Jaebong Lim

I am a Ph.D. student at Pusan National University (PNU) in South Korea, where I work on driver behavior analysis and machine learning.

I obtained my B.S., and M.Sc. degrees advised by Prof. Yunju Baek in School of Computer Science and Engineering from Pusan National University (PNU) in 2016 and 2018, respectively. I am currently pursuing the Ph.D. degree.

Email / CV / Google Scholar

PNU Mar. 11 - Present	Virginia Tech Sep. 22 - Oct. 22

Ph.D. Thesis

Deep Learning Model and Early-Exiting Method for Low-Latency and Reliable Driver Profiling

Research

I'm interested in hardware-aware automated machine learning (automl) and neural network compression. Much of my research is about inferring the context from time-series sensor data. Representative papers are highlighted.

	Temporal Early Exiting With Confidence Calibration for Driver Identification using Driving Sensing Data Jaebong Lim, Yunju Baek, Bumhee Chae IEEE Access, 2022 Proposed system identifies the driver with less driving data for easy-to-identify trips and more driving data for hard-to-identify trips. To adaptively exit the identification by considering the difficulty of a trip, we propose a temporal early-exiting method by thresholding the confidence score and three temporal confidence calibration methods that adjust calibration strength according to the driving time and trip difficulty.
	Joint Framework of Curriculum Learning and Knowledge Distillation for Noise-Robust and Small-Footprint Keyword Spotting Jaebong Lim, Yunju Baek IEEE Access, 2023 This paper presents the first study on a joint framework of curriculum learning and knowledge distillation for noise-robust and small-footprint keyword spotting. The main finding is that distilling a small network after applying curriculum learning to the large teacher network is superior to directly applying curriculum learning to the small network.
	Open-Set Driver Identification System Based on Metric Learning with Driving Situation Awareness Jaebong Lim, Yunju Baek IEEE ITSC, 2023
	User-Defined Keyword Spotting Utilizing Speech Synthesis for Low-Resource Wearable Devices Jaebong Lim, Yunju Baek IEEE ICCE, 2022
	CamThings: IoT Camera with Energy-Efficient Communication by Edge Computing based on Deep Learning Jaebong Lim, Juhee Seo, Yunju Baek ITNAC, 2018
	Design and Implementation of Driving Information Collection System for Driver Behavior Analysis Beomjun Kim, Juhee Seo, Jaebong Lim, Yunju Baek ACM MobiSys, 2018 (Poster)
	Design and Implementation of Camera Network Platform for Information Exchange using Dual Wireless Interface Beomjun Kim, Sanghyun Son, Jaebong Lim, Yunju Baek ITNAC, 2016

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