Computer Science at Adams State University
Get hands-on experience with cutting-edge technology while you study computer science at Adams State University. Earning a B.S. in Mathematical Sciences with a Computer Science emphasis prepares you to work in a challenging, creative, and intellectually stimulating field with outstanding opportunities for employment and advancement.
While learning the essentials of information technology, computer programming and security, you’ll acquire valuable problem-solving techniques, including how to develop mathematical models and develop effective user friendly software.
Graduates of this program become software engineers, game programmers, mobile application developers, web developers, systems administrators, and more.
Computer Science Program Highlights
Artificial Intelligence and Social and Emotional Robotics
Adams State University students have the unique opportunity to develop artificial intelligence and social-emotional programming for robots through a three-year grant of more than a half-million dollars from the Department of Defense Army Research Office (ARO). Their work will tie together with similar projects underway across the world, through scholarly collaborations developed by Dr. Matthew Ikle, professor of mathematics.
$501,159
Grant dollars for the Artificial Intelligence and Social and Emotional Robotics program.
Computer Science Program Outcomes
$50,000 – $70,000
Starting salary range for computer science graduates in 2018
72%
Computer Science graduates finding employment within six months after graduation (Forbes, 2015)
In our project-centric computer science curriculum you will be a creative problem solver working side by side with faculty in ongoing projects such as robotic emotional perception, Artificial General Intelligence (AGI), deep learning and your own senior project. Recent senior projects include a Deep Learning Fish classification system, a Capture the flag game simulation, a Robotic cat toy collector, a mobile color matching application for artists and a support vector machine learning system.
When you graduate from the Adams State computer science program you will be ready to apply state of the art technology and expertise to the ever broadening scope of computer applications. You will have hands-on experience in specific application domains you have chosen so you will be able to point your computer science career in the direction that most interests you.
ACME
Adams State Computer Science, Mathematics and Engineering Club Competes annually in Mathematics and Programming competitions Contact Dr. Steven Aldrich
SLV STEAM Shop
On-campus makerspace available to students featuring advanced fabrication equipment such as 3D printers, Laser cutters, digital electronics tools, and computer controlled metal milling. Contact George Sellman.
Porter Scholars
Competitive Scholarship
Computer Science Program Faculty
Matt Nehring, Ph.D.
Program Chair of Computer Science
George Sellman
Assistant Professor of Mathematics/Computer Science
Ahmed Shafee, Ph.D.
Assistant Professor of Computer ScienceComputer Science Program Curriculum
Explore Some of Our Courses
CSCI 104: Fundamentals of Programming (3 hours)
This course is the first course in the introductory programming sequence for computer science and information technology majors, but is suitable for non-majors interested in getting a taste of computer programming. The course covers program creation, basic control structures, variables, arithmetic expressions, functions, parameters, internal documentation, arrays and strings.
CSCI 328: Artificial Intelligence/Machine Learning (3 hours)
Provides both a brief overview of the basics of artificial intelligence and machine learning, and an in-depth investigation of selected hot topics in the field. The course will examine basic and advanced search techniques, knowledge representation, machine learning and data mining, natural language processing, and historical and philosophical issues regarding artificial intelligence. The course is a project-based course that will involve implementing and experimenting with open-source machine-learning software.
Academic Catalog