University Lectures

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Graduates Courses

  • Smart Mobile Platform (스마트모바일플랫폼) [ECE654] (Fall 2019), Korea University School of Electrical Engineering [GitHub]
  • Wireless and Mobile Networks (무선이동네트워크) [ECE522] (Spring 2020), Korea University School of Electrical Engineering [GitHub]
  • Optimal Design Theory and Applications (최적설계이론및응용) (Spring 2019, Spring 2018, Spring 2017), Chung-Ang University School of Computer Science and Engineering
  • Topics in Computer Science and Engineering (컴퓨터공학특강) (Fall 2018, Fall 2017, Fall 2016), Chung-Ang University School of Computer Science and Engineering

Undergraduates Courses

  • Probability and Random Process (확률및랜덤프로세스) [KECE209] (Spring 2020), Korea University School of Electrical Engineering [GitHub]
  • Digital System (디지털시스템) [KECE207] (Spring 2020), Korea University School of Electrical Engineering [GitHub]
  • Computer Language and Laboratory (컴퓨터언어및실습) [EGRN151] (Fall 2019), Korea University School of Electrical Engineering [GitHub]
  • Numerical Analysis (수치해석) (Spring 2019), Chung-Ang University School of Computer Science and Engineering
  • Compiler Design (컴파일러설계) (Spring 2019, Spring 2018, Spring 2017), Chung-Ang University School of Computer Science and Engineering
  • Principles of Programming Languages (프로그래밍언어론) (Fall 2018, Fall 2017, Fall 2016), Chung-Ang University School of Computer Science and Engineering
  • Algorithm Analysis (알고리즘분석) (Fall 2016), Chung-Ang University School of Computer Science and Engineering
  • Mobile App Development (모바일앱개발) (Fall 2018, Fall 2017), Chung-Ang University School of Computer Science and Engineering
  • Operating Systems (운영체제) (Spring 2017, Spring 2016), Chung-Ang University School of Computer Science and Engineering
  • Calculus (미적분학) (Spring 2017, Spring 2016), Chung-Ang University School of Computer Science and Engineering

Graduate Teaching Assistants at USC Viterbi School of Engineering

  • Wireless and Mobile Networks Design and Laboratory (EE579/CSCI575, 3 Units), Ming Hsieh Department of Electrical Engineering, USC Viterbi School of Engineering (Los Angeles, California, USA)
    • This course covers theoretical and application-specific issues (i.e., system-on-chip (SoC), location-based services (LBS), energy-efficiency, wireless networks, crowd sourcing, and health sensing) of mobile platform research activities.
    • Spring 2013: I designed 3 assignments related to mobile programming, i.e., (i) geo-tagging and Bluetooth-based file sharing (i.e., camera API, GPS API, and Bluetooth API were used), (ii) distributed file sharing architectures via Bluetooth connections, and (iii) mobile route finder with given simplified LA metro subway topologies, held office hours (2 hours/week), and lectured several tutorials for mobile programming in class, i.e., (i) Android Development Environment Setting, (ii) Google AppEngine Cloud Computing Platforms, (iii) Android with SQLite Database, (iv) Android WiFi, and (v) Android Graphics with OpenGL (with Google Android SDK 4.0+ over Samsung Galaxy Tab II platforms) during 14 weeks for 21 students.
  • Programming Systems Design (CSCI/EE455x, 4 Units), Department of Computer Science, USC Viterbi School of Engineering (Los Angeles, California, USA)
    • This course covers object-oriented programming design and principles, advanced data structures and algorithms, software design and engineering concepts.
    • Fall 2012: I led 12 lab sessions (4 hours/week), held office hours (more than 2 hours/week), and proctored exams (2 midterms) during 14 weeks for 49 students.
    • Spring 2012: I led 12 lab sessions (4 hours/week), held office hours (more than 2 hours/week for 12 weeks), and proctored exams (2 midterms and 1 final) during 14 weeks for 24 students.

Special Lectures (Full/Half Day Presentation)

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Research Institutes and Societies

  • Federated and Adversarial Imitation Learning, KICS Workshop (Seoul, Korea, 12/2019)
  • Deep Learning Theory and Software, Korean Institute of Broadcast and Media Engineers (Seoul, Korea, 12/2019)
  • Deep Reinforcement Learning: Algorithms, Software, Applications, and Trends, OSIA (Seoul, Korea, 11/2019)
  • Deep Reinforcement Learning, KICS Workshop (Daejeon, Korea, 10/2019)
  • Deep Learning Theory and Software, Korea Institute for Robot Industry Advancement (Daegu, Korea, 08/2019)
  • Deep Learning Basics and Software, KICS Workshop (Seoul, Korea, 08/2019)
  • Deep Learning Theory and Software, IEIE Special Lecture Series (Seoul, Korea, 08/2019)
  • Machine Learning (Advanced), Korea Institute of Robot and Convergence (Seoul, Korea, 07/2019)
  • Deep Reinforcement Learning: from Basics to Autonomous Driving Applications, KICS Workshop (Seoul, Korea, 07/2019)
  • Deep Learning Programming with TensorFlow/Keras, Korea Institute for Robot Industry Advancement (Daegu, Korea, 07/2019)
  • Deep Reinforcement Learning, KIISE Information Networking Society (Seoul, Korea, 05/2019)
  • Machine Learning for Data Analytics, Intelligent Transport Society of Korea (ITS Korea) (Anyang, Korea, 04/2019)
  • Deep Learning Programming with TensorFlow/Keras, Korea Institute for Robot Industry Advancement (Daegu, Korea, 02/2019)
  • Deep Reinforcement Learning: Algorithms and Applications, OSIA (Seoul, Korea, 02/2019)
  • Deep Learning Theory and TensorFlow Implementation, Korean Institute of Broadcast and Media Engineers (Seoul, Korea, 02/2019)
  • Deep Learning Programming with TensorFlow, Korea Institute for Robot Industry Advancement (Gumi, Korea, 09/2018)
  • The 1st KICS Lecture on TensorFlow-based Deep Learning Programming, KICS Workshop (Seoul, Korea, 06/2018)
  • Machine Learning Basics, KIISE Database Society, Big Data Technology Winter School (Seoul, Korea, 02/2018)

Industry

  • Artificial Intelligence (A.I.) Practice, KTDS (2019)
  • Deep Learning Theory and Software, KT Education Center for Artificial Intelligence (2017, 2018, 2019), SK C&C (2018, 2019), PoscoICT (2018), BC Card (2019)
  • Deep Learning and Natural Language Processing, PoscoICT (2018), LGCNS (2018, 2019)
  • Natural Language Processing with Deep Learning Practice, LGCNS (2018, 2019)
  • Natural Language Processing with Deep Learning Workshop, LGCNS (2018, 2019)
  • Machine Learning Theory and Practice, PoscoICT (2017), KT Education Center for Artificial Intelligence (2017, 2018), LGCNS (2018), Shinhan Card (2018), SK C&C (2019)
  • Learning Inference, KT Education Center for Artificial Intelligence (2018)
  • Statistics and Statistical Inference for Big-Data Analytics, LGCNS (2018)
  • Python Programming and TensorFlow, KTDS (2017)

Open Lectures

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Deep Learning

  • TBD

Mathematics and Optimization

  • TBD

Lectures