Kihan Park

Kihan Park, PhD

Assistant Professor

Mechanical Engineering



Textiles 213


2019Georgia Institute of TechnologyPhD
2011Korea Advanced Institute of Science and Technology (KAIST)MS
2009Korea Advanced Institute of Science and Technology (KAIST)BS


  • Robotics





Introduction to the various aspects of the mechanics of robotics, its classifications and terminologies involved. Direct and inverse kinematics of a robot manipulator are treated in detail with the application of homogeneous and Denavit-Hartenberg transformation techniques. Dynamics, control and programming of a robot manipulator are discussed with associated laboratory work.

Topical courses not offered in regular course rotation--e.g., new courses not in the catalog, courses by visiting faculty, courses on timely topics, highly specialized courses responding to unique student demand. Conditions and hours to be arranged. Prerequisites: Submission of a proposal, including the course description, goals, deliverables, time allocation and grading procedure; approval by the instructor, department chairperson, department graduate director and college dean.


Research Interests

  • Medical Robotics
  • Micro-scale Sensing/Actuation
  • Machine Learning
  • Biosignal Processing

Kihan Park is an assistant professor of the Department of Mechanical Engineering at University of Massachusetts Dartmouth. He received his Ph.D. degree in Robotics (Home Department: Biomedical Engineering) from Georgia Institute of Technology, Atlanta, GA, USA in 2019, B.S and M.S degrees in Mechanical Engineering from Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea in 2009 and 2011, respectively. His primary research interests are design/control of robotic systems, micro-scale sensing/actuation, microfabrication, and machine learning for both medical and industrial applications.

He is a recipient of Korean governmental scholarship (USD 150,000) for his doctoral education and his works have been awarded to the best student paper from IEEE MARSS 2017 and the best conference paper finalist from IEEE BioRob 2011.

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