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Cognitive Science

Cognitive science is an interdisciplinary effort to understand and explain the mind. It draws on knowledge from psychology, computer science, philosophy, linguistics, anthropology, neuroscience, and biology.

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Office of Graduate Admissions
Bendetson Hall
Medford, MA 02155
(617) 627-3395
gradadmissions@tufts.edu

Cognitive Sciences Ph.D. Program

  • Ph.D. in Psychology: Cognitive Science 

Indicate "Cognitive Science" on application.

  • Ph.D. in Child Study and Human Development

Enroll in Cognitive Sciences program after matriculation.

  • Ph.D. in Computer Science

Indicate "Cognitive Science" on application.

  • Ph.D. in Education: Cognitive Science 

Indicate "Cognitive Science" on application.

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.

In recent years, Tufts has built up a world-renowned faculty in Cognitive Science, some of whom have been prominent since the beginnings of the field. The new joint Ph.D. program has particular interdisciplinary strength in the area of human language, including theoretical linguistics, psycho- and neurolinguistics, reading and dyslexia, and computational linguistics, and it offers considerable expertise as well in other traditional subareas of cognitive science including animal cognition, human memory, behavioral/cognitive/affective neuroscience, cognitive modeling, robotics, and human computer interaction.

Learn more about the Cognitive Science Program

 

Ph.D. in Child Study and Human Development: Cognitive Science Learning Objectives
  • Students will have a knowledge base that reflects mastery of important areas in field of child development.
  • Students will have knowledge of methodologies and working ability in statistical techniques used in applied child development research.
  • Students will demonstrate ability to assume the role of a professional in the field.
  • Students will have exposure, experience with, and develop expertise in, the conduct of research in the field of Applied Child Study and Human Development.
  • Students will gain experience in the process of reading and critically evaluating empirical research, and in preparing their own work for publication.
  • Students will gain experience in the evaluation, preparation, and submission of grant proposals.
  • Students will be actively engaged in work that promotes health and positive development among children and families.
  • Students will develop skills in communicating knowledge and supporting the intellectual growth of others through teaching and mentoring.
  • Students will demonstrate their competence in disseminating the results of their work to non-academic audiences.
  • Students will demonstrate cultural sensitivity in the conduct of research, teaching, policy work and engaging with others.
Ph.D. in Psychology: Cognitive Science Learning Objectives

The graduate program's course-work and milestone requirements have been constructed to consider the student's professional development and to foster a successful research career. Effective written communication is an essential research skill. As such, one of the main objectives of the graduate program focuses on effective written communication of scientific research. To achieve this objective, students receive extensive feedback on writing from personalized faculty committees

  • Written communication—students will gain facility in written scientific communication.
  • Oral communication—students will gain facility in oral scientific communication.
  • Synthesizing psychological research literature—students will gain facility in understanding scientific research from theoretical and methodological perspectives.
  • Independent scientific research—students will move toward conducting independent and peer-collaborative scientific research.
  • Statistical competence—students will learn fundamentals of promoting and responding to the broader research community about their work
  • Teaching competence—students will learn fundamentals involved with teaching courses in psychology.

