Paul A. Navrátil

Director, Strategic Technologies

Phone: 512-471-6245 | Email: pnav@tacc.utexas.edu

Paul Navrátil is the Director of Strategic Technologies at TACC, a research scientist at The University of Texas at Austin, and faculty for the Plan II interdisciplinary honors program. As director of Strategic Technologies, he leads a team tasked with imagining the scientific workflows of 2030 and beyond, encompassing hardware, software, data, analysis and UI/UX needs; developing TACC strategy to address those needs; and implementing transformative projects to achieve that vision.

Previously, Navrátil was Director of the Visualization area at TACC, where his research interests included efficient algorithms for large-scale parallel visualization and data analytics (VDA) and innovative design for large-scale VDA systems, with particular focus on in-situ, high-fidelity visualization techniques. His recent work includes software-defined visualization capabilities, particularly the NSF-funded GraviT project, the DOE-funded Galaxy project, and the Intel supported SpRay project, which all enable large-scale distributed-memory ray tracing in various forms. This work enables photo-realistic rendering of the largest datasets produced on supercomputers today. He also developed and still maintains the TACC Analysis Portal.

Navrátil also teaches TC 310: Applied Logic and Reasoning through Programming and Data Analysis for the Plan II interdisciplinarity honors program in the College of Liberal Arts UT Austin. This course provides students with a foundation for self-education and exploration in the rich Python software ecosystem as well as experience with fundamental concepts in artificial intelligence (particularly neural networks) and the deeper implications for society and our own concept of humanity.

Education

Ph.D. Computer Science
University of Texas at Austin

M.S. Computer Science
University of Texas at Austin

B.S. Computer Science
University of Texas at Austin

B.A. Plan II
University of Texas at Austin

Areas of Research

Scientific Data Visualization

Irregular Algorithms

Parallel Systems