Ki-Jun Yoon
Also known as Kijun Yoon, 윤기준
Ki-Jun Yoon is a KAIST neuroscientist whose work connects stem-cell research with AI imaging. He earned a BS in biology and a PhD at POSTECH, then held postdoctoral appointments at Seoul National University and Johns Hopkins before becoming a research associate at Penn. His 2014 Cell Stem Cell paper modeled schizophrenia risk in iPSCs and mice, and his 2017 Cell paper examined how m6A methylation affects the timing of cortical neurogenesis. At KAIST, he joined the Department of Biological Sciences in 2018 and received the 2019 SUHF Young Investigator Award for RNA research in neural stem cells. As of October 2026, he is an assistant professor in biological sciences and an adjunct professor in the Department of AX, with work in image-based AI analysis and deep-learning-guided holotomography.
- Now at
- KAIST
Timeline
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1999–2008
Biology at POSTECH
He earns a BS in biology at POSTECH in 2003 and a PhD there in 2008, with Young-Yun Kong as his doctoral mentor.
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2008–2017
Postdoctoral training at two universities
At Seoul National University, he is a postdoctoral fellow from 2008 to 2009. He then joins Johns Hopkins University's Institute for Cell Engineering, Department of Neurology, as a postdoctoral fellow from 2010 to 2017, mentored by Hongjun Song and Guo-li Ming.
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2014
Modeling schizophrenia risk
He coauthors a 2014 Cell Stem Cell paper, “Modeling a genetic risk for schizophrenia in iPSCs and mice reveals neural stem cell deficits associated with adherens junctions and polarity.”
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2017
m6A and cortical neurogenesis
He coauthors a 2017 Cell paper on how m6A methylation helps time mammalian cortical neurogenesis.
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2017–2018
Research associate at Penn
He becomes a research associate in the Department of Neuroscience at the University of Pennsylvania's Perelman School of Medicine in August 2017.
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2018–2019
KAIST faculty and SUHF award
In October 2018, he joins KAIST's Department of Biological Sciences as an assistant professor. In 2019, he receives the Suh Kyung-Bae Science Foundation Young Investigator Award for work on RNA regulation in neural stem cells.
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2026
Deep-learning holotomography
In 2026, he coauthors the bioRxiv preprint “Deep Learning-Guided Holotomography Reveals Early Structural Remodelling During Pluripotency Exit.” His lab develops deep-learning-guided holotomography platforms to monitor early structural changes during human pluripotent stem-cell differentiation.
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As of October 2026
Image-based AI at KAIST
He is an assistant professor in KAIST's Department of Biological Sciences and an adjunct professor in its Department of AX. His work includes image-based AI analysis of induced pluripotent stem cells and brain organoids, and his AI competencies include generative AI.
Career
- Since 2018KAISTAssistant professor
- 2017–2018Perelman School of Medicine at the University of PennsylvaniaResearch associate
- 2010–2017Johns Hopkins UniversityPostdoctoral fellow
- 2008–2009Seoul National UniversityPostdoctoral fellow
Education
Colleagues
Sources and credits
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