Seokju Lee

Assistant Professor at Korea Institute of Energy Technology(KENTECH)

Seoul, South Korea
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Summary

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Senior
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Top School
Seokju Lee is an assistant professor at KENTECH leading the Viewlab and heading the Energy AI track with nine years of research experience in computer vision, robotics, and machine learning. He holds a PhD in Robotics Engineering from KAIST and brings deep expertise in robust visual perception, sensor fusion, and navigation for autonomous systems developed during long-term research roles at KAIST and internships at Microsoft. His work bridges academic rigor and applied systems, focusing on perception for autonomous driving as well as UAV/UGV navigation, now applied to energy-focused AI problems. Based in Seoul, he maintains an active research lab that fosters cross-disciplinary projects and student mentorship. Less obvious: his early work on wireless/mobile networking during undergrad informs a practical systems perspective when integrating perception with communication and distributed platforms.
code9 years of coding experience
job10 years of employment as a software developer
bookBachelor of Science - BS, Electrical and Computer Engineering, Bachelor of Science - BS, Electrical and Computer Engineering at Ulsan National Institute of Science and Technology
bookStudent Exchange Program, Computer Science, Student Exchange Program, Computer Science at University of California, Los Angeles
bookDoctor of Philosophy - PhD, Robotics Engineering, Doctor of Philosophy - PhD, Robotics Engineering at Korea Advanced Institute of Science and Technology
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Github Skills (62)

depth-estimation10
projection10
siggraph10
visual-odometry10
depth10
pytorch9
vehicle-detection9
computer-vision8
sparse8
generative8
consistency8
self-attention8
robotics8
image-processing7
attention-mechanism7

Programming languages (5)

C++CLuaJupyter NotebookPython

Github contributions (5)

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SeokjuLee/TF_FlowNet

Jul 2019 - Jul 2019

Contributions:41 commits, 43 pushes, 1 branch in 4 days
SeokjuLee/Insta-DM

Dec 2019 - Jan 2023

Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency (AAAI 2021)
Contributions:18 commits, 4 PRs, 17 pushes in 3 years 1 month
pytorchdynamic-scenesmonocular-depth-estimationvisual-odometryprojection
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