Tufts University, Doctor of Philosophy in Computer Science - Artificial Intelligence, 12 Semester(s)

Forget everything you've heard about computer science departments that limit you to a narrow path of study or herd students into large lecture halls where you get lost in the crowd. We do things differently at Tufts. Tufts Computer Science stands out from other programs due to the highly interdisciplinary nature of our research programs. Computer Science faculty actively seek interdisciplinary collaborations within Tufts School of Engineering and across the university. Funded research includes projects with civil, chemical, electrical, and biomedical engineering departments, Tufts School of Medicine, Tufts Sackler School of Biomedical Science, the Tufts Medical Center, and the departments of biology, chemistry, astrophysics, classics, child development, and psychology in Tufts School of Arts and Sciences. Learning: including foundations and algorithms for machine learning and data mining, interdisciplinary applications, and learning from natural language instructions. Knowledge representation and inference: including representation, inference algorithms and complexity analysis for... Read more

Forget everything you've heard about computer science departments that limit you to a narrow path of study or herd students into large lecture halls where you get lost in the crowd. We do things differently at Tufts. Tufts Computer Science stands out from other programs due to the highly interdisciplinary nature of our research programs. Computer Science faculty actively seek interdisciplinary collaborations within Tufts School of Engineering and across the university. Funded research includes projects with civil, chemical, electrical, and biomedical engineering departments, Tufts School of Medicine, Tufts Sackler School of Biomedical Science, the Tufts Medical Center, and the departments of biology, chemistry, astrophysics, classics, child development, and psychology in Tufts School of Arts and Sciences. Learning: including foundations and algorithms for machine learning and data mining, interdisciplinary applications, and learning from natural language instructions. Knowledge representation and inference: including representation, inference algorithms and complexity analysis for propositional problems, and for relational structured domain. Agent architectures: for simulated and robotic agents, including investigations of architectural tradeoffs and novel architectural mechanisms and algorithms for introspection and reflection, fault detection and recovery.

For more information on this course, you can get in touch with Manya Education for a detailed discussion and understanding of requirements. Just share your details and we will reach out to you for a FREE session.