I am a Postdoctoral Research Fellow at the Singapore University of Technology and Design (SUTD). I earned my Ph.D. in Electrical Engineering and Computer Science from the Gwangju Institute of Science and Technology (GIST), South Korea, in 2017, focusing on User Interest Modeling in Social Media for Personalized Services. Following my doctoral studies, I served as a Research Scientist at Seoul National University Hospital (SNUH) and later as a Postdoctoral Research Fellow at Korea National University of Transportation (KNUT). During these roles, I contributed to diverse projects encompassing medical image segmentation/classification, fruit freshness classification, face mask detection, anomaly detection, and knowledge distillation. Beyond my academic and research pursuits, I have a passion for music. I've worked as a lounge pianist and have composed my own solo piano pieces, some of which are available on popular platforms such as iTunes and Spotify. Currently, my research endeavors extend into the realm of music generation for video, leveraging a dataset of music videos.

Education

• Ph.D. Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST) (Mar. 2009 - Feb. 2017)
  • Thesis: User Interest Modeling in Social Media for Personalized Services
    Advisor: Prof. Hyunju Lee; Committee: Kuk-Jin Yoon, Sung-Hee Lee, Sung Chan Jun, Xing Xie
    Formal Advisor: Prof. Kwang Mong Sim
• B.S. Computer Engineering, Changwon National University (CWNU) (Mar. 2005 - Feb. 2009)

Work Experiences

• Post-doctoral Researcher, Singapore University of Technology and Design (SUTD), Singapore (Dev. 2021 - Present)
• Post-doctoral Researcher, Korea National University of Transportation (KNUT), South Korea (Jun. 2019 - Nov. 2021)
• Research Scientist, Seoul National University Hospital (SNUH), Seoul, South Korea (Apr. 2018 - Mar. 2019)

Honors and Awards

• Best Paper Reward (Grand Prize), Next Generation Computing Conference (2021)
• First Runner Up, Online Hackathon “AI Data for Panoramic Image of Road Environment” (2020)
• Qualcomm-GIST Innovation Award (IT Research Paper Award), School of EECS, GIST (Supported by Qualcomm) (2016)
• National Full-ride Scholarships, GIST (2009-2016)
• Student Travel Award, IEEE International Conference on Data Engineering (ICDE) (2015)
• First Runner Up, CWNU Programming Contest (2006)
• CWNU “NURI” Scholarships for Outstanding Students , CWNU, (2006-2009)

Professional Activities

• Reviewer in IJCC, ICCAIS, IJCVR, IJMTM, INRT, and PLOS One
• Teaching Assistant, Courses: Computer programming (2005), Programming Language Project (2006), Data Processing (2006) in CNU

Publications

International Journal

• Jaeyong Kang, Soujanya Poria, Dorien Herremans, “Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model”, Expert Systems with Applications (in press), 2024
• Younghoon Jeon, Jaeyong Kang, Byeong C Kim, Kun Ho Lee, Jong-In Song, Jeonghwan Gwak, “Early Alzheimer’s Disease Diagnosis using Wearable Sensors and Multilevel Gait Assessment: A Machine Learning Ensemble Approach”, IEEE Sensors Journal, 2023
• Jaeyong Kang, Chul-Su Kim, Jeong Won Kang, Jeonghwan Gwak, "Recurrent Autoencoder Ensembles for Brake Operating Unit Anomaly Detection on Metro Vehicles", Computers, Materials & Continua, 2023
• Jaeyong Kang, Jeonghwan Gwak, “Ensemble of Multi-task Deep Convolutional Neural Networks using Transfer Learning for Fruit Freshness Classsification”, Multimedia Tools and Applications, 2022.
• YoungHoon Jeon, Thi Kieu Khanh Ho, Jaeyong Kang, Byeong C Kim, Kun Ho Lee, Jong‐In Song, Jeonghwan Gwak, "Machine learning–based detection model of early Alzheimer's disease using wearable device and gait assessment", Alzheimer's & Dementia, 2021
• Jaeyong Kang, Chul-Su Kim, Jeong Won Kang, Jeonghwan Gwak, "Anomaly Detection of the Brake Operating Unit on Metro Vehicles Using a One-Class LSTM Autoencoder", Applied Sciences, 2021
• Jaeyong Kang, Zahid Ullah, Jeonghwan Gwak, “MRI-based Brain Tumor Classification using Ensemble of Deep Features and Machine Learning Classifiers”, Sensors, 2021.
• Jaeyong Kang, Jeonghwan Gwak, “Ensemble Learning of Lightweight Deep Learning Models using Knowledge Distillation for Image Classification”, Mathematics, 2020.
• Junho Ahn, Thi Kieu Khanh Ho, Jaeyong Kang, Jeonghwan Gwak, “Using Artificial Intelligence Methods for Dental Image Analysis: State-of-the-Art Reviews”, Journal of Medical Imaging and Health Informatics, 2020.
• Jaeyong Kang, Jeonghwan Gwak, “Ensemble of Instance Segmentation Models for Polyp Segmentation in Colonoscopy Images”, IEEE Access, 2019.
• Jaeyong Kang, HongSeok Choi, Hyunju Lee, “Deep Recurrent Convolutional Networks for Inferring User Interests from Social Media”, Journal of Intelligent Information Systems, 2019.
• Jaeyong Kang, Hyunju Lee, “Modeling User Interest in Social Media using News Media and Wikipedia”, Information Systems, 65, 52-64, 2017.
• Jaeyong Kang, Kwang Mong Sim, “Ontology-enhanced Agent-based Cloud Service Discovery”, International Journal of Cloud Computing. 2016.
• Jaeyong Kang, Kwang Mong Sim, “A Multiagent Brokering Protocol for Supporting Grid Resource Discovery”, Applied Intelligence, 37(4), 527–542, 2012.

