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Computing and Systems

Computing and Systems is a formal interdisciplinary program with faculty addressing problems throughout civil and environmental engineering.  We offer a suite of graduate and undergraduate courses including civil engineering systems, computer methods and applications, numerical methods, high-performance computing, evolutionary computation, stochastic modeling, complex adaptive systems, information technology and modeling, and inverse modeling.  Our graduates pursue careers at traditional firms, government agencies, national laboratories, and universities, as well as at companies such as SAS, Cisco, IBM, Microsoft, GE, and Intel.

Explore Our Focus Areas


FacultyResearch Specialties
Sankar ArumugamStochastic methods, Hydroclimatology, Water Resources
John BaughSoftware Design, Formal Methods, Scientific Computing, Cyber-Physical Systems
Emily BerglundComplex Systems Analysis, Systems and Optimization, Water Systems Analysis
Downey BrillSystems and Optimization, Mathematical Programming, Environmental and Water Resources Systems Analysis
Joseph DeCarolisSystems and Optimization, Energy Systems Analysis, Uncertainty Analysis
Casey DietrichCoastal Hydrodynamics, Large-Scale Modeling of Coastal Hazards, Finite elements, High-Performance Computing
Fernando GarciaComplex Systems Analysis, Systems, and Optimization, Water Systems Analysis
Murthy GuddatiComputational Mechanics, Inverse Modeling and Optimization, Wave Propagation
Ali HajbabaieTraffic Engineering, Advanced Traffic Control, Traffic Flow Theory, Traffic Operations
Kevin HanConstruction automation and robotics
Marc HoitComplex Systems Analysis, Systems, and Optimization, Water Systems Analysis
Jeremiah JohnsonStructural optimization, Numerical methods, High-performance computing
Kumar MahinthakumarHigh-Performance Computing, Numerical methods, Water Systems Analysis, Groundwater modeling
Dan ObenourStochastic methods, Water quality modeling, Geospatial modeling
Ranji RanjithanStructural optimization, Numerical methods, High-performance computing

C & S Introductory Video

Related Courses

CourseCourse NumberCreditsCurrent and Planned Offerings*
Introduction to Numerical Methods for Civil EngineersCE 5363
Computer Methods and ApplicationsCE 5373
Information Technology and ModelingCE 5383
Special Topics in Civil Engineering: Modeling & Analysis of Civil Eng. SystemsCE 5903
Special Topics in Civil Engineering ComputingCE 5913
Special Topics in Civil Engineering Computing: Design of a Robotic Computer Vision System for Autonomous NavigationCE/CSC/ECE 5923
Advanced Topics in Civil Engineering ComputingCE 7911-3
High-Performance Computer ModelingCE 791A3
Evolutionary ComputationCE 791B3
Inverse ModelingCE 791C3
Advanced Methods for Systems AnalysisCE 791D3
Modeling Analysis of Environmental SystemsCE 7753
Advanced Water Management SystemsCE 7763
Stochastic Methods in Water and Environmental EngineeringCE 7963
Probabilistic Methods of Structural EngineeringCE 7243
Matrix and Finite Element Structural AnalysisCE 7213
Dist. = Distance courses offered through Engineering Online.*Note: Course offerings are subject to change.**Note: New courses are offered as CE 591 (“Special Topics”) until they become permanent courses, at which point the course number will change. Students may register by selecting the appropriate section of CE 591.

Facilities and Centers

CaS students with Professors Emily Berglund (right) and Sarat Sreepathi (bottom) in the CCEE High-Performance Computing Lab (CCEE HPCL)

Graduate Course Requirements

The Master of Science (MS) degree requires a minimum of 30 semester hours of graduate study including up to 6 credit hours for a thesis and a final oral examination. The Master of Civil Engineering (MCE) degree requires a minimum of 30 semester hours of graduate study without a thesis.  The MS and MCE degrees require 15 and 18 credit hours in civil engineering courses respectively, of which 6 hours must be taken from a set of core courses in computing and systems. For more details check out the advising documents below.

MS degree program in Computing and Systems (advising document)

MCE degree program in Computing and Systems (advising document)

The Doctor of Philosophy (PhD) degree requires 54 credit hours of thesis or course work for students with a prior MS degree or 72 credit hours otherwise. The major component of the Ph.D. program is the preparation of a dissertation reporting the results of an original investigation that represents a significant contribution to knowledge.  For the Ph.D. degree, consult with your advisor for appropriate courses.