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Human-Robot Interaction

As intelligent autonomous robots increasingly become part of our lives, the field of human-robot interaction seeks to understand and improve all aspects of interactions between humans and robots.

M.S. and Ph.D. Programs
A researcher reaches out to a robot in the Human-Robot Interaction Lab.
  • Degree Offerings
  • Faculty
  • Application Requirements
  • Contact the Program

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Contact us:

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

Human-Robot Interaction M.S. Programs

  • M.S. in Computer Science: Human-Robot Interaction
  • M.S. in Electrical and Computer Engineering: Human-Robot Interaction
  • M.S. in Mechanical Engineering: Human-Robot Interaction

The Departments of Computer Science, Electrical and Computer Engineering and Mechanical Engineering offer an M.S. degree in Human-Robot Interaction (HRI). Students in each department share a set of five required core courses, but other requirements vary.

Human-Robot Interaction Ph.D. Program

  • Ph.D. in Computer Science: Human-Robot Interaction
  • Ph.D. in Electrical and Computer Engineering: Human-Robot Interaction
  • Ph.D. in Mechanical Engineering: Human-Robot Interaction

Doctoral students in Human-Robot Interaction have the opportunity to build a unique degree program for themselves as they lay the foundations for future generations of researchers and practitioners working with robots. Graduating doctoral candidates will receive a joint Ph.D. in their home department and in Human-Robot Interaction.

Faculty

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
Jason Rife
Associate Professor
Ph.D. , Stanford University
Navigation, Robotics, Controls
Usman Khan
Associate Professor
Ph.D. , Carnegie Mellon University
Robotics, Signal Processing, Sensing in The Context of Distributed Estimation and Control Algorithms, Distributed, Iterative Algorithms in Random Environments
Shuchin Aeron, headshot
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: SSP algorithms for geophysical signal processing, Compressed Sensing architectures and evaluation, video and Image data acquisition and processing, bioengineering-metabolic networks
Jan P. de Ruiter
Professor
Ph.D. , Radboud University, Nijmegen
Philosophy of science, artificial intelligence, inferential statistics, social robotics
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
William Messner
John R. Beaver Professor
Ph.D. , University of California at Berkeley
Automatic Control Systems with an Emphasis on Applications to Data Storage Systems, Robotics, Microfluidics, Biological Systems and Instrumentation
Eric Miller, headshot
Eric Miller
Department Chair and Professor
Ph.D. , Massachusetts Institute of Technology
Physics-Based Signal and Image Processing and Inverse Problems, Applications Explored Include Medical Imaging and Image Analysis, Environmental Monitoring and Remediation, Landmine and Unexploded Ordnance Remediation, Homeland Security, and Automatic Target Detection and Classification
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
Chris B. Rogers
Department Chair and Professor
Ph.D. , Stanford University
Robotics, Musical Instrument Design, Engineering Education
Assistant Professor Jivko Sinapov
Jivko Sinapov
Assistant Professor
Ph.D. , Iowa State
Developmental robotics, computational perception, artificial intelligence, machine learning
Barry A. Trimmer
Professor
Ph.D. , University of Cambridge, England
Neurobiology: Cellular and Molecular Processes in Behavior
Robert D. White
Associate Professor
Ph.D. , University of Michigan
Micro- and Nano- electromechanical systems (MEMS/NEMS), Sensors, Dynamic System Modeling, Acoustics, Vibrations

Application Deadline


Spring: September 15
Fall: December 15 

Application Requirements:
> Application Fee
> Resume/CV
> Personal Statement
> Official GRE scores
> Official TOEFL or IELTS, if applicable
> Transcripts
> Three letters of Recommendation

M.S. Program

Three departments are associated with the human-robot interaction M.S. program: Computer Science, Electrical and Computer Engineering, and Mechanical Engineering. Students will enroll in the program through one of these departments.

Ph.D. Program

Three departments are associated with the joint human-robot interaction Ph.D. program: Computer Science, Electrical and Computer Engineering, and Mechanical Engineering. Students apply to and enroll in the joint human-robot interaction 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 human-robot interaction Ph.D. program. Select the home department with the human-robot interaction degree track  (i.e. Computer Science: Human-Robot Interaction (Ph.D.) ). 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 human-robot interaction Ph.D. program.

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

For questions about this program, contact:

Professor Matthias Scheutz (Computer Science)

Associate Professor Usman Khan (Electrical and Computer Engineering)

Associate Professor Jason Rife (Mechanical Engineering)