Teaching and Research Supervising

UNIST, Korea

Undergraduate

ESD 201 - Engineering Mechanics, Spring 2014

This course studies the essential and fundamental concepts of engineering mechanics including solid mechanics, dynamics, fluid dynamics. In this course, students are expected to understand basic knowledge of system physics in order to analyze and model mechanical systems.


ESD 301 - Engineering Drawing and Analysis, Spring 2014

This course not only provides the fundamental components of mechanical drawing, but also studies mechanical kinematics, system analysis and parameter optimization via simulation tools. In this course, students are expected to learn various computer simulation tools and their fundamentals for the design and development of mechanical products.


ESD 411 - Introduction to Vehicle Design, Fall 2013

This course will cover a broad range of topics for automotive design and engineering with the following selected areas:
- Automotive engineering (body and frame, power plant, power train, suspension system, steering system, brake system, electrical system)
- Car manufacturing processes

During this class, an automotive assembly plant visit will be made for hands-on experience. Furthermore, two guest lectures by automotive industry experts and one guest lecture by automotive design expert will be delivered.

Graduate

DHE 571 - Advanced Control and Signal Processing, Fall 2014

This course deals with signals, systems, and transforms, from their theoretical mathematical foundations to practical implementation in computer algorithms. Furthermore, advanced linear feedback control with time-invariant linear systems will be covered.

DHE 802 - Special Topics in ESD 2 (Optimization Methods), Winter 2014

The course discusses fundamentals of discrete optimization methods as applied to engineering problems. Topics include discrete optimization models, integer and mixed-integer programming algorithms, graph search algorithms, heuristic algorithms, and case studies. Lectures present the key concepts and mathematical basis of each topic with its applications. The student are expected to learn how to create appropriate mathematical optimization models and to use analytical and computational techniques to solve them.

DHE 801 - Special Topics in ESD 1 (Big Data Analytics), Fall 2013

This course explores basic data analysis methods which will be an important tool for analyzing either simulation results or experimental data. Students are expected to learn algorithms of data analytics and their implementations in Matlab.

Details:
Programming in Matlab, Basic linear algebra, Statistics, Probability, Frequency domain analysis, Time series analysis, Principal component analysis, Multivariate classification (Logistic regression, SVM, SOM), Parameter estimation (MMSE, Maximum Likelihood, Bayes estimators), Neural networks, Bayesian networks, etc.



University of Michigan, Ann Arbor

Ph.D. Committee, since Winter 2011

Member of the doctoral committee for Ahmad Almuhtady
Dissertation title: "Degradation-Based Swapping Optimization Policy for Fleet-Level Battery Utilization"



ME 590 - Independent Studies, Fall 2011

Supervising graduate students

  • "Benchmark on Energy Consumption in Automotive Plant" by Yi Liu
  • "Basic Concept of the Fuel Injection System" by Kai Chen

ME 590 - Independent Studies, Winter 2011

Supervising graduate students

  • "The Development and Implementation of Optimal Maintenance Strategies for Assembly Manufacturing Line" by Xi Gu
  • "Intensive Care Unit (ICU) Admission Early Warning System Using Statistical Analysis" by Mo Chen

ME 590 - Independent Studies, Fall 2010

  • "Remaining Useful Life Prediction of Lithium-ion Battery Using Prediction Error Methods" by Harry Cui

IOE 565 - Time Series Analysis, Fall 2009

Topics that this class covers:

  1. Modeling physical systems/processes from operational data
  2. Time series models as tools for system analysis
  3. Forecasting the behavior based on the dynamics of a system
  4. Continuous stochastic systems
  5. Forecasting control to alter a system's performance
  6. Trends and seasonality
  7. Multiple series
  8. Applications of time series analysis

As a graduate student instructor for this course, I held two office hours per week.

When asked: "Overall, the instructor was an excellent teacher.", my ratings were as follows: 4.32/5.00

ME 495 - Laboratory II, Winter 2009

ME 495 - Laboratory II, Winter 2008

Weekly lectures and extended experimental projects are designed to demonstrate experimental and analytical methods as applied to complex mechanical systems. Topics will include controls, heat transfer, fluid mechanics, thermodynamics, mechanics, materials, and dynamical systems. Emphasis on laboratory report writing, oral presentations, and team-building skills, and the design of experiments.

As a graduate student instructor for this class, I taught 2 lab sections in a given semester with 32 students. My tasks include:

  • develop lab assignments and projects
  • hold a lab section once a week that provided “hands-on” class activities, as well as problem review session

When asked: "Overall, the instructor was an excellent teacher.", my ratings were as follows: 4.88/5.00, 4.28/5.00



Seoul National University

ME 345 - Introduction to Robotics, Spring 2000

This introductory course offers a rigorous foundation in robotics, with an emphasis on robot kinematics and dynamics, and the basics of robot movement planning and control. The emphasis will be on learning fundamental concepts and principles that underly robotics, and are grounded in mechanics and mathematics; the intent is to help students develop both a reliable intuition and a set of analytical tools for the modeling, planning, and control of robots. The course should also prepare students for advanced study not only in robotics, but also multibody dynamics, computer-aided design, computer graphics and animation, computer vision, and any subject in which the study of motions plays a fundamental role.

As a teaching asistants, I taught 1-hour weekly discussion section for 12 students. My tasks includes:

  • review the lecture material
  • solve practice problems
  • give the students an opportunity to ask questions


Courses Taken

Mechanical Engineering

Analytical mathematics, Solid Continuum Mechanics, Intermediate dynamics, Linear systems, Linear feedback control, Non-linear system and control, Non-linear dynamics of mechanical systems.

Industrial Engineering

Discrete event simulation, Discrete design optimization, Scheduling, Time series analysis, Probability and random process, Stochastic process.

Electrical Engineering

Electronic circuits, Logic design, Digital system design, Analog circuits, Electromagnetics, Signals & systems.