Our department conducts research in a variety of areas, including: artificial intelligence; bioinformatics; computer science education; information storage and retrieval; software engineering; real-time systems; networking; parallel processing; and distributed systems.
Want to learn more about what our faculty are doing? Check out the research areas below.
Current Research Areas
The Bioinformatics Lab
Dr. Aleksandar Poleksic directs research in algorithms for molecular biology and computational pharmacology. The goal of the AEONET project, linked here, is to explore large biomedical databases to predict additional associations between concepts such as genes, diseases, drugs, side effects and symptoms, to name a few.
The Computer Science Education Group
The CS Education group develops curriculum to prepare teachers to teach general computer science in the K-12 schools. It offers multiple courses to assist teachers in gaining the appropriate knowledge and experience.
The Laboratory of Security & Storage Technology (LOSST)
LOSST was founded in 2014 by Dr. Sarah Diesburg to research computer privacy issues dealing with data and storage. Specifically, they investigate specialized forensics and anti-forensics techniques for recovering, destroying, and hiding data.
Real-time Systems Lab
Real-time systems monitor, respond to, or control an external environment. This environment is connected to the computer system through sensors, actuators, and other input-output interfaces.
Systems for Next generation of Intelligent networkS (SyNthesIs)
At SyNthesIs, we develop real-world systems to solve the exciting next-gen problems with innovative and ingenious methods. Our interests span wireless networks, mobile computing, machine learning, smart spaces, and the larger Internet-of-Things.
This software enables the construction of fast, indexed, sequence retrieval programs in large genomic databases where query processing time is determined mainly by the size of the query and number of sequences retrieved rather than the size of the database.
Manipulatives are a powerful tool to help students grasp the foundational concepts of mathematics. The goal of LLAMA is to create a new toolset called motion virtual manipulatives that enable students to use motion-sensing input devices to interact with mathematics in an engaging environment.
Mumps is a general-purpose programming language that supports a native hierarchical database facility. It is supported by a large user community, mainly biomedical, and a diversified installed application software base.