Graduate

Director of Graduate Studies: Bei Wang
Associate Director of Graduate Studies: Paul Rosen, Aditya Bhaskara
Contact: dgs@cs.utah.edu (This e-mail is only for students already in the program; for admissions-related questions, please write to the graduate admissions e-mail: grad-admission@cs.utah.edu.) 

Graduate Advisors:
Karissa Moss (responsible for students with last names A-M)
Sammie Riley (responsible for students with last names N-Z)

Prospective students contact: grad-admission@cs.utah.edu
Current students contact: grad-advisors@cs.utah.edu

Directors of Graduate Admissions: Vijay Nagarajan & Shireen Elhabian
Contact: grad-admission@cs.utah.edu

The overall graduate program is administered by the Director of Graduate Studies (DGS), with support from the Associate Director of Graduate Studies (aDGS), and the graduate advisors.

The computer science program and the different tracks are administered by a program director (for the CS program) and track directors (for all computing tracks). These directors are usually responsible for any issues related to a student’s program of study.

The requirements of the degree program are set by the Graduate Student Handbook. The handbook is updated every year; the handbook of a particular year is valid for the students entering the program in that year.

You can find all handbooks in this folder.

Director: Haitao Wang – haitao.wang@utah.edu 

The computer science program aims to educate students in three fundamental categories: theory, systems and hardware. It is made up of three required courses in these areas, which can also be substituted by courses from the same area. See the graduate handbook for details.

Students in the computing program have to choose a track of specialization. The school of computing currently offers the following computing tracks.

Track Director: Ana Marasović – ana.marasovic@utah.edu
Track Faculty: Ziad Al-Halah, Aditya Bhaskara, Daniel Brown, Shireen Elhabian, Anna Fariha, Tom Henderson, Tucker Hermans, John Hollerbach, Weiyu Liu, Kenneth Marino, El Kindi Rezig, Alan Kuntz, Varun Shankar, Vivek Srikumar, Benjie Wang, Shandian Zhe

Artificial Intelligence (AI) is a discipline that studies the theory and methods that underlie thought and intelligent behavior and their implementation in machines.  The full AI endeavor is multidisciplinary, encompassing the study necessary to understand and develop systems that can perceive, learn, reason, communicate, and act in the world.

The AI track is designed to train students to undertake research for advancing, applying, and governing this computing technology.

Track Director: Kobus Van der Merwe – kobus@cs.utah.edu
Track Faculty: Rajeev Balasubramonian, Erik Brunvand, Neil Cotter (ECE), Priyank Kalla (ECE), Sneha Kumar Kasera, John Regehr, Ponnuswamy (Saday) Sadayappan, Brent Stephens, Ken Stevens (ECE)

Computer Engineering is a discipline that combines elements of both Electrical Engineering and Computer Science. Computer engineers design and study computer systems at many levels from the circuits that make up computers, to the architecture of processors and subsystems, to the programming interfaces of those processors.

Track Director: Shandian Zhe – zhe@cs.utah.edu
Track Faculty: Aditya Bhaskara, Anna Fariha, Lajos Horvath (Math), Chris Johnson, Sneha Kumar Kasera, Mike Kirby, Marina Kogan, Alexander Lex, Braxton Osting (Math), Valerio Pascucci, Bei Wang Phillips, Jeff Phillips, El Kindi Rezig, Vivek Srikumar, Blair Sullivan

The rate at which scientists and businesses are producing data is increasing at a unstoppable rate. Being able to efficient process and make sense of such data has become a key scientific challenge in computer science. Not only must one be able to store such information compactly, but one additionally must develop algorithms to process it efficiently and intelligent systems that can reason about this data to find interesting patterns or make decisions. These topics form the core of the Data Management and Analysis track.

Track Director: Cem Yuksel – cem@cemyuksel.com
Track Faculty: Martin Berzins, Kate Isaacs, Chris Johnson, Mike Kirby, Joshua Levine, Valerio Pascucci, Paul Rosen, Bei Wang Phillips

The graphics and visualization track includes research efforts in most areas of computer graphics, including geometric modeling, CAD/CAM, isogeometric analysis, scientific visualization, biomedical visualization, information visualization, visual analytics, computer vision, terrain modeling and rendering, haptics (force-feedback), realistic rendering, physically-based simulation, real-time rendering, GPU programming, computer animation, digital geometry processing, immersive environments, visual perception and spatial cognition.

Track Director: Elaine Wiese– eliane.wiese@utah.edu
Track Faculty: Daniel Brown, Erik Brunvand, Yue Jiang, Marina Kogan, Vineet Pandey, Sameer Patil, Jason Wiese

The purpose of the HCC track is to train students to understand and create digital products that reflect and improve people’s capabilities, goals, and social environments. Students will learn to conduct original, rigorous research through interdisciplinary training in computer science, behavioral and social sciences, and design, and specifically in the use of user-focused methods and methodologies.

