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Contact Information
Dr. Christer Karlsson, Program Coordinator
Department of Mathematics and Computer Science
McLaury 211A
Dept: (605) 646-3130
E-mail: Christer.Karlsson@sdsmt.edu
www.sdsmt.edu/CSR
Faculty
Professors McGough and Weiss; Associate Professors Pyeatt, Qiao, and Riley; Assistant Professors Karlsson, Hinker, and Rebenitsch; Lecturer Schrader.
Computational Sciences and Robotics
The Master of Science in Computational Sciences and Robotics (CSR) is a distinctive degree that combines the intelligent power of the computational sciences with the cutting edge utility present in modern day robotics.
The CSR graduate program provides students with the advanced skills they will need in a rapidly evolving field. The program has the specialized courses to develop technical skills along with a strong emphasis on teamwork, including research projects which involve faculty and students from a variety of disciplines.
The core of the program covers the fundamentals and the students have the opportunity to gain advanced knowledge in focus areas such as pattern recognition, machine intelligence, simulation, computer vision, nonlinear control, digital signal processing and communications.
The primary objective of the CSR program is to give students a basic understanding of the tools required to implement intelligent systems in a dynamic context.
Two options for the degree are offered: thesis and non-thesis. The thesis program provides a research experience which is more focused. The non-thesis option provides the opportunity for students to expand their technical background with additional course work.
Graduates of this program should have a variety of career options in industrial applications, defense, homeland security, space exploration, or graduates can elect to continue their studies with a more advanced degree.
General Background
The entering student will normally have completed a four year degree (B.S.) in either computer science, computer engineering, electrical engineering, mechanical engineering, or a closely related field of study. The admission committee also expects a minimum of 3.0 GPA or higher in the undergraduate program of study. However, any capable and highly motivated student interested in this program is encouraged to apply regardless of academic background. Credit by examination may be available for certain courses. In the case of deficits in background, the student may be admitted on a probationary status while they make up missing coursework.
Mathematics Background
- Year of Calculus (Calculus I and II)
- One semester of Multivariate Calculus (Calculus III)
- Discrete Mathematics
- One semester of Linear Algebra
- One semester of Probability and Statistics
Physics Background
- Two semesters of calculus-based physics are suggested but not required.
Computing Background
- Three semesters of programming including a semester of data structures.
GRE
- Recommended but not required.
English Proficiency
International students must meet the Graduate School English requirements. See Graduate School website for details: www.sdsmt.edu/GraduateEducation