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

Systems and Optimization

We develop and apply systems & optimization techniques with a focus on mathematical modeling, search algorithms, decision support systems, stochastic modeling, inverse problems, forecasting and data assimilation, and uncertainty quantification.

High-Performance Computing

We develop and apply high-performance computing algorithms for computationally intense search and simulation problems with a focus on parallel and distributed computing, concurrent systems, and performance analysis.

Numerical Methods

We focus on developing numerical methods for civil engineering systems including finite element and other discretization methods, particle methods, and solvers.

Software Engineering

We focus on programming methodology, formal approaches for reasoning about computer systems, and verification and validation.

Faculty

Faculty	Research Specialties
Sankar Arumugam	Stochastic methods, Hydroclimatology, Water Resources
John Baugh	Software Design, Formal Methods, Scientific Computing, Cyber-Physical Systems
Emily Berglund	Complex Systems Analysis, Systems and Optimization, Water Systems Analysis
Downey Brill	Systems and Optimization, Mathematical Programming, Environmental and Water Resources Systems Analysis
Joseph DeCarolis	Systems and Optimization, Energy Systems Analysis, Uncertainty Analysis
Casey Dietrich	Coastal Hydrodynamics, Large-Scale Modeling of Coastal Hazards, Finite elements, High-Performance Computing
Fernando Garcia	Complex Systems Analysis, Systems, and Optimization, Water Systems Analysis
Murthy G uddati	Computational Mechanics, Inverse Modeling and Optimization, Wave Propagation
Ali Hajbabaie	Traffic Engineering, Advanced Traffic Control, Traffic Flow Theory, Traffic Operations
Kevin Han	Construction automation and robotics
Mar c Hoit	Complex Systems Analysis, Systems, and Optimization, Water Systems Analysis
Jeremiah Johnson	Structural optimization, Numerical methods, High-performance computing
Kumar Mahinthakumar	High-Performance Computing, Numerical methods, Water Systems Analysis, Groundwater modeling
Dan Obenour	Stochastic methods, Water quality modeling, Geospatial modeling
Ranji Ranjithan	Structural optimization, Numerical methods, High-performance computing

C & S Introductory Video

Related Courses

Course	Course Number	Credits	Current and Planned Offerings*
Course	Course Number	Credits	Fall	Spring
Introduction to Numerical Methods for Civil Engineers	CE 536	3
Computer Methods and Applications	CE 537	3
Information Technology and Modeling	CE 538	3
Special Topics in Civil Engineering: Modeling & Analysis of Civil Eng. Systems	CE 590	3
Special Topics in Civil Engineering Computing	CE 591	3
Special Topics in Civil Engineering Computing: Design of a Robotic Computer Vision System for Autonomous Navigation	CE/CSC/ECE 592	3
Advanced Topics in Civil Engineering Computing	CE 791	1-3
High-Performance Computer Modeling	CE 791A	3
Evolutionary Computation	CE 791B	3
Inverse Modeling	CE 791C	3
Advanced Methods for Systems Analysis	CE 791D	3
Modeling Analysis of Environmental Systems	CE 775	3
Advanced Water Management Systems	CE 776	3
Stochastic Methods in Water and Environmental Engineering	CE 796	3
Probabilistic Methods of Structural Engineering	CE 724	3
Matrix and Finite Element Structural Analysis	CE 721	3

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)

High-Performance Computing Laboratory (CCEE-HPCL)
Virtual Computing Laboratory (VCL)
Computing and Systems Collaboratory (CSC)

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.