International Conference

• Zixun Guo, Jaeyong Kang, Dorien Herremans, “A domain-knowledge-inspired music embedding space and a novel attention mechanism for symbolic music modeling”, Proc. of the AAAI Conference on Artificial Intelligence, 2023
• Zahid Ullah, Thi Kieu Khanh Ho, Hyunseok Lim, Jaeyong Kang, Jeonghwan Gwak, "COVID-19 Detection with a Semi-Supervised Adversarial Autoencoder in Chest Radiographs", The 16th Asia Pacific International Conference on Information Science and Technology (APIC-IST 2021), 2021
• Thi Kieu Khanh Ho, Hyunseok Lim, Jaeyong Kang, Jong-In Song, Jeonghwan Gwak, "A CNN-LSTM Model for Alzheimer’s Disease Multi-Class Classification using Multichannel EEG", The 16th Asia Pacific International Conference on Information Science and Technology (APIC-IST 2021), 2021
• Thi Kieu Khanh Ho, Zahid Ullah, Inki Kim, Hyunseok Lim, Jaeyong Kang, Jeonghwan Gwak, "Feature Integration for COVID-19 Classification using Chest Radiography", The 16th Asia Pacific International Conference on Information Science and Technology (APIC-IST 2021), 2021
• Jaeyong Kang, Jeonghwan Gwak, “KD-ResUNet++: Automatic Polyp Segmentation via Self-Knowledge Distillation”, Proc. of MediaEval, 2020.
• Jaeyong Kang, Kwang Mong Sim, “A Cloud Portal with A Cloud Service Search Engine”, Proc. of the 2011 International Conference on Information and Intelligent Computing (ICIIC’11), Hong Kong, 2011.
• Jaeyong Kang, Kwang Mong Sim, “Towards Agents and Ontology for Cloud Service Discovery”, Proc. of the 2011 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC’11), Beijing, China, 2011.
• Jaeyong Kang, Kwang Mong Sim, “Ontology and Search Engine for Cloud Computing System”, Proc. of the 2011 International Conference on System Science and Engineering (ICSSE’11), Macau, China, 2011.
• Jaeyong Kang, Kwang Mong Sim, “Cloudle: An Ontology-enhanced Cloud Service Search Engine”, Proc. of the 2010 International Workshop on Cloud Information System Engineering (CISE’10), Hong Kong, 2010.
• Jaeyong Kang, Kwang Mong Sim, “Cloudle: A Multi-criteria Cloud Service Search Engine”, Proc. of the 2010 IEEE Asia-Pacific Service Computing Conference (APSCC’10), Hangzhou, China, 2010.
• Jaeyong Kang, Kwang Mong Sim, “Cloudle : An Agent-based Cloud Search Engine that Consults a Cloud Ontology”, Proc. of the 2010 International Conference on Cloud Computing and Virtualization (CCV’10), Singapore, 2010.
• Jaeyong Kang, Kwang Mong Sim, “A Brokering Protocol for Agent-Based Grid Resource Discovery”, Proc. of the 2009 International Conference on Grid and Distributed Computing (GDC’09), Jeju Island, Korea, 2009.

Domesctic Journal

• Jaeyong Kang, Jeonghwan Gwak, “Deep Learning-Based Brain Tumor Classification in MRI images using Ensemble of Deep Features”, Journal of The Korea Society of Computer and Information, 2021.
• Jaeyong Kang, Jeonghwan Gwak, “Embedding similarity-based anomaly detection in crowd scenes via object-centric augmentation”, Journal of The Korea Society of Computer and Information, 2021
• Jaeyong Kang, Jeonghwan Gwak, “Adaptive Face Mask Detection System based on Scene Complexity Analysis”, Journal of The Korea Society of Computer and Information, 2021

Domestic Conference

• Jaeyong Kang, Inki Kim, Hyunseok Lim, Jeonghwan Gwak, "A Crack Detection