The machine learning (ML) Ph.D. program is a collaborative venture between Georgia Tech's colleges of Computing, Engineering, and Sciences. Approximately 25-30 students enter the program each year through nine different academic units.
ML@GT manages all operations and curricular requirements for the new Ph.D. Program, which include four core and five elective courses, a qualifying exam, and a doctoral dissertation defense.
See the curriculum overview for more information.
Students admitted into the ML Ph.D. program can be advised by any of our participating ML Ph.D. Program faculty.
More information about admission to the ML Ph.D. program can be found here.
More information about the program itself, including details on operations and curriculum, can be found in the ML Ph.D. Handbook and current student resources.
ML@GT Ph.D. Faculty Advisory Committee
- Aerospace Engineering (AE): Evangelos Theodorou, email@example.com
- Biomedical Engineering (BME): May Wang, firstname.lastname@example.org
- Chemical and Biomolecular Engineering (ChBE): Martha Grover, email@example.com
- Computational Science and Engineering (CSE): Polo Chau, firstname.lastname@example.org
- Electrical Computer Engineering (ECE): David Anderson, email@example.com
- Computer Science (CS): Jacob Abernethy, prof.gatech.edu
- Industrial Systems Engineering (ISyE): Yao Xie, firstname.lastname@example.org
- Interactive Computing (IC): Zsolt Kira, Zsolt.Kira@gtri.gatech.edu
- Mathematics (MATH): Vladimir Koltchinskii, email@example.com