Kajsa Duke, PhD, PEng
Contact
Associate Professor, Faculty of Engineering - Mechanical Engineering Dept
- kkduke@ualberta.ca
- Phone
- (780) 492-4710
- Address
-
10-239 Donadeo Innovation Centre For Engineering
9211 116 StEdmonton ABT6G 2H5
Overview
Area of Study / Keywords
Health Technologies Human Performance Systems Product Development
About
Education:
- BSc (University of Alberta)
- MSc (University of Alberta)
- PhD (Ecole Polytechnique, Montréal)
Research
Dr. Duke’s research is in the area of biomechanics with a strong focus in orthopaedics and design. If you are interested in obtaining more detailed information please contact her directly.
Courses
MEC E 265 - Engineering Graphics and CAD
Engineering drawing and sketching, conventional drafting, computer-aided drawing in 2D and 3D, solid modelling, and computer-aided design.
MEC E 409 - Experimental Design Project I
Selected group projects in experimental measurement and mechanical design. Two to four person groups develop planning, design, testing and report writing skills on projects in applied mechanics, thermosciences and engineering management. Prerequisites: MEC E 301 and ENG M 310 or 401.
MEC E 460 - Design Project I
Part 1 of the Capstone Design Project. Working in teams, students will undertake a feasibility study and detailed design of a project which requires students to exercise creative ability, to make assumptions and decisions based on synthesis of technical knowledge, and in general, devise new designs, rather than analyse existing ones, and test prototypes for performance and durability. Prerequisite: MEC E 360, Corequisite: ENG M 401.
MEC E 590 - Statistics and Data Management for Engineers
Introduction to theoretical and applied aspects of statistics, data analytics, and data management with a focus on using coding tools for engineers.
MEC E 668 - Design of Experiments in Mechanical Engineering
Introduction to Experimental Design, with particular emphasis on mechanical engineering. Randomized factorial and fractional factorial experiments. Fitting regression models and optimization. Applications to analytical and computer models.