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Other than CS department’s funding, our faculty frequently receive outside funding for research and education that provide excellent research opportunities for students.

Our faculty receive funding from multiple agencies, such as South Dakota Competitive Research Grant Program (SDCRGP), Department of Education (DOE) and National Science Foundation (NSF). Besides, our students frequently receive research and creative scholarships from both categories: undergraduate and graduate.

The Computer Science Department is primarily focused on algorithms, artificial intelligence, machine vision, machine learning, pattern recognition, data science, information retrieval, internet of things, cyber security and big data. Applications are ranging from healthcare to risk management.

Our department is composed of award-winning faculty and students. A few of these prestigious awards/honors include the President’s Research Excellence Award (2019) and Undergraduate Research Excellence Awards (2018 – 2019).

If you are interested to work with our faculty, we would consider if you have experience on topics such as algorithms, programming science, AI and machine learning.

Brown Bag Research Talk Series

The Computer Science Department hosts a brown-bag research talk series in a relaxed and an informal setting. The talks are aimed to solely focus on AI-related research domains. Our speakers are potentially industry professionals and academic research professors/scientists.

We are not limited to computer science professors/scientist for a talk, instead, we are open to “open-eye” talks from other domains that can relate to the computer science market. Such talks are free and open to public.

If you are interested, please contact the Chair of the Computer Science Department at

Besides, computer science students organize meetings (with clubs such as ACM-USD and Code Club), where industry professionals are their main focus.

Szilard Vajda

Tuberculosis Detection in Chest X-Ray Images Using Small Data Collections

February 4, 2 – 3 PM (Central Time)
Zoom Meeting Space

Speaker: Szilard Vajda, Ph.D.
Assistant Professor, Central Washington University, WA

Dr. Vajda is a multilingual scholar serving as an Assistant Professor at the Computer Science Department at Central Washington University. He is conducting research in machine learning, pattern recognition, high-performance computing, etc. and he is actively involved in supervising graduate and undergraduate students. He holds a Ph.D. in Computer Science from the University of Lorraine in France and a B.S. in Computer Science from the University of Babes-Bolyai in Romania.

Mark Montgomery

Metamorphic Transformation with Enterprise-Wide Artificial Intelligence

November 19, 2 – 3 PM (Central Time)
Zoom Meeting Space

Speaker: Mark Montgomery

Mark Montgomery is the founding, chief executive officer and chairman of the board of the company. He is the inventor of the now patented AI system that serves as the foundation for the KYield OS, as well as the patent-pending Synthetic Genius Machine. Mark has been a pioneer in cloud computing and AI systems since the 1990s. He was formerly an entrepreneur, consultant and early-stage venture capitalist.

Justin Smith Headshot

Machine Learning in Healthcare

Thursday, Oct. 29, 2 – 3 PM (Central Time)
Zoom Meeting Space

Speaker: Justin Smith, Ph.D.
Senior Director Advanced Analytics,  St Luke’s Health System

Justin Smith, Ph.D. leads and functions in many capacities as Senior Director of Advanced Analytics for St. Luke’s Health System in Boise, Idaho. St. Luke’s is a 3 billion dollar organization and Idaho’s largest employer. As an experienced leader Dr. Smith leads multidisciplinary teams to build machine learning models that enable St. Luke’s to improve clinical care and better understand business drivers. Dr. Smith employs a unique skill set of strong analytical skills and thought leadership as St. Luke’s transitions from the world of advanced analytics to artificial intelligence. Dr. Smith has published numerous articles in peer-reviewed international journals and regularly reviews work in the fields of Machine Learning, Artificial Intelligence and Healthcare. He holds a Ph.D. in the field of Neuroscience and a M.S. and B.S. in Research Psychology.