Future
Computing
Leading research in software and hardware development for future exascale computing and designing adaptive, self-learning neuromorphic computers for real-time data analysis.
Our world continues to be shaped by technology, with computer technology allowing for advancements in everything from more personalized and responsive healthcare to commerce increasingly reliant on the non-stop improvements in software, hardware, and machinery.
Within our college, we have experts working on new and exciting ways of computing, on improving the performance and reliability of devices, and even on making the user experience something that can be adapted to individual needs.
As smart technologies and artificial intelligence continue to play an ever-increasing role in our world, our researchers will be there.
Involved Faculty
![Jack Dongarra](/wp-content/uploads/2022/04/jack-dongarra-1.jpg)
Jack Dongarra
Professor Emeritus
Software, Hardware, or Performance
Numerical algorithms in linear algebra; parallel computing; advanced-computer architectures; programming methodology; development, testing, and documentation of high quality mathematical software; design and implementation of EISPACK, LINPACK, BLAS, LAPACK, ScaLAPACK, Netlib, PVM, MPI, NetSolve, Top500, ATLAS, and PAPI software systems.
![Michela Taufer](/wp-content/uploads/2022/04/michela-taufer-1.jpg)
Michela Taufer
Dongarra Professor
Software, Hardware, or Performance
High performance computing; scientific applications and their programmability on multi-core and many-core platforms; numerical reproducibility and stability of multithreaded applications; performance analysis, modeling, and optimization of multi-scale applications; cloud computing and volunteer computing; big data analytics and mapreduce.
![Gregory Peterson](/wp-content/uploads/2022/04/greg-peterson.jpg)
Gregory Peterson
Professor
Software, Hardware, or Performance
High performance computer architectures; computational science; performance evaluation; computer engineering; digital systems; acceleration refinement; framework for parallel computing.
![Michael Berry](/wp-content/uploads/2022/04/Berry_EECS_2011.jpg)
Michael Berry
Professor
Software, Hardware, or Performance
Scientific computing; information retrieval; data science and analytics; augmented intelligence parallel numerical algorithms; data mining; computational science and performance evaluation; visual analytics; linear systems, algebra, and algorithms.
![Micah Beck](/wp-content/uploads/2022/04/micah-beck.jpg)
Micah Beck
Associate Professor
Software, Hardware, or Performance
Parallel and distributed computing; automatic program parallelization; program development tools; distributed and fault tolerant systems; data logistics networks; data tools; the convergence of storage, networking, and optimization.
![Austin Henley](/wp-content/uploads/2022/04/Henley2021.jpg)
Austin Henley
Assistant Professor
Software, Hardware, or Performance
Software engineering; human-computer interaction; developer productivity; code comprehension; detecting anomalies in software and data; increasing collaboration among coders.
![Jian Huang](/wp-content/uploads/2022/04/jian-huang.jpg)
Jian Huang
Professor
Software, Hardware, or Performance
Large data visualization; ultrascale visualization for time-varying and multivariate data; parallel, remote and distributed visualization; large scale parallel visualization systems; exascale computing.
![James Plank](/wp-content/uploads/2022/04/james-plank.jpg)
James Plank
Professor
Neuromorphic Computing or Artificial Intelligence
Fault-tolerance; erasure codes; storage systems; distributed computing; operating systems; neural networks and reducing their size requirements; neuromorphic networks for edge computing; optimizing neuromorphic systems.
![Ahmedullah Aziz](/wp-content/uploads/2022/04/ahmedullah-aziz.jpg)
Ahmedullah Aziz
Assistant Professor
Neuromorphic Computing or Artificial Intelligence
Very large-scale integration and nanoelectronics of circuits; emerging memory devices and beyond CMOS technologies; hardware security; cryogenic circuits and quantum computing hardware; artificial intelligence and neuromorphic hardware.
![Garrett Rose](/wp-content/uploads/2022/04/garrett-rose.jpg)
Garrett Rose
Associate Professor
Neuromorphic Computing or Artificial Intelligence
Nanoelectric Circuit Design; memristors and memristive systems; emerging nanoelectronic computer architectures; hardware security and security implications of emerging computing systems; neuromorphic computing; neuromorphic networks for edge computing.
![Roger Horn](/wp-content/uploads/2022/04/roger-horn.jpg)
Roger Horn
Research Professor
Neuromorphic Computing or Artificial Intelligence
Neuromorphic computing; machine learning; image and pattern recognition; analysis of systems used in nuclear power and medical devices; indexed storage, retrieval, and analysis of data.
Recent News
Dongarra Chosen IEEE Computer Society’s Computer Pioneer for 2020
Jack Dongarra, professor of electrical engineering and computer science, was selected as IEEE Computer Society’s Computer Pioneer for 2020.
UT–ORNL Data Center Course Takes Students on a Virtual Ride through ORNL’s Supercomputing Facilities
UT–ORNL data center course takes Tickle College of Engineering students on a virtual ride through ORNL’s supercomputing facilities.
Dongarra Earns Major National Computing Honor
Jack Dongarra, distinguished professor at UT, was recently award a major computing honor from SIAM and ACM in recognition of his work.