Artificial intelligence (AI) is the general study of making intelligent machines. Machine learning (ML) is a subtopic of AI that focuses on the development of computer programs that can teach themselves and act/adapt without the need for explicit programming when encountering new information or examples.
Research in this area explores the construction and study of algorithms that build models and make data-driven predictions or decisions. It is an impactful rapidly evolving sub-field of computer science that nearly all CSE faculty incorporate into their research.
Work in AI and ML at CSE involves foundational research in deep learning, probabilistic models and reasoning, large-scale machine learning, reinforcement learning, data-driven decision making and AI/ML in science and engineering. There are significant efforts aimed at a wide range of applications, including traditional areas such as recognizing natural language, networks, speech and images; to more cutting-edge novel ones connecting to other domains such as forecasting pandemics like COVID-19; diagnosing and treating complex diseases like asthma and cancer; detecting fraud and online adversarial behavior; designing new materials; AI for social good; incentive design for solving social dilemmas; and predicting the responses of social, natural and engineered systems.
ML spans many broad research areas and groups at Georgia Tech. CSE faculty have active collaborations with several groups on campus, including researchers from the schools of Computer Science, Interactive Computing, Industrial and Systems Engineering, Mathematics, and Electrical and Computer Engineering.
Ph.D. Program in Machine Learning
Institute for Data Engineering and Science (IDEaS)