Kajsa Duke, PhD, PEng

Associate Professor, Faculty of Engineering - Mechanical Engineering Dept

Contact

Associate Professor, Faculty of Engineering - Mechanical Engineering Dept
Email
kkduke@ualberta.ca
Phone
(780) 492-4710
Address
10-239 Donadeo Innovation Centre For Engineering
9211 116 St
Edmonton AB
T6G 2H5

Email
kkduke@ualberta.ca

Overview

Area of Study / Keywords

Biomechanics And Biomedical Engineering Respiratory Mechanics Orthopaedics Design And Manufacturing Advanced Manufacturing Manufacturing Management Design of Experiments


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 300 - Mechanical Measurements

Characterization and behavior of measuring systems. Statistics and analysis of measurement data; measurement techniques applied to fundamental mechanical engineering phenomena. Prerequisites: CIV E 270, ECE 209, STAT 235. Corequisite: MEC E 330 or MEC E 331.


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 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.


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