Faculty

Shuchin Aeron - Associate Professor
Shuchin Aeron
Associate Professor
Ph.D. , Boston University
Technical foci: Statistical Signal Processing (SSP), Inverse Problems, Compressed Sensing, Information Theory, Convex optimization, Machine learning; Application areas: Algorithms for geophysical signal processing, Compressed Sensing architectures and evaluation, video and Image data acquisition and processing, bioengineering-metabolic networks
Marina Bers
Professor
Ph.D. , Massachusetts Institute of Technology
Educational technology and Impact of new technologies for personal, social, and moral development
Bruce Boghosian
Professor of Mathematics
Ph.D. , University of California, Davis
Theoretical and computational fluid dynamics, quantum computation
Bárbara M. Brizuela
Professor and Dean of Academic Affairs
Ph.D. , Harvard University
Mathematics education, early childhood education, and cognitive development
Ming Chow
Associate Teaching Professor
M.S. , Tufts University
Game Development, Online Game Security, Web Application Security, Computer Science Education
Robert Cook
Professor, Dean of Graduate School of Arts and Sciences
Ph.D. , University of California, Berkeley
Animal Cognition and Learning
Alva Couch
Associate Professor
Ph.D. , Tufts University
Policy-Based Languages for System and Network Administration, Support Tools for Teaching Hands-On Computer Science
Lenore Cowen
Professor
Ph.D. , Massachusetts Institute of Technology
Graph Algorithms, Distributed Algorithms, Approximate Routing, Classification and Clustering For High-Dimensional Data, Coloring and Its Generalizations, Computational Molecular Biology
Gregory R. Crane
Professor & Winnick Family Chair in Technology and Entrepreneurship
Ph.D. , Harvard University
Greek and Latin language and Digital humanities
Ethan Danahy
Research Assistant Professor
Ph.D. , Tufts University
Educational Technology, Collaboration, Robotics, Makerspaces, Hands-on learning, Project-based learning
Fahad Dogar
Associate Professor
Ph.D. , Carnegie Mellon
Mobile Computing, Cloud Computing, Internet Architecture and Protocols
Calvin Gidney
Calvin Gidney III
Associate Professor
Ph.D. , Georgetown University
Linguistics and Language of African American children
Samuel Guyer
Associate Professor
Ph.D. , University of Texas, Austin
Compiler-Assisted Memory Management
David Hammer
Professor and Chair
Ph.D. , University of California
Physics education; Director of the Institute for Research on Learning and Instruction
Soha Hassoun - Professor
Soha Hassoun
Professor
Ph.D , University of Washington
Computational methods for systems biology and metabolic engineering, Computer-aided design for integrated circuits
Mark Hempstead
Mark Hempstead
Associate Professor
Ph.D. , Harvard University
Computer Architecture, Computer Systems, Power-Aware Computing, Embedded Systems, Mobile Computing
Ray Jackendoff
Seth Merrin Professor of Philosophy
Ph.D. , Massachusetts Institute of Technology
Natural language semantics and Syntax
Robert J. K. Jacob
Professor
Ph.D. , Johns Hopkins
Human-Computer Interaction, New Interaction Techniques and Media, Tangible User Interfaces,Virtual Environments, User Interface Software, Information Visualization, Software Engineering
Misha Kilmer
William Walker Professor of Mathematics
Ph.D. , University of Maryland, College Park
Numerical linear and multilinear algebra, inverse problems
Gina Kuperberg, Stibel Dennett Professor of Cognitive Science
Gina Kuperberg
Dennett Stibel Professor of Cognitive Science
Ph.D. , Kings College, University of London
Cognitive Neuroscience, Language (semantics), Clinical cognitive neuroscience (neuropsychiatry)
Susan Landau - Professor
Susan Landau
Professor
Ph.D , Massachusetts Institute of Technology
Cyber security policy, Communications surveillance, Privacy
Liping Liu - Assistant Professor
Liping Liu
Schwartz Family Faculty Development Assistant Professor
Ph.D , Oregon State University
Machine learning, Graphical models, Computational sustainability
Noah Mendelsohn
Professor of the Practice
Distributed Systems, Operating Systems, World Wide Web
Eric Miller - Professor and Chair of Electrical and Computer Engineering
Eric Miller
Professor
Ph.D , Massachusetts Institute of Technology
signal and image processing, inverse problems
Megan Monroe - Lecturer
Megan Monroe
Assistant Teaching Professor
Ph.D , University of Maryland-College Park
Data, Visualization, Language
Karen Panetta - Professor
Karen Panetta
Professor and Dean of Graduate Education
Ph.D. , Northeastern University
Image and Signal Processing for Security and Medical Applications, Modeling and Simulation, Multimedia
Norman Ramsey
Associate Professor
Ph.D. , Princeton University
Programming Languages and Systems, Functional Programming, Compiler Construction
Matthias Scheutz - Professor
Matthias Scheutz
Professor and Program Director
Ph.D. , Indiana University
Artificial Intelligence, Artificial Life, Cognitive Modeling, Complex Systems, Foundations of Cognitive Science, Human-Robot Interaction, Multi-scale Agent-based Models, Natural Language Processing
Mark Sheldon
Associate Teaching Professor
Ph.D. , Massachusetts Institute of Technology
Data Structures, Programming Languages, Software Systems, Software Design
Donna Slonim
Professor
Ph.D. , Massachusetts Institute of Technology
Algorithms for Mircroarray Data Analysis, Inference of Genetic Regulatory Networks, Interpretation of Biological Experiments in the Context of Genomic and Systems Information
Diane Souvaine
Professor
Ph.D. , Princeton University
Computational Geometry, Design and Analysis of Algorithms, Computational Complexity
Holly Taylor - Professor
Holly A. Taylor
Professor
Ph.D. , Stanford University
Spatial Cognition, Language, Memory
Ayanna Kim Thomas
Ayanna Kim Thomas
Dean of Research and Professor
Ph.D. , University of Washington
Memory and Aging
Heather L. Urry
Professor and Director of Graduate Studies
Ph.D. , University of Arizona
Affective Neuroscience

Application Deadline


Fall: December 1 (Child Study and Human Development), December 15 (Psychology), December 15 (Computer Science)
Spring: September 15 (Computer Science)

Currently, three departments are associated with the joint cognitive science Ph.D. program: Child Study and Human Development, Computer Science, and Psychology. Students apply to and enroll in the joint cognitive science Ph.D. program through one of these departments either as a prospective graduate student or as a current graduate student after they have been accepted by one of the departments (e.g., after they have already started their Ph.D.).

There is no separate admissions process for the cognitive science Ph.D. program. Applicants simply indicate in their application to a home department that they would like to be admitted to the cognitive science Ph.D. program. The program director will work with faculty responsible for admission in the home department to determine the applicant's eligibility. The director proposes candidates to the Steering committee, who will vote on admissions. Note that this process will not conflict with the admissions process (or criteria) in the student's home department; only students that satisfy the admissions criteria of the home department can be considered for admission into the cognitive science Ph.D. program.

Current Tufts graduate students in one of the affiliated departments can send the program director an informal petition to be admitted to the cognitive science Ph.D. program. As with prospective graduate students, the director proposes eligible candidates who meet the prerequisites for the cognitive science program to the Steering Committee which then approves admissions.

Application Requirements:


> Application Fee
> Resume/CV
> Personal Statement
> Official TOEFL, IELTS, or Duolingo English Test scores, if applicable
> Transcripts
> Three Letters of Recommendation
> GRE General Test scores not required for applicants applying to Psychology: Cognitive Science, Child Study and Human Development: Cognitive Science, and Education: Cognitive Science. If you are applying to the Computer Science: Cognitive Science program, GREs are waived for those who will have received a degree from a U.S. or Canadian institution by time of enrollment; GRE scores are required for all other Computer Science: Cognitive Science applicants.

For questions about this program, including scholarships and assistantships, please contact your graduate program director:

Computer Science/Cognitive Science
Anselm Blumer

Psychology/Cognitive Science
Gina Kuperberg

Child Development/Cognitive Science
Chip Gidney or Maryanne Wolf