Milad Nazarahari, PhD, EIT
Pronouns: he, him, his
Contact
Assistant Professor, Faculty of Engineering - Mechanical Engineering Dept
- nazaraha@ualberta.ca
- Address
-
10-367 Donadeo Innovation Centre For Engineering
9211 116 StEdmonton ABT6G 2H5
Overview
Area of Study / Keywords
Biomechanics And Biomedical Engineering Mechatronics Robotic Rehabilitation Human Mechanical Systems Mechanical Systems Wearable Technologies Optimization Artificial Intelligence Bio-signal Processing Biomedical Instrumentation Human Movement Neuromechanics & Neurophysiology Control Systems
About
Research Group Website: IDEA Lab
Education
- AMTD Waterloo Global Talent Postdoctoral Fellowship, University of Waterloo, 2022
- PhD, Mechanical Engineering, University of Alberta, 2021
- MSc, Mechanical Engineering, Iran University of Science & Technology, 2014
- BSc, Mechanical Engineering, Iran University of Science & Technology, 2012
Awards (Selected)
- AMTD Waterloo Global Talent Postdoctoral Fellowship, 2021
- Honorary Izaak Walton Killam Memorial Scholarship, 2019
- Vanier Canada Graduate Scholarship, 2018
- Alberta Innovates Graduate Student Scholarship, 2017
Research
In general, I am interested in developing:
- Intelligent autonomous systems, specifically, robotic and wearable technologies for tele-assessment of human activity/health and tele-rehabilitation post-impairment.
- Heuristic and meta-heuristic optimization algorithms for solving large-scale optimization problems.
Please see the details of my research activities in our lab website: IDEA Lab
You find the list of my publications at: Google Scholar
Teaching
TBA
Announcements
Currently, there are a number of open positions for graduate students at the IDEA Lab. Please visit our website for more information.
Courses
MEC E 250 - Engineering Mechanics II
Moments of inertia. Kinematics and kinetics of rigid body motion, energy and momentum methods, impact, mechanical vibrations. Prerequisites: ENGG 130, EN PH 131 and MATH 101. There is a consolidated exam.
MEC E 694 - Applied Computational Intelligence for Engineers
Introduction to intelligent agents and environments. Examples of application of computational intelligence in engineering. Solving problems by searching. Learning through optimization. Feature selection and dimension reduction for managing real-world data. Application of learning in classification and function approximation. Data clustering. Fuzzy logic and fuzzy inference systems.