Courses
All Courses
Graduate Courses
The School of Computational Science has developed innovative courses to support its new graduate degree
programs in computational science. The SCS classes all have an ISC number. In addition, SCS faculty
teach graduate courses in computational science listed with
different departments across campus. All graduate courses (ISC and other courses) taught by SCS faculty are listed below. They serve as core or elective courses for the school's graduate degree
programs.
[ Current SCS graduate students ]
[ Classroom Schedule ]
| Instructor:
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Gordon Erlebacher
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| Course Name:
| Applied Computational Science I
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This course provides students with high performance computational tools necessary to investigate problems arising in science and engineering with an emphasis on combining them to accomplish more complex tasks. A combination of course work and lab work will provide the proper blend of theory and practice. Problems to be investigated will be culled from the applied sciences. Example problems might be the computation and visualization of rarified gases, superconductivity or biological systems.
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Details
| Course #: | ISC 5315 |
| Semester: |
Spring 2008 |
| Room: | DSL 152 |
| Hours: | |
| Pre-requisites: | Prerequisites for this course include "Introduction to Scientific Programming" or permission of instructor. |
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| Instructor:
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Tomasz Plewa
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| Course Name:
| Verification & Validation in Computational Science
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The course will cover both theory and practice of verification and validation in computational sciences. Students will learn basic terminology, procedures used in software implementation verification and solution verification, use of exact and manufactured solutions, and basics of software quality assurance.
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Details
| Course #: | ISC 5935 - 04 |
| Semester: |
Spring 2008 |
| Room: | 468 DSL/152 DSL |
| Hours: | T 11:00 - 12:15/ W 8:50-10:50 |
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| Instructor:
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Ming Ye
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| Course Name:
| Uncertainty Analysis & Risk Management in Earth & Environment
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Theoretical foundations and practical applications of uncertainty assessment and risk analysis in earth and environmental sciences, with focus on quantification and reduction of uncertainties impacting geological and environmental processes. Explores scientific and technical uncertainty and risk analysis in support of science-based decision-making by scientists, engineers, and regulatory agencies.
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Details
| Course #: | ISC 5935 - 06/GLY 5896 -03 |
| Semester: |
Spring 2008 |
| Room: | 152 DSL |
| Hours: | T TH 3:35 - 4:50 |
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| Instructor:
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Gavin Naylor
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| Course Name:
| Introduction to Bioinformatics
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This course is for biologists and biochemists seeking to improve quantitative skills that will facilitate interpretation of their data, and students from mathematics, computer science, and other quantitative disciplines interested in learning to apply their skills in computational biology.
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Details
| Course #: | ISC 5224/BIO 4933 (05) |
| Semester: |
Spring 2008 |
| Room: | 499 DSL / 152 DSL |
| Hours: | M W 9:30- 0:45/ W 3:35 -5:45 |
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| Instructor:
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Wei Yang
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| Course Name:
| Molecular Dynamics: Algorithms and Applications
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Molecular dynamics simulation is one of major computational techniques in molecular
sciences, which range broadly in multiple disciplines including chemistry, physics, applied
mathematics, biochemistry, material science, chemical engineering, bioengineering, &
mechanical engineering etc. With the increase of computing power and the accumulation of
computing algorithms, especially in recent years, molecular dynamics simulation has been
systematically developed to be a powerful “coming of age” technique to solve the problems
in broad range of time-scale and length-scale. The goal of this course is to provide a
comprehensive introduction to molecular dynamics simulation algorithms and their
corresponding applications in molecular sciences. The course is addressed to applied
scientists, who need to understand, develop, and apply basic or advanced molecular
dynamics simulation techniques in their scientific researches. The contents incorporate both
traditional MD simulation techniques and state-of-the-art developments in very recent years
(including 2005). Hands-on computer experiments are provided to closely link lecture
contents to real-world research work. |
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Details
| Course #: | ISC 5225-01 |
| Semester: |
Spring 2008 |
| Room: | DSL 152 |
| Hours: | M/W 11:00 - 12:15 |
| Pre-requisites: | Prerequisites: Calculus I and II. Experience in Physical Chemistry class (or equally
Thermodynamics class) is preferred, but not mandatory. |
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| Instructor:
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Anter El-Azab
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| Course Name:
| Multiscale Modeling of Materials
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Mathematical and computational basis for atomic scale, mesoscale and continuum scale modeling approaches in materials science, with emphasis of atomic-to-continuum connection, statistical approaches and homogenization problems in continuum models. Concrete examples will be used to explain the basic ideas, and the students will pursue projects in which they apply the concepts discussed in the lectures.
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Details
| Course #: | ISC 5935-03 |
| Semester: |
Spring 2008 |
| Room: | 152 DSL |
| Hours: | T Th 11:00 - 12:15 |
| Pre-requisites: | In addition to having genuine interest in this topic, the students are required to have basic knowledge of atomic structure of materials, especially crystalline materials, continuum mechanics, and graduate level knowledge in engineering mathematics and/or mathematical physics. Some knowledge in numerical methods is highly desired but not required to take this course.
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| Instructor:
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Adrian Barbu
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| Course Name:
| Applied Machine Learning
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This course presents a hands -on introduction to supervised, unsupervised learning. In particular, covers support vector machines, decision trees , random forest, linear discriminant analysis, neural networks, boosting. Object detection and recognition in computer vision, medical imaging, and language processing. |
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Details
| Course #: | ISC 5935-05/STA 5934 -01 |
| Semester: |
Spring 2008 |
| Room: | 468 DSL |
| Hours: | T TH 5:15 - 6:30 |
| Pre-requisites: | Knowledge or strong willingness to learn C++ or Matlab.
Knowledge or strong willingness to learn C++ or Matlab.
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| Instructor:
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Xiaoqiang Wang
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| Course Name:
| Scientific Visualization
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Introduction to scientific and information visualization for a range of applications from meteorology to biology, astronomy and information networks. Fundamental concepts, data structures and algorithms will be presented and applied using datasets from different disciplines.
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Details
| Course #: | ISC 5935-07 |
| Semester: |
Spring 2008 |
| Room: | 152 DSL |
| Hours: | T TH 12:30 - 1:45 |
| Pre-requisites: | C/C++ programming experience
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