Spring 2019 Courses

ISC 1057
Computational Thinking
Janet Peterson
This introductory course considers the question of how computers have come to imitate many kinds of human intelligence. The answer seems to involve our detecting patterns in nature, but also in being able to detect patterns in the very way we think. This course will look at some popular computational methods that shape our lives, and try to explain the ideas that make them work. This course has been approved to satisfy the Liberal Studies Quantitative/Logical Thinking requirement.
ISC 3313
Introduction to Scientific Computing
M W F 1:25-2:15 152 DSL
Kyle Shaw
This course introduces the student to the science of computations. Topics cover algorithms for standard problems in computational science, as well as the basics of an object-oriented programming language, to facilitate the student’s implementation of algorithms. The computer language will be Java. Prerequisites: MAC 2311, MAC 2312.
ISC 4220C
Continuous Algorithms for Science Applications
M W F 9:05-9:55 152 DSL, T 3:30-6:00 (Lab) 152 DSL
Sachin Shanbhag
Basic computational algorithms including interpolation, approximation, integration, differentiation, and linear systems solution presented in the context of science problems. The lab component includes algorithm implementation for simple problems in the sciences and applying visualization software for interpretation of results. Corequisite: ISC 3222; Prerequisite: MAC 2312.
ISC 4234C/5247C
Geometric Morphometrics
T R 11:00-12:15 152 DSL
Dennis Slice
Morphometrics, or shape analysis, contributes to many diverse research areas. The shape of an organ or organism may affect its function and can reflect developmental state, ecological adaptation, and/or evolutionary history. We’ll examine the methods and tools of shape analysis with emphasis on the latest geometric methods, especially coordinate-based methods for analysis of anatomical landmark locations. Prerequisites: STA 2122, STA 2171, or equivalent.
ISC 4304C
Programming for Scientific Applications
T R 9:30-10:45 152 DSL, M 2:30-5:00 (Lab) 152 DSL
Peter Beerli
Provides knowledge of Python, which serves as a front-end to popular packages and frameworks, along with the compiled language C++. Topics include the practical use of an object-oriented scripting and compiled language for scientific programming applications. There is a laboratory component, concepts learned are illustrated in several science applications. Prerequisites: MAC 2312, COP 3014 or ISC 3313.
ISC 4933/ISC 5318
High-performance Computing
T R 2:00-3:15 152 DSL
Xiaoqiang Wang
Introduces high-performance computing, the use of parallel supercomputers, computer clusters, and software and hardware, to speed up computations. Students learn to write faster code that is optimized for modern multi-core processors and clusters, using modern software-development tools and performance analyzers, specialized algorithms, parallelization strategies, and advanced parallel programming constructs. Prerequisite: ISC 5305.
ISC 4933/ISC 5395
Iterative and Direct Solvers for Linear Systems
M W F 10:10-11:00 152 DSL
Bryan Quaife
Linear systems play a central role in countless problems including partial differential equations, inverse problems, and data analysis. Performing a matrix-vector multiplication, matrix inversion, or matrix factorization is computationally expensive if applied in its textbook form. This course will explore iterative and direct algorithms that accelerate these basic tasks. Examples of algorithms that may be covered include multigrid, fast summation methods, preconditioners, incomplete LU, interpolative decomposition, randomized algorithms, and low-rank factorizations.
ISC 5227
Survey of Numerical Partial Differential Equations
T R 11:00-12:15 422 DSL
Tomasz Plewa
This course provides an overview of the most common methods used for numerical partial differential equations. These include techniques such as finite differences, finite volumes, finite elements, discontinuous Galerkin, boundary integral methods and pseudospectral methods. Prerequisite: ISC 5305.
ISC 5316
Applied Computational Science II
T R 9:30-10:45 422 DSL, R 3:15-6:15 (Lab) 152 DSL
Tomasz Plewa
Provides students with high performance computational tools to investigate problems in science and engineering with an emphasis on combining them to accomplish more complex tasks. Topics include numerical methods for partial differential equations, optimization, statistics, and Markov chain Monte Carlo methods. Prerequisite: ISC 5315.
ISC 5473
Introduction to Density Functional Theory
T R 12:30-1:45 152 DSL
Chen Huang
The course is designed for materials scientists, chemists, physicists, and applied mathematicians who are seeking to know both the basic concept and certain advanced topics in density functional theory. Density functional theory (DFT) is widely used nowadays in both industry and academia to simulate various properties of materials and molecules, such as electronic properties, crystal structures, and chemical reactions.
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