AI Platform Lead at
Deargen
PhD in Computer Vision AI at
The University of Edinburgh
I started computer programming when I was 9. I began MFC(C++) Windows programming at age 14 and opened a personal website, "sparkware.co.kr". I made a Hair Proportion Analysis algorithm and obtained a patent when I was 17. Now my interests are in machine learning application on computer vision and image signal processing.
"Kiyoon" stands for glowing field. I want to make my field of study glow in the future.
Cirriculum Vitae
I started computer programming with Flash ActionScript 2.0.
I started MFC Windows Programming and opened my own website, sparkware.co.kr. I released many Windows programs on this website.
I finished a project about Hair Proportion Analysis algorithm based on the Maximum Likelihood estimation.
I studied both Electronics and Computer Engineering. I won lots of competitions like Hexathon (supported by Naver), Korea Supercomputing Challenge, and Naver Poster Award. See experience below.
We've visited UC Berkeley for 9 weeks to exchange ideas
about making a start-up company. (Article)
Extreme Low Resolution Activity Recognition Using
Siamese Embedding (Paper)
We've demonstrated our technologies at CVPR 2017
Expo. (Youtube video)
Deep learning, Computer vision, Signal processing, Linux server buildup, Web development, Machine integration, Video editing and filmography, Product design
C ∙ C++ ∙ Python ∙ Linux Bash ∙ TensorFlow / Keras (Machine learning) ∙ MPI (Parallel programming) ∙ CUDA (GPU parallel programming) ∙ MATLAB ∙ OpenCV ∙ Git (Version control) ∙ Docker ∙ NVIDIA Jetson TX2 (Linux embedded device) ∙ Raspberry Pi (IoT Linux) ∙ MFC (Windows programming) ∙ Java ∙ HTML ∙ PHP ∙ MySQL / Maria DB ∙ R ∙ Flash action script ∙ Processing ∙ NXT Robot C ∙ Xpress Engine(Website) ∙ Wordpress(Website) ∙ LATEX
K Kim, D Moltisanti, O Mac Aodha, L Sevilla-Lara, “An
Action Is Worth Multiple Words: Handling Ambiguity in Action
Recognition”, 33rd British Machine Vision Conference 2022,
BMVC 2022
K Kim, SN Gowda, O Mac Aodha, L Sevilla-Lara, “Capturing
Temporal Information in a Single Frame: Channel Sampling
Strategies for Action Recognition”,
33rd British Machine Vision Conference 2022, BMVC 2022
SN Gowda, L Sevilla-Lara, K Kim, F Keller, M Rohrbach, “A
new split for evaluating true zero-shot action recognition”,
DAGM German Conference on Pattern Recognition, 2021
M. S. Ryoo, K. Kim and H. J. Yang, ”Extreme Low Resolution
Activity Recognition with Multi-Siamese Embedding Learning,
”AAAI Conference on Artificial Intelligence, New Orleans,
Louisiana, February 2018.
[acceptance rate: 24.6%]
1st place - Naver UNIST Undergraduate Poster Award
1st place - HeXATHON, UNIST, supported by NAVER
KSC (Korea Supercomputing Challenge) : MPI parallel computing 5th
place
Bronze Medal in the National Olympiad for Informatics (KOI, Korea
Olympiad in Informatics)
Patent : Hair Percentage Analysis algorithm
UNIST Startup clinic: Smart home app controlling electrical output