Teaching

Statistical Model Estimation

(Georgia Institute of Technology, Spring 2021-Present)
This course teaches students the theoretical underpinnings and application scopes of various statistical and deterministic modeling (data-driven prediction) techniques, within the context of bioengineering and robotics research. Listed as graduate course ME 8873: Special Topics in Bioengineering at Georgia Institute of Technology, Atlanta, GA, USA in spring 2020.

Introduction to Biomechanics

(Georgia Institute of Technology, Fall 2019-Present)
This is an introductory course covering mechanics applied to biomedical engineering problems. The course provides students with basic concepts and approaches for solving deformation and dynamics problems relevant to biomedical applications. The course will focus on the application of simple models from statics, mechanics of materials, kinematics, and dynamics. Listed as undergraduate course BMED 3410: Intro to Biomechanics at Georgia Institute of Technology, Atlanta, GA, USA in fall 2020.

Fundamentals of Mechatronics

(Georgia Institute of Technology, Fall 2016-Present)
This course introduces students to microcontrollers and control of mechanical devices, with focus on microcontroller design and programming, mechanical actuators, sensors, feedback control, and system modeling. Students develop a strong fundamental understanding of microcontroller programming, analog-to-digital conversion, control of mechanical systems, feedback concepts, and embedded software development. Through several lab exercises and a final project, students will gain experience designing and constructing all aspects of mechatronics systems. Listed as undergraduate course ME 4405: Fundamentals of Mechatronics at Georgia Institute of Technology, Atlanta, GA, USA in spring 2017.

Computing Techniques

(Georgia Institute of Technology, Spring 2016)
The methods learned in this course allow engineers to efficiently solve a variety of complex, large scale, real-world engineering problems which are generally intractable using analytical approaches. These methods can be used to model and predict the behaviors of advanced engineering systems (by numerical approximation) for the purpose of design and control, and can also be used to interrogate and gain greater insight into poorly understood physical processes. Listed as undergraduate course ME 2016: Computing Techniques at Georgia Institute of Technology, Atlanta, GA, USA in spring 2016.