Our graduate students conduct leading-edge research, and receive high quality and technically current instruction. Our graduate program is constantly expanding and many research opportunities that are available for all computer science students in:
- Data Science: Visualization, reinforcement learning, deep learning, intelligent transportation systems applications, data quality, spatial-temporal data analysis
- Artificial Intelligence and Computer Vision: Image analysis, video analysis, audio analysis, text analysis, intelligence
- Security: Usable security & privacy, cybersecurity & online privacy, human computer interaction, deep learning
- Software and Systems: biodiversity database, data transformations, intelligent transportation systems, software engineering principles, practices, and patterns, distributed systems.
- Algorithm: Computational geometry, data structures, optimization
- Education: Online education, outreach
We provide students with a wide assortment of up-to-date equipment to support all aspects of the computer science education. There are a variety of desktop computers, workstations, and deep learning GPU computers. There are labs with the associated hardware and software for research in data science, artificial intelligence, computer vision, security, algorithms, software and systems, and education.
At the graduate level, our faculty perform research in a wide variety of fields.
- Mahdi Nasrullah Al-Ameen: Cyber Security, Usable Security and Privacy, Human-computer Interaction
- Vicki Allan: MultiAgent Systems, Outreach
- Heng-Da Cheng: Computer Vision, Pattern Recognition, Image Processing, Artificial Intelligence
- Stephen Clyde: Software Engineering, Distributed Systems, Data Integration
- Curtis Dyreson: Databases, Software Systems
- John Edwards: Data Science, Geometric Modeling, Simulation, Scientific Visualization
- Nick Flann: Data Science, Intelligent Systems, Smart Energy Technologies, Computational Biology, Bioinformatics
- Douglas Galarus: Data Science and Systems, Data Quality, Spatio-Temporal Data Analysis, Intelligent Transportation Systems
- Minghui Jiang: Theoretical Computer Science, Discrete Mathematics
- Vladimir Kulyukin: Data Science, Artificial Intelligence
- Xiaojun Qi: Image Processing, Machine Learning, Computer Vision
- Haitao Wang: Computational Geometry, Algorithms and Data Structures, Theoretical Computer Science
- Dan Watson: Algorithms for Massive Parallel Processors, Parallel Systems
- Shuhan Yuan: Data Science, Deep Learning, Representation Learning, Fraud and Spam Detection, Text Mining and Information Extraction
Data Science is an emerging area that combines research in big data, data mining, and data visualization to understand complex processes and help formulate solutions to pressing national problems in areas such as climate science, genomics, energy use, and computer security. Over the past decade, the decreasing cost of data acquisition and storage has accelerated the growth and volume of data in many disciplines. This data tidal wave has created a pressing need to develop new algorithms to convert the massive amounts of raw data to knowledge and present the knowledge in a compelling visual story. Computer scientists in the area of Data Science have developed algorithms such as deep learning, which is based on a convolution of neural networks, to make use of the massive amount of data and tools such as Tableau to derive knowledge and visualize the data.
The CS department plans to pair the PDRF student with a mentor in the area of Data Science and have a student committee populated by Data Scientists. The committee will provide the necessary institutional infrastructures to help the PDRF student to understand the research problems, challenges, and the state-of-the-art techniques and come up with novel solutions to address the challenges to achieve better performance than the state-of-the-art. The CS department at USU is building its research focus in Data Science. CS has recently added several Data Science researchers to its faculty. Assistant Professor Douglas Galarus researches data quality algorithms, and has applied his research to transportation networks and maps; Assistant Professor John Edwards is an expert in data visualization and has worked with a company to develop visualization tools; and Assistant Professor Shuhan Yuan applies deep learning to computer security, in particular, fraud detection in computer networks. These faculty join others with interest in Data Science. Associate Professor Nicholas Flann teaches reinforcement learning (a sub-area within deep learning) and applies those techniques in the areas of clean energy, bioinformatics, and financial data; and Associate Professor Vladimir Kulyukin teaches Data Science algorithms, such as deep learning, as part of his Intelligent Systems course and applies deep learning in his Bee-PI project.
The CS department was able to leverage this expertise in Data Science to create a new MS program in Data Science in Fall 2019. It will continue to hire faculty in Data Science to prepare graduate students through cross-disciplinary training to develop innovative software solutions that improve the efficiency and scope of data science tools.