Track Director: Shireen Elhabian – shireen@sci.utah.edu
Track Faculty: Ziad Al-Halah, Tom Henderson, Sarang Joshi, Tolga Tasdizen

The School of Computing has image analysis research efforts in a wide variety of areas with a strong focus on biological and medical research but also significant efforts in other rapidly expanding areas such as geosciences. Most of these projects are multi-disciplinary and/or nationwide activities that provide unique opportunities for students to get a broader insight into research and engineering concepts and into the challenges and rewards of collaborative research.

Track Director: Daniel Brown – dsbrown@cs.utah.edu
Track Faculty: Jake Abbott (ME), Ziad Al-Halah, Tom Henderson, Tucker Hermans, Alan Kuntz, Weiyu Liu, Tommaso Lenzi (ME), Steve Mascaro (ME), Mark Minor (ME), Vivek Srikumar

The Robotics Track is a program of study that may be taken either in the School of Computing or the Department of Mechanical Engineering. The field of robotics has expanded tremendously since its early focus on industrial robots and now includes a variety of topics such as autonomous vehicles, medical robots, smart sensor networks, micro-robots, robot vacuum cleaners, sentry robots, and pet robots.

Track Director: Varun Shankar – shankar@cs.utah.edu
Track Faculty: Martin Berzins, Mary Hall, Tom Henderson, Chris Johnson, Mike Kirby, Joshua Levine, Pavel Panchekha, Valerio Pascucci, Ponnuswamy (Saday) Sadayappan

The Scientific Computing track trains students to perform cutting edge research in all of the aspects of the scientific computing pipeline: mathematical and geometric modeling; advanced methods in simulation such as high-performance computing and parallelization; numerical algorithm development; scientific visualization; and evaluation with respect to basic science and engineering.

Track Director: Sneha Kumar Kasera – kasera@cs.utah.edu
Core Faculty: Sneha Kumar Kasera, Stefan Nagy, Sameer Patil, Pratik Soni, Jun Xu, Mu Zhang
Associate Faculty: Aditya Bhaskara, Anton Burtsev, Eric Eide, Ganesh Gopalakrishnan, Pavel Panchekha, Jeff Phillips, John Regehr, Rob Ricci, Vivek Srikumar, Ryan Stutsman, Kobus Van der Merwe, Eliane Wiese, Jason Wiese

The Computing Track in Secure Computing rigorously prepares graduate students for careers in cybersecurity research and development. It provides students with both a solid foundation of cybersecurity principles and hands-on practice of cutting-edge technologies. It offers practical experience in techniques for detection and analyses of cyberattacks, and for effective prevention, response, and recovery. The human aspects of security and privacy are addressed along with cyber operation including crime investigation and digital forensics. Students will also be exposed to business aspects of security and privacy, specifically aspects of cybersecurity risk and compliance, through a collaboration with the David Eccles School of Business at the University of Utah.

The PhD degrees are research focused and typically take five years to complete. Students are supported financially throughout their graduate career via a combination of teaching assistantships, research assistantships, and fellowships, conditional on good progress.

The MS degrees typically take two years and can be completed as a thesis or non-thesis degree. The degrees provide comprehensive courses and research experience. MS students have the opportunity to apply for funding as teaching assistants or research assistants.

The PhD and MS degrees assume a completed undergraduate education in computer science or a related field.

The PhD and MS degrees are offered in Computer Science, and in Computing. In the Computing program, students select a track for specialization.

The Master of Software Development (MSD) degree is is a comprehensive and rigorous 16-month STEM program producing capable coders, big data analysts, computer security experts, and more for graduates looking to carve out a new career path. It’s also the perfect next step for those with no CS background who want to enhance their careers by learning software development. Please refer to the MSD page for more details.

Certificate programs allow students in other departments to learn about a particular topic in depth and receive a certificate for completing the program. The certificate goes on the official transcript.  Many of the classes in the certificate programs will be video recorded and live-streamed and made available soon after each class. This will help professional students on a busy schedule from falling behind if they miss a class, and will allow all students to easily review the material as presented in the lecture.

The Kahlert School of Computing currently offers four Graduate Certificate Programs:

• Graduate Certificate in Data Science
• Graduate Certificate in Deep Learning
• Graduate Certificate in Secure Computing
• Graduate Certificate in AI & Robotics

Up to 15 credits from courses taken in a certificate program can later be used in a graduate program.

If you’re interested in attending graduate school in the School of Computing, please see our graduate admissions information.

For questions related to the PhD and MS program, refer to the Graduate FAQ.

For questions related to the MSD Program, refer to the MSD page.

For questions related to the certificates, see the respective certificate pages.