Skip to main content

Jae Jin Cho

Seoul National University · 医学

研究室紹介

Professor Jae Jin Cho's research lab specializes in biomedical engineering and translational science, focusing on the development of advanced materials and technologies for regenerative medicine and clinical diagnostics. The lab investigates stem cell behavior on novel metallic biomaterials—particularly 3D-printed cobalt-chrome and nickel-chrome alloys—aiming to improve dental implant biocompatibility and osseointegration. Additionally, the lab explores machine learning applications in speech recognition and emotion detection, integrating acoustic and linguistic features through deep learning models such as LSTMs and CNNs. A significant research thrust involves understanding the role of innate immune receptors, such as Toll-like receptors, in cancer progression and tissue regeneration.

biomaterialsstem cell differentiation3D printingdeep learningimmune modulation

Research Overview

Papers
174
Total Citations
1,623
Papers (5y)
86
Primary Field
医学

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
86total
2021
2022
2023
2024
2025
Citations per year (5y)
330total
20212022202320242025

Selected Papers

15
1
Article|112 citations·2018
Multilingual Sequence-to-Sequence Speech Recognition: Architecture, Transfer Learning, and Language Modeling
Jaejin Cho, Murali Karthick Baskar, Ruizhi Li, Matthew Wiesner, Sri Harish Mallidi, Nelson Yalta, Martin Karafiát, Shinji Watanabe, Takaaki Hori

Sequence-to-sequence (seq2seq) approach for low-resource ASR is a relatively new direction in speech research. The approach benefits by performing model training without using lexicon and alignments. However, this poses a new problem of requiring more data compared to conventional DNN-HMM systems. In this work, we attempt to use data from 10 BABEL languages to build a multilingual seq2seq model as a prior model, and then port them towards 4 other BABEL languages using transfer learning approach.

Artificial IntelligenceComputer Science
2
Article|94 citations·2018
Deep Neural Networks for Emotion Recognition Combining Audio and Transcripts
Jaejin Cho, Raghavendra Pappagari, Purva Kulkarni, Jesús Villalba, Yishay Carmiel, Najim Dehak

In this paper, we propose to improve emotion recognition by combining acoustic information and conversation transcripts.On the one hand, a LSTM network was used to detect emotion from acoustic features like f0, shimmer, jitter, MFCC, etc.On the other hand, a multi-resolution CNN was used to detect emotion from word sequences.This CNN consists of several parallel convolutions with different kernel sizes to exploit contextual information at different levels.A temporal pooling layer aggregates the

Experimental and Cognitive PsychologyPsychology
3
Article|46 citations·2013
Phenotypic Characterization and In Vivo Localization of Human Adipose-Derived Mesenchymal Stem Cells
Young-Joon Ryu, Tae‐Joon Cho, Dong‐Sup Lee, Jin‐Young Choi, Jaejin Cho
SJR Q1Molecules and Cells
GeneticsMedicine
4
Article|46 citations·2013
Chondrogenesis of periodontal ligament stem cells by transforming growth factor-β3 and bone morphogenetic protein-6 in a normal healthy impacted third molar
Sunyoung Choi, Tae‐Joon Cho, Soon-Keun Kwon, Gene Lee, Jaejin Cho
SJR Q1International Journal of Oral ScienceOA

The periodontal ligament-derived mesenchymal stem cell is regarded as a source of adult stem cells due to its multipotency. However, the proof of chondrogenic potential of the cells is scarce. Therefore, we investigated the chondrogenic differentiation capacity of periodontal ligament derived mesenchymal stem cells induced by transforming growth factor (TGF)-β3 and bone morphogenetic protein (BMP)-6. After isolation of periodontal ligament stem cells (PDLSCs) from human periodontal ligament, the

UrologyMedicine
5
Article|38 citations·2019
Human Stem Cell Responses and Surface Characteristics of 3D Printing Co-Cr Dental Material
Boldbayar Ganbold, Seong‐Joo Heo, Jai‐Young Koak, Seong‐Kyun Kim, Jaejin Cho
SJR Q2MaterialsOA

Recently, the selective laser melting (SLM) method of manufacturing three dimensional (3D) dental prosthetics by applying a laser to metal powder has been widely used in the field of dentistry. This study investigated human adipose derived stem cell (hADSC) behavior on a 3D printed cobalt-chrome (Co-Cr) alloy and its surface characteristics and compared them those of a nickel-chrome (Ni-Cr) alloy. Alloys were divided into four groups according to the material and manufacturing methods. Co-Cr dis

