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School of Engineering

Computer Science

Computer Science

Computer Science faculty work across research areas of: Computational and Systems Biology, Cognitive Science, HCI, Networking, Cloud Computing, Machine Learning and Data Science, Programming Languages, Robotics and Human-Robot Interactions, Analytics, and Visualization. In addition to partnerships with industries, we have collaborations with Tufts School of Medicine, Tufts School of Veterinary Medicine, Tufts School of Arts and Sciences (Classics, Philosophy, Psychology and Child Development), and other departments in Tufts School of Engineering, including Civil, Electrical, Chemical and Biological, and Biomedical.

Cognitive Science

The Cognitive Science Ph.D. program is an interdisciplinary effort to understand and explain the mind. It draws on knowledge from psychology, computer science, philosophy, linguistics, anthropology, neuroscience, and biology, among others. Cutting across the information and life sciences, cognitive science is a paradigmatic multi- and inter-disciplinary research program with enormous future societal benefits, especially as intelligent artificial agents are becoming part of our lives.

Data Science

Tufts School of Engineering is uniquely positioned to offer an interdisciplinary data science program, expanding research in the field and providing students with state-of-the-art facilities to work on projects and hone their skills. The M.S. in Data Science is offered jointly by the departments of Computer Science and Electrical and Computer Engineering.

Human-Robot Interaction

The Human-Robot Interaction M.S. and Ph.D. programs are interdisciplinary and seek to understand and improve all aspects of interactions between humans and robots. The programs call on expertise from computer science and mechanical and electrical engineering, as well as psychology, philosophy, anthropology, and legal fields, among various others.

Bioengineering - Bioinformatics

The Bioinformatics track of the Bioengineering M.S. program looks at computational approaches to biomedical problems. Students may focus in computational data analysis, systems biology, data mining, simulation and modeling, visualization, or other areas that incorporate computer science and mathematics in biological research. This track requires some undergraduate computer science as a prerequisite (Comp 15 or the equivalent). Students will work with an advisor to design a coherent program including computer science electives as well as courses in computational biology, math and biotechnology.