Teaching

I have taught undergraduates, graduates, and MBAs. My courses are interactive and equipped for digital learning. Digital learning allows distance learning students the opportunity to stay on track, and local students the opportunity to focus on interactivity when in class. Here are some example courses:

MBA: Marketing Innovation

This MBA course aims to help students understand innovation through case studies and modern analytics methods. I have acted as a course advisor for three semesters now, focusing on topics such as conjoint analysis and perceptual mapping.

I have also helped put together new open access teaching materials for designing a new product using real conjoint analysis and product design data. We are in the process of releasing it publically.

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Marketing Innovation Tutorial

Example of teaching module for teaching how to estimate market demand to forecast revenue, calculate fixed and variable costs, to obtain forecasts of NPV profit.


MBA: Enterprise Management

This MBA course aims to help students build understanding across cross-functional disciplines. I lectured on the role of marketing as focused on the 4 P's, 5 C's, and segmentation/targeting/planning. I also discussed qualitative methods including design ethnography and experiential focus groups, and quantitative tools include perceptual mapping and modern advances from machine learning.

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Marketing Overview

Example of lecture focused on the 4 P's, 5 C's, and segmentation/targeting/planning.


Graduate Level: Optimization and Machine Learning for Product Design

This graduate-level optimization and mathematical modelling course is based in the engineering college and cross-listed among disciplines such as manufacturing, design, and mechanical engineering. This course covers mathematical formulation of optimization problems, analytic and data-driven modelling, and subsequent solution methods.

I focus on building intuition using analytic methods, followed by practical usage with iterative constrained linear and quadratic approximation methods, and later progress towards more sophisticated methods involving constraint handling and deriviative-free methods. I have introduced a number of modelling methods, including linear and logistic regression, neural networks, and Gaussian processes (kriging), which appears in the new edition of the book.

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Fundamental Concepts in Optimization

Example of teaching module for KKT conditions for constrainted optimality.


Undergraduate Level: Analytic Product Design

This is a product design project course offered to undergraduate seniors and first-year graduate students. Although this course emphasizes engineering design and system integration, I introduce elements of marketing and consumer behaviour to develop products better suited to the end user. In teaching this course, I received a student-nominated award across the entire the University of Michigan College of Engineering. Here are examples of some projects I supervised that left the classroom:

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    Rubbuild

    After the 2010 Haitian Earthquake, more permanent shelter material was needed for humanitarian aid. For ME455, after two months of end-user surveys, Mischa, Katherine, Vaishu, and David developed and optimized a wireframe basket that could be used to build bricks from the local rubble.

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    UM Solar Car Optimization

    The UM Solar Car is an student-run organization that has won 6 consecutive national championships. For ME555, Jianhong, Florian, and Ning performed CFD aerodynamic optimization, FEA stucture optimization, and solar panel topology optimization for the 2016 solar car.