Machine Learning

Polo Chau headshot

Machine learning (ML) focuses on the development of computer programs that can teach themselves and act without the need for explicit programming when encountering new information or examples. The process of ML is similar to that of data mining in that both systems search data for patterns. However, instead of simply mining data for humans to interpret, ML programs use that data to redirect or adapt their own actions. ML is one of several components of artificial intelligence.

Research in this area explores the construction and study of algorithms that build models and make data-driven predictions or decisions. It is a useful, rapidly evolving sub-field of computer science that nearly all CSE faculty incorporate into their research. There are a wide range of applications, including recognizing images, characters, and spoken language; categorizing messages; diagnosing and treating complex diseases such as asthma and cancer; detecting fraud; and predicting the responses of humans, natural events, and other dynamic processes.

ML spans many broad research areas and groups at GT. In addition to CSE, the Machine Learning at GT group includes the schools of Computer Science, Interactive Computing, Industrial and Systems Engineering, Mathematics, and Electrical and Computer Engineering, as well as a full ML-dedicated center called ML@GT.

Interdisciplinary CSE Faculty specializing in machine learning research: