature, developing frameworks for coupling AI and simulations on exascale supercomputers, and building innovative and large-scale solutions to scientific challenges.
Education
- Completed a Ph.D. in Computer Science with Globus Labs at the University of Chicago, co-advised by Ian Foster and Kyle Chard; Bachelors in Computer Science from the University of Texas at Austin.
Background
- Computer Scientist // Software Engineer. Research interests span high-performance computing, distributed systems, and deep learning frameworks.