Artificial Intelligence/Machine Learning Research
Our AI Research Program delves into the intersection of methods, applications and ethics of AI. Researchers develop novel methods to enhance capabilities, transparency and interpretability of AI models. Simultaneously, the program applies these techniques to real-world challenges: the usability of computer systems by people with disabilities, science problems and ensuring that AI technology benefits society responsibly and justly.
Academics and Coursework
Students may specialize their education around Artificial Intelligence/Machine Learning topics via these undergraduate and graduate level courses, as well as in a Graduate Certificate in Ethical Artificial Intelligence.
- CSC 308: Introduction to Machine Learning for Interdisciplinary Data Scientists
- CSC 508: Machine Learning and Data Science for Personalized Medicine
- CSC 509: Data Science and Machine Learning for Medical Image Analysis
- CSC 601: Data Science and Machine Learning for Biotechnology Seminar Series
- CSC 602: Interview Preparation for Data Science and Machine Learning for Biotechnology Opportunities
- CSC 621: Natural Language Technologies
- CSC 665: Biomedical Imaging and Analysis
- CSC 671: Deep Learning
- CSC 676: Soft Computing and Decision Support Systems
CSC 820: Natural Language Technologies
CSC 821: Biomedical Imaging and Analysis
CSC 859: AI Explainability and Ethics
CSC 865: Artificial Intelligence
CSC 871: Deep Learning
CSC 872: Pattern Analysis and Machine Intelligence
CSC 874: Topics in Big Data Analysis
CSC 876: Soft Computing and Decision Support Systems
CSC 878: Big Data Platforms and Systems
CSC 890: Graduate Seminar - Advanced Artificial Intelligence
Faculty and Focus Areas
Wes Bethel
High performance computing, quantum computing, scientific computing, computer graphics, scientific visualization, artificial intelligence/machine learning, computer vision/image analysis, computer organization and architecture
Jozo Dujmovic
Computational intelligence: soft computing, graded logic, decision support systems
Anagha Kulkarni
Natural language processing, information retrieval, machine learning
Kaz Okada
Machine learning, computer vision, biomedical imaging
Dragutin Petkovic
Ethical artificial intelligence
Hui Yang
Data mining and machine learning, with a current focus on educational data mining/machine learning