Bio as of 2/20/2023:

Ganesh L. Gopalakrishnan (Senior Member of IEEE and ACM Distinguished
Scientist) earned his B.Sc.(EE) degree from NIT Calicut in 1978,
M.Tech (EE) from IIT Kanpur in 1980, and PhD in Computer Science from
Stony Brook University in 1986, when he joined the University of Utah.

Prof. Gopalakrishnan's notable contribution to computer science education
is through his Jove software system that was authored by him, and is hosted
at https://github.com/ganeshutah/Jove.git . This system has been the basis
for his hands-on approach to teaching of Automata, Computability and Logic
in undergraduate and graduate classes.

He has published two textbooks: (1) Computation Engineering: Applied
Automata Theory and Logic, Springer, 2006. (2) Automata and
Computability: A Programmer's Perspective, CRC Press, 2019. He has
published over 200 refereed papers, and has graduated 25 PhD students,
and mentored 54 Undergraduate Researchers to date.

His main research interests are in correctness and reproducibility
methods for software involving floating-point operations. In this area,
he is working on binary instrumentation for GPU floating-point exception
checking, using Bayesian Optimization for triggering exceptions, and
the construction of LLVM-based floating-point analysis tools. He is also
working on data compression methods, neural-network compression, and
data race checking in shared memory parallel programs.

Prof. Gopalakrishnan maintains steady interest in computer science
foundations and formal methods, having published in the first Computer
Aided Verification conference. He blends his interest in formal methods
with pragmatic needs that arise in practical implementations of
Scientific Computing software on CPU and GPU-based machines.

His external engagements include Visiting Assistant Professorship at
the University of Calgary (1988-89) and sabbatical visits at Stanford
University (1995-96), Intel (2002-03), and sabbatical projects with
Microsoft on developing parallel computing curriculum (2009-10), and
work on textbooks using Jupyter notebooks in undergraduate Discrete
Math and Automata Theory classes (2016-17).

He is serving as the Director of the Center for Parallel Computing at
Utah ("CPU").  He was awarded one of the six "Beacons of Excellence"
Awards for 2012 by the University of Utah for his work on mentoring
undergraduates.

His PhD students have received these honors: 2020 Best Student Paper
in Supercomputing 2020 (PhD student Arnab Das); 2020 Test of Time
Honorable Mention in Foundations of Software Engineering 2020 (PhD
student Guodong Li for his paper in 2010); 2020 Nvidia Graduate
Fellowship (PhD student Vinu Joseph); and Lawrence Livermore National
Laboratory Director's 2020 Excellence in Publication (Student Category
Winner, Ph.D. Student: Michael Bentley).