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COMPUTATIONAL SCIENCE
AN INTERDISCIPLINARY GRADUATE MINOR PROGRAM
THE PENNSYLVANIA STATE UNIVERSITY


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If you plan to pursue the Minor, submit your application soon; so we can complete the necessary paperwork. Don't wait until your final semester to apply. If you have additional questions, please contact the graduate advisor in your home department or Prof. Long (email: LNL).





WHAT IS THE COMPUTATIONAL SCIENCE GRADUATE MINOR?

The minor in Computational Science was created to provide an opportunity for graduate students in all colleges and majors to pursue a focused set of courses that emphasize all aspects of computational science. Computational science involves using computers to study scientific problems and complements the areas of theory and experimentation in traditional scientific investigation. This Minor would be a valuble program for almost any graduate student at Penn State.

Official description: The Aerospace Engineering Department administers this interdisciplinary minor. Each student.s program is planned by the student and a designated computational science adviser, in consultation with the graduate adviser in the student's major field. The minor offers an opportunity for students in all colleges and majors to pursue a focused set of courses that emphasize computational science. The minor requires 9 credits in computational science courses for a masters degree and 15 credits for a doctoral minor. All students are required to take the two-semester (3 credits total) computational science colloquium (AERSP 590). Six additional credits will be taken from AERSP 424, NUC E 530 (or CSE 557), or MATH 523. For the Ph.D. minor, six additional credits will be chosen from a list of approved courses on the Web site (www.csci.psu.edu). Each of the core courses will be offered every year. In addition, the course prerequisites can be met readily by students in science and engineering and many other disciplines. More information can be found on the Web site: http://www.csci.psu.edu.

This Grad Minor was approved by the Board of Trustees on July 14, 2006. This new Minor replaces the former Grad Minor in High Performance Computing.





WHAT COURSES DO STUDENTS NEED TO TAKE ?

The COMPUTATIONAL SCIENCE Graduate Minor requires:

Masters degree: 9 credits in COMPUTATIONAL SCIENCE courses. (all must be from the list of core courses)

Doctoral degree: 15 credits in COMPUTATIONAL SCIENCE courses. (9 must be from the list of core courses.)
NOTE: These do not have to be additional credits beyond your graduate degree requirements. When appropriate, the same course can be used to satisfy your graduate degree and the COMPUTATIONAL SCIENCE Minor. Nine of the above credits must be from the Core COMPUTATIONAL SCIENCE courses. (Note: you cannot get an M.S. Minor with a Ph.D. If you are pursuing a Ph.D. major then you have to do the Ph.D. Minor)






WHAT ARE THE CORE COURSES ?

CORE COURSES
Students must take both semesters of these (3 cr):


Students must take two of these:







WHAT OTHER COURSES CAN BE USED FOR THE PHD MINOR ?

To find out when a course is offered, please consult the Penn State Schedule of courses .

To suggest additional courses be added to this list, please send the syllabus and outline (or a weblink) to Prof. Long (LNL)

*** NOTE: Only one of the two non-core courses can be a 400-level course from this list. ***

ADDITIONAL COURSES
  • ABE 562 / EMCH 562: Boundary element analysis

  • ACS 597: Computational acoustics

  • AERSP 423: Intro. to Computational Fluid Dynamics (including AERSP 596 from Spring 2007)
  • AERSP 424: Advanced Computer Programming (CORE COURSE)
  • AERSP 440: Introduction to Software Engineering
  • AERSP 514: Stability of Laminar Flows
  • AERSP / ME 524: Homogeneous Turbulence
  • AERSP / ME 525: Inhomogeneous Turbulence
  • AERSP / ME 526: Computational methods for shear layers
  • AERSP / ME 527: Computational methods in transonic flow
  • AERSP / ME 528: Computational methods for recirculating flows
  • AERSP 529: Advanced analysis and computation of turbomachinery flows
  • AERSP 560: Finite Element Methods
  • AERSP 590: Computational Science Tools (Fall semester, 2 credits) (CORE COURSE)
  • AERSP 590: Computational Science Invited Lectures (Spring semester, 1 credit) (CORE COURSE)

  • ARCH 597A, Topics in Visualization

  • CE 541: Structural Analysis
  • CE 597: Evolutionary Algorithms

  • CH E 597: Numerical methods in chemical engineering
  • CH E 597A: Optimization in Biological Systems

  • CHEM 560: Quantum mechanical electronic structure calculations
  • CHEM 560A, Computer Simulations for Physical Scientists
  • CHEM 597B, Introduction to Computational Science and Engineering

  • CSE 418, Computer Graphics
  • CSE 511 Operating Systems Design
  • CSE 514. Computer Networks
  • CSE 530: Computer architecture
  • CSE 531: Parallel processors and processing
  • CSE 532: Multiprocessor architecture
  • CSE 543: Interconnection networks in highly parallel computers
  • CSE 550, Numerical Linear Algebra
  • CSE / MATH 551: Numerical solution of ordinary differential equations
  • CSE / MATH 552: Numerical solution of partial differential equations
  • CSE / MATH 555: Numerical optimization techniques
  • CSE / MATH 556: Finite element methods
  • CSE 557: Concurrent Matrix Computation (CORE COURSE)
  • CSE 598, Advanced Topics in Scientific Computing
  • CSE 598E / Stat 597E: Data Mining

  • EE / E SCI 456, Introduction to Neural Networks
  • EE 537: Numerical and asymptotic methods in electromagnetics
  • EE 556, Graphs, Algorithms, and Neural Networks
  • EE 597I, Intelligent Control

  • E SCI / EE 456, Introduction to Neural Networks
  • E SCI 483, Simulation and design of nanostructures
  • E SCI 497B, Brain Computer Interfaces

  • EMCH 560: Finite element methods
  • EMCH 562/ABE 562: Boundary element analysis
  • EMCH 563/ME 563: Nonlinear finite element methods

  • Geo Sci 561: Mathematical Modeling in the Geosciences

  • IE 567: Distributed Systems and Control
  • IE 578: Using simulation models for design

  • IST 597C, Advanced Topics in Databases
  • IST 597F, Simulating Human Behavior

  • MATH 523: Computational Math (CORE COURSE)
  • MATH / CSE 550: Numerical linear algebra
  • MATH / CSE 551: Numerical solution of ordinary differential equations
  • MATH / CSE 552: Numerical solution of partial differential equations
  • MATH / CSE 555: Numerical optimization techniques
  • MATH / CSE 556: Finite element methods
  • MATH 580: Applied Math I
  • Math 597B, Intro to Multigrid and Domain Decomposition

  • MatSC 597C, Computational Thermodynamics
  • MatSE 597E, Computational Materials Science II: Continuum, Mesoscale Simulations
  • MatSE 597F, Polymeric Materials: Introduction to Computational Materials Science

  • ME / AERSP 524: Homogeneous Turbulence
  • ME / AERSP 525: Inhomogeneous Turbulence
  • ME / AERSP 526: Computational methods for shear layers
  • ME / AERSP 527: Computational methods in transonic flow
  • ME / AERSP 528: Computational methods for recirculating flows
  • ME 540: Numerical solutions applied to heat transfer and fluid mechanics
  • ME 563 / EMCH 563: Nonlinear finite element methods
  • ME 597A: Grid Generation

  • METEO 526: Numerical weather prediction
  • METEO 586: Advances in numerical weather prediction

  • MNG 557: Computational Geomechanics

  • NucE 521, Neutron Transport Theory
  • NucE 525, Introduction to Monte Carlo Methods
  • NucE 530: Parallel/Vector Algorithms for Scientific Applications (CORE COURSE)

  • PHYS 527: Computational physics
  • PHYS 597: Computational physics II
  • PHYS 597B: Computer Simulation of Materials
  • PHYS 597B, Introduction to Computational Science and Engineering
  • PHYS/AERSP/CHEM/CSE/MATH 597, Introduction to Many-Body Problems and Algorithms

  • PNG 511: Numerical Solution of the Partial Differential Equations of Flow in Porous Media
  • PNG 512: Numerical Reservoir Simulation

  • Stat 515: Stochastic Processes and Simulation
  • Stat 597E/CSE 598E: Data Mining






HOW DOES A STUDENT APPLY FOR THE MINOR?

  • Students can apply online by filling out this form.
  • Students should sign up for the Minor as soon as possible. There is a fair amount of paperwork, so don't delay applying.
  • After the online submission, we will write a letter to the graduate school informing them of your intent to pursue the Minor (once this is done, there will be a "Yes" in the appropriate column in the List of Students)
  • When we are notified that the student has been aproved by the Grad School, there will be a "Yes" in the final column in the List of Students
  • Once the student has been approved, a note to this effect should appear on their transcript (this must appear on the transcript before graduation)
  • All the students pursuing the Minor should also make sure they are on the CSci-GRAD-MINOR listserver, which is how we communicate with all the students. Instructions for joining the list are at: LIST SERV LINK .








Maintained by: Prof. Lyle N. Long , The Pennsylvania State University
Last modified: Saturday, 19-Apr-2008 23:47:13 EDT
Announcements:

Six students to receive Grad Minor in Spring 2008:

  • James Han (M.S. & CSci Minor)
  • Murat Cetinkaya (Ph.D. & CSci Minor)
  • Kamalesh Bhambare (M.S. & CSci Minor)
  • Eloisa Bentivegna (Ph.D. & HPC Minor)
  • Arash Mahdavi (Ph.D. & HPC Minor)
  • Richard Medvitz (Ph.D. & HPC Minor)

Courses students could consider for Fall 2008:


www.psu.edu
www.csci.psu.edu