I am an Applied Scientist at AWS AI - Computer Vision, in Seattle.
I received my PhD degree in August 2019 from the Electrical and Computer Engineering department at the University of Texas at Austin (UT Austin). I was advised by Professor Joydeep Ghosh, director of Intelligent Data Exploration and Analysis Laboratory (IDEAL), and was affiliated with the Wireless Networking and Communications Group (WNCG). Prior to joining UT Austin, I received my MSE degree in Electrical Engineering-Systems from University of Michigan, Ann Arbor and completed my BS degree in Electrical Engineering from Korea Advanced Institute of Science and Technology (KAIST).
My primary research interests are in machine learning and computer vision. I am also interested in robust deep learning, anomaly/out-of-distribution detection, and continual learning algorithms.
Click here to see my CV
Email: ktaewan at amazon dot com
Google Scholar: Google Scholar
Work Experience
Amazon, Seattle, WA 2019.9 - Present
Applied Scientist II, AWS AI - Computer Vision, Seattle, WA, 2022.7 - Present
Applied Scientist II, Amazon Physical Stores (Just Walk Out, Amazon Go Research), Seattle, WA, 2021.11 - 2022.6
Applied Scientist II, Amazon Robotics AI, Seattle, WA, 2020.10 - 2021.10 [article1, article2]
Applied Scientist I, Amazon Robotics AI, Seattle, WA, 2019.9 - 2020.9 [article]
Applied Scientist Intern, Amazon Robotics, Seattle, WA, 2018.5 - 2018. 8
Data Scientist/Analyst Intern, Toyota Connected, Plano, TX, 2016.6 - 2016. 8
Software Engineer Intern (Android game developer), Neowiz Internet, Korea, 2012.1 - 2012.2
Education
The University of Texas at Austin, Austin, TX, 2014.08 - 2019.08
Ph.D. in Electrical and Computer Engineering.
Advisor: Prof. Joydeep Ghosh
Research Projects
XML (Explainable Machine Learning), 2018.9 - 2019.8
CAR-STOP (Communications and Radar-Supported Transportation Operations and Planning), TxDOT, 2015.4 - 2019.1
University of Michigan, Ann Arbor, MI, 2012.09 - 2014.05
M.S. in Electrical Engineering: Systems
Graduate Research: Prof. Emily Mower Provost, CHAI (Computational Human-Centered Analysis and Integration) Laboratory
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea, 2006.03 - 2012.02
B.S. in Electrical Engineering,
Advisor: Prof. Sae-Young Chung
Undergraduate Research: Prof. Yung Yi, LANADA (LAboratory of Network Architecture, Design, and Analysis)
Publications
Jongheon Jeong*, Yang Zou*, Taewan Kim, Dongqing Zhang, Avinash Ravichandran, Onkar Dabeer, "WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation", IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023) [arxiv, presentation]
Taewan Kim, Joydeep Ghosh, "On Single Source Robustness in Deep Fusion Models", Advances in Neural Information Processing Systems (NeurIPS 2019) [link, arxiv, code, slide, poster]
Taewan Kim, Michael Motro, Patrícia Lavieri, Saharsh Samir Oza, Joydeep Ghosh, Chandra Bhat, "Pedestrian Detection with Simplified Depth Prediction", IEEE 21st International Conference on Intelligent Transportation Systems (ITSC), 2018 [link, code]
Taewan Kim, Joydeep Ghosh, "Relaxed Oracles for Semi-Supervised Clustering", NeurIPS 2017 Workshop: Learning with Limited Labeled Data: Weak Supervision and Beyond (LLD 2017) [link, arxiv]
Taewan Kim, Joydeep Ghosh, "Robust Detection of Non-motorized Road Users using Deep Learning on Optical and LIDAR Data", IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), 2016 [link]
Academic Activities
Organizing Challenge: Organizing Team of "VAND: Visual Anomaly and Novelty Detection" 2023 Challenge Track (CVPR 2023)
Reviewer for conferences
2021 IEEE 39th International Conference on Robotics and Automation (ICRA 2022)
2019 IEEE 22nd International Conference on Intelligent Transportation Systems (ITSC 2019)
2018 IEEE 21th International Conference on Intelligent Transportation Systems (ITSC 2018)
2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017)
2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC 2016)
Talks
"Machine Learning for Connected Vehicles and Safer Transportation Systems/Semi-Supervised Active Clustering with Weak Oracles", Information Systems Lab, KAIST, Daejeon, Korea, 2017.3
"Robust Deep Fusion Models", Machine Learning Lab, Samsung Advanced Institute of Technology, 2021.2
Teaching
Teaching Assistant, The University of Texas at Austin, EE 361M, Introduction to Data Mining, Fall 2016
Teaching Assistant, The University of Texas at Austin, EE 351K, Probability and Random Processes, Spring 2015
Honors and Awards
Graduate Study Scholarship (doctorate program), The Kwanjeong Educational Foundation, 2014 - 2019
Graduate Study Scholarship (master's program), The Kwanjeong Educational Foundation, 2012 - 2014
National Undergraduate S & T Scholarship, Korea Student Aid Foundation, 2006 - 2012
