Artificial Intelligence & Machine Learning

At Georgia Tech, artificial intelligence (AI) and machine learning (ML) focuses on core research problems in intelligence involving fundamental advances in artificial intelligence, machine learning, and deep learning, as well as challenges in computer vision, natural language processing, and other application areas. We also study the implications of AI and ML in explainable AI, computational creativity, and fairness in the context of ML models. Finally, our faculty work where AI and ML intersect with other areas and fields such as robotics, human computer-interaction, cognitive science, and computer graphics. We advise Ph.D. and MS students in AI/ML through graduate programs in CS and ML, and we offer a broad set of undergraduate and graduate courses. 

At the undergraduate level, AI and ML are mainly found in three threads: Intelligence, People, and Devices. Popular courses include Introduction to Artificial Intelligence, Machine Learning, Computer Vision, Natural Language Understanding, Deep Learning, Knowledge-based AI, Game AI, and Cognitive Science. Graduate offerings of these courses are also available, as are specialized seminars on a range of topics in vision, language, deep learning, cognition and their intersections (e.g., Machine Learning with Limited Supervision). In addition, several courses in robotics and HCI also discuss new methods in AI or ML. 

AI and ML touch multiple areas and schools within the College of Computing, representing a large swath of faculty and research interests across the different schools. In addition to the Ph.D. program in Computer Science, Faculty in the School of Interactive Computing also participate in focused Ph.D. programs in Robotics and Machine Learning. Our faculty also lead the Institute for Robotics and Intelligent Machines (IRIM) as well as two NSF-funded National AI centers, AI-ALOE and AI-CARING.