OrthodonticsDentistry
6
Article|34 citations·2019
Robust water–fat separation for multi‐echo gradient‐recalled echo sequence using convolutional neural network
Jaejin Cho, HyunWook Park
SJR Q1Magnetic Resonance in Medicine

PURPOSE: To accurately separate water and fat signals for bipolar multi-echo gradient-recalled echo sequence using a convolutional neural network (CNN). METHODS: A CNN architecture was designed and trained using the relationship between multi-echo images from the bipolar multi-echo gradient-recalled echo sequence and artifact-free water-fat-separated images. The artifact-free water-fat-separated images for training the CNN were obtained from multiple signals with different TEs by using iterative

Radiology, Nuclear Medicine and ImagingMedicine
7
Review|34 citations·2019
Toll‐like receptors: A pathway alluding to cancer control
Ana Patricia Ayala‐Cuellar, Jaejin Cho, Kyung‐Chul Choi
SJR Q1Journal of Cellular Physiology

Toll-like receptors (TLRs) are usually expressed on immune cells such as macrophages, dendritic cells, mast cells, as well as on eosinophils and some epithelial cells. They play a central role in the recognition of harmful molecules that belong to invading microorganisms or internal damaged tissues, which lead to inflammation. Among the hallmarks of cancer, there is immune evasion and inflammation. Summing this with the discovery that a majority of cancers also seem to express TLRs, made researc

ImmunologyImmunology and Microbiology
8
Article|22 citations·2012
A potent small-molecule inducer of chondrogenic differentiation of human bone marrow-derived mesenchymal stem cells
Tae Jun Cho, Jonghoon Kim, Soon-Keun Kwon, Keunhee Oh, Jeong Ae Lee, Dong‐Sup Lee, Jaejin Cho, Seung Bum Park
SJR Q1Chemical Science

We discovered a novel small-molecule modulator 5{i,2} that can specifically induce the chondrogenic differentiation of human bone marrow-derived mesenchymal stem cells (hBM-MSCs). Based on our biochemical and histological studies, 5{i,2} showed more of a directed differentiation of MSCs to chondrocyte balls compared to TGF-β3.

RheumatologyMedicine
9
Article|21 citations·2022
Estrogen Regulates the Expression and Localization of YAP in the Uterus of Mice
Sohyeon Moon, Ok‐Hee Lee, Byeongseok Kim, Jinju Park, Semi Hwang, Siyoung Lee, Giwan Lee, Hyukjung Kim, Hyuk Song, Kwonho Hong, Jaejin Cho, Youngsok Choi
SJR Q1International Journal of Molecular SciencesOA

The dynamics of uterine endometrium is important for successful establishment and maintenance of embryonic implantation and development, along with extensive cell differentiation and proliferation. The tissue event is precisely and complicatedly regulated as several signaling pathways are involved including two main hormones, estrogen and progesterone signaling. We previously showed a novel signaling molecule, Serine/threonine protein kinase 3/4 (STK3/4), which is responded to hormone in the mou

Cell BiologyBiochemistry, Genetics and Molecular Biology
10
Article|20 citations·2023
Time‐efficient, high‐resolution3Twhole‐brain relaxometry using3D‐QALASwithwave‐CAIPIreadouts
Jaejin Cho, Borjan Gagoski, Tae Hyung Kim, Fuyixue Wang, Mary Kate Manhard, Douglas Dean, Steven Kecskemeti, Arvind Caprihan, Wei‐Ching Lo, Daniel Splitthoff, Wei Liu, Daniel Polak
SJR Q1Magnetic Resonance in Medicine

Abstract Purpose Volumetric, high‐resolution, quantitative mapping of brain‐tissue relaxation properties is hindered by long acquisition times and SNR challenges. This study combines time‐efficient wave–controlled aliasing in parallel imaging (wave‐CAIPI) readouts with the 3D quantification using an interleaved Look‐Locker acquisition sequence with a T 2 preparation pulse (3D‐QALAS), enabling full‐brain quantitative T 1 , T 2 , and proton density (PD) maps at 1.15‐mm 3 isotropic voxels in 3 min.

Radiology, Nuclear Medicine and ImagingMedicine
11
Article|13 citations·2019
Endothelin-converting enzyme-1 expression in acute and chronic liver injury in fibrogenesis
Tae‐Joon Cho, Hyo-Jung Kim, Jaejin Cho
SJR Q1Animal Cells and SystemsOA

Endothelin-1 (ET-1) induces contraction, proliferation, and collagen synthesis of activated hepatic stellate cells and is a potent mediator of portal hypertension. Endothelin-converting enzyme-1 (ECE-1) generates ET-1 from the inactive precursor big-endothelin-1. The cellular distribution and activity of ECE-1 in the liver is unknown. Hepatic fibrogenesis was induced in rats by CCl<sub>4</sub> administration and secondary biliary cirrhosis after 6 weeks of complete bile duct occlusion (BDO). The

PhysiologyMedicine
12
Article|13 citations·2022
Wave-Encoded Model-Based Deep Learning for Highly Accelerated Imaging with Joint Reconstruction
Jaejin Cho, Borjan Gagoski, Tae Hyung Kim, Qiyuan Tian, Robert Frost, Itthi Chatnuntawech, Berkin Bilgiç
SJR Q2BioengineeringOA

A recently introduced model-based deep learning (MoDL) technique successfully incorporates convolutional neural network (CNN)-based regularizers into physics-based parallel imaging reconstruction using a small number of network parameters. Wave-controlled aliasing in parallel imaging (CAIPI) is an emerging parallel imaging method that accelerates imaging acquisition by employing sinusoidal gradients in the phase- and slice/partition-encoding directions during the readout to take better advantage

Radiology, Nuclear Medicine and ImagingMedicine
13
Preprint|11 citations·2021
The JHU submission to VoxSRC-21: Track 3
Jaejin Cho, Jesús Villalba, Najim Dehak
arXiv (Cornell University)OA

This technical report describes Johns Hopkins University speaker recognition system submitted to Voxceleb Speaker Recognition Challenge 2021 Track 3: Self-supervised speaker verification (closed). Our overall training process is similar to the proposed one from the first place team in the last year's VoxSRC2020 challenge. The main difference is a recently proposed non-contrastive self-supervised method in computer vision (CV), distillation with no labels (DINO), is used to train our initial mode

Artificial IntelligenceComputer Science
14
Article|10 citations·2019
Characterization of canine adipose tissue‐derived mesenchymal stem cells immortalized by SV40‐T retrovirus for therapeutic use
Ana Patricia Ayala‐Cuellar, Cho‐Won Kim, Kyung‐A Hwang, Ji‐Houn Kang, Gabsang Lee, Jaejin Cho, Kyung‐Chul Choi
SJR Q1Journal of Cellular Physiology

Abstract Canine mesenchymal stem cells (cMSCs) are gaining popularity in the veterinary field as a regenerative therapy. But, their limited culture lifespan makes it an obstacle for preclinical investigation and therapeutic use. In this study, primary canine adipose tissue‐derived MSCs (PCAT‐MSCs) were isolated from adipose tissue and were transfected with the SV40‐T retrovirus resulting in a life‐extended immortalized canine adipose tissue‐derived MSCs (ICAT‐MSCs). A comparison was made through

GeneticsMedicine
15
Article|9 citations·2013
Comparison of the Ultrastructural and Immunophenotypic Characteristics of Human Umbilical Cord-derived Mesenchymal Stromal Cells and in Situ Cells in Wharton’s Jelly
Young-Joon Ryu, Hyang Sook Seol, Tae Jun Cho, Tae Jung Kwon, Se Jin Jang, Jaejin Cho
SJR Q3Ultrastructural Pathology

The umbilical cord contains mucinous connective tissue, called Wharton's jelly. It consists of stromal cells, collagen fibers, and amorphous ground substances composed of proteoglycan. Recently, these stromal cells have been redefined as a new cell therapy source, named human umbilical cord-derived mesenchymal stromal cells (hUCMSCs). However, there are few studies on the ultrastructural features and immune-phenotypic characteristics of isolated hUCMSCs and comparisons with the cells found in or

GeneticsMedicine

Research Areas

Radiology, Nuclear Medicine and ImagingArtificial IntelligenceGeneticsMolecular BiologyBiomedical EngineeringPhysiology

Jae Jin Choの研究をNubintでさらに深く

この研究室の論文をアプリで開き、AIと共に読み、要約し、引用しましょう。