* More details are described here: Curriculum Vitae

Research Interest

  • RGB-D Perception, Human Pose Understanding
  • Computer Vision, Robot Perception, Deep Learning, Autonomous Driving



Academic Activities

  • IEEE International Conference on Robotics and Automation (ICRA) Reviewer, 2018
  • IEEE Transactions on Image Processing (TIP) Reviewer, 2017
  • Women In Robotics Workshop III, Robotics: Science & systems (RSS) Poster Presentation, Jul 15, 2017
  • IEEE International Conference on Robotics and Automation (ICRA) Reviewer, 2017
  • Midwest Robotics Workshop (MWRW) Poster Presentation, Mar 17, 2016
  • IEEE International Conference on Robotics and Automation (ICRA) Reviewer, 2016


  • Mar 2013 - Jun 2013 Tutoring on Programming Structures, KAIST
  • Sep 2011 - Dec 2011 Tutoring on Signals and Systems, KAIST

Technical Courses

  • University of Michigan, Ann Arbor  show
    Mobile Robotics: Methods and Algorithms (EECS 568)
    Image Processing (EECS 556)
    Advanced Topics in Computer Vision (EECS 542)
    Matrix Methods for Signal Processing, Data Analysis and Machine Learning (EECS 551)
  • Stanford University  show
    Computer Vision: From 3D Reconstruction to Recognition (CS 231A)
    Convolutional Neural Networks for Visual Recognition (CS 231N)
    Probabilistic Graphical Models: Principles and Techniques (CS 228)
    Advanced Statistical Learning Theory (CS 229T)
    Machine Learning (CS 229)
    Convex Optimization I (EE 364A)
    Convex Optimization II (EE 364B)
    Stochastic Control (EE 365)
    Introduction to Linear Dynamical Systems (EE 263)
    Mining Massive Datasets (CS 246)
    Data Mining and Analysis (STATS 202)
    Design and Analysis of Algorithms (CS 161)
    Introduction to Parallel Computing using MPI, OpenMP, and CUDA (CME 213)
    Computational Biology: Structure and Organization of Biomolecules and Cells (CS 279)
  • Korea Advanced Institute of Science and Technology  show
    Statistical Learning Theory (EE 531)
    Engineering Random Processes (EE 528)
    Probability and Statistics (MAS 250)
    Introduction to Information Theory and Coding (EE 326)
    Digital Signal Processing (EE 432)
    Special Topics in Electrical Engineering: Discrete Methods for Electrical Engineering (EE 488)
    Electronics Design Lab.: Network of Talking Teddy Bears (EE 405)
    Communication Engineering (EE 321)
    Introduction to electronics design Lab: Communications and Internet Computing (EE 305)
    Electronic Circuits (EE 304)
    Digital System Design (EE 303)
    Probability and Introductory Random Processes (EE 210)
    Programming Structure for Electrical Engineering (EE 209)
    Electromagnetics (EE 204)
    Signals and Systems (EE 202)
    Circuit Theory (EE 201)
    Classical Electromagnetism I,II (PH 231,232)
    Classical Mechanics I,II (PH 221,222)
    Physics Lab. I,II (PH 251,252)