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Washington State University Factsheets

Master of Science in Computer Science – Vancouver

Faculty working with Students: 7
Students: 23
Students receiving assistantships or scholarships: 52.17%
Priority deadline:
  • Fall January 10
  • Spring July 1
Campus:
  • Vancouver: Yes
Tests required:
  • 550 TOEFL Minimum score
  • 80 TOEFLI Minimum score
  • 7 IELTS Minimum score

Degree Description:

The Master of Science in Computer Science is a thesis program requiring a significant research project, as well as course work in the following general areas:

  • Algorithms
  • Artificial Intelligence
  • Parallel and distributed computing
  • Computer networks
  • Cloud systems
  • Computer security

 

The program has a “Cloud Computing” theme. It refers to a modern set of technologies that span core areas of Computer Science, including computer theory, systems and networks, software development, big data and artificial intelligence. Our laboratories are equipped with 4 state-of-the-art computing clusters, with a total of 24 nodes, 396 cores, and more than 120TB of networked data storage.

The Master of Science in Computer Science requires 30 credit hours, including 21 hours of graded course work and 9 credits of thesis research (CS 700).

Teaching and research assistantships are available for qualified students.

The WSU Vancouver MS in Computer Science is designed and administered separately from the MS program in Pullman. If you designate the WSU Pullman program as your main objective, you will not be automatically considered by the Vancouver program unless you submit the specific documentation requested on our “How to Apply” web page (http://encs.vancouver.wsu.edu/how-apply). Except in rare cases, only those who indicate WSU Vancouver as their main objective will be prompted to submit any missing documentation so our Selection Committee can review their completed applications.

Admission Requirements:

An undergraduate grade point average of 3.0 on a 4.0 grading scale is a minimum to be considered for admission to the MS program. A Bachelor of Science degree from an accredited program in Computer Science provides a good background for the MSCS graduate program. Students from other academic disciplines are encouraged to apply; however such students will be required to take or have taken the equivalent of the following courses: CS 317, CS 360 and CS 450, including all prerequisites for these courses.

Admission to the graduate program is a joint decision between the WSU Graduate School and the School of Engineering and Computer Science at WSU Vancouver. Submitting your application for admission to WSUV MSCS is a two-step process. Please complete both steps to ensure your application is received and reviewed by WSUV ENCS and the WSU Graduate School (how to apply- https://ecs.vancouver.wsu.edu/how-apply):

  1. Complete and submit the online application form specific to your interests in the School of Engineering and Computer Science. This form indicates your intention to apply to the Graduate School, and includes the student interest profile plus the optional application for a graduate assistantship in ENCS.
  2.  Complete and submit the online application for the WSU Graduate School. You can also find the Graduate School’s requirements and deadlines, as well as requirements for both domestic and international students.

You should be prepared to submit the following along with your application to the WSU Graduate School:

  1. Transcripts: required from all non-WSU colleges or universities you have previously attended. (Unofficial transcripts may be accepted by the Graduate School at the time of application submittal, for initial consideration purposes only.) 
  2. TOEFL scores (international students): must be sent directly from ETS to WSU. The Washington State University school code is 4705
  3. Letters of Recommendation: will be requested on-line from your references. Make sure to have your references contact information available at the time of applying.
  4. Resume
  5. Statement of Purpose

Student Learning Outcomes:

All graduates will be able to:

  1. Have a depth of knowledge in a specialty area of computer science
  2. Formulate and execute a research plan, including generating and analyzing research results
  3. Communicate effectively through oral presentations and publications
  4. Pursue professional development to meet the challenging demands and increasing responsibilities of a successful career in computer science

Faculty Members:

Bonamy, Paul, Ph.D.

Location: Vancouver

Serves as: member only of graduate committee

Research Interests

Computer security
Data integrity protection
Public-interest technology
Data management

Bozorgi, Mandana, Ph.D.

Location: Vancouver

Serves as: member only of graduate committee

Research Interests

Machine Learning:
Data mining topics including nearest neighbor classification, logistical regressions, sampling, feature selection, and high-dimensional data analysis.

Statistical machine learning:
Algorithms and data structures ,high-dimensional statistics, and concentration inequalities. Develop and analyze scalable learning algorithms for healthcare, finance, recommender systems, approximate posterior inference.

Big Data:
Develop statistical tools to understand massive amounts of “Big-Data”. Technological advances in medicine ,health data, engineering, the Internet, and finance. Use modern multivariate analysis, graphical models, statistical machine learning, and the emerging area of data integration.

Data Governance:
Identify and develop Re-Engineering solutions for current or transitional Enterprise Data Governance Processes, Pipelines and Automation/Integration priorities.

McCamish, Ben, Ph.D.

Location: Vancouver

Serves as: member only of graduate committee

Research Interests

Data management
Game theory
Entity resolution
User interaction with respect to keyword queries
Database systems that learn through interaction

Wallace, Scott, Ph.D.

Location: Vancouver

Serves as: chair, co-chair, or member of graduate committee

Research Interests

Applied machine learning

Wisniewska, Anna, Ph.D.

Location: Vancouver

Serves as: chair, co-chair, or member of graduate committee

Zhang, Xuechen, Ph.D.

Serves as: chair, co-chair, or member of graduate committee

Research Interests

File and storage systems
Operating systems
High performance computing
Cloud and distributed computing

Zhao, Xinghui, Ph.D.

Location: Vancouver

Serves as: chair, co-chair, or member of graduate committee

Research Interests

Parallel and distributed systems
Machine learning
Big data computing
Concurrency

Contact Information:

Keri Deford
Engineering and Computer Science Bldg 201B
Vancouver, WA
360-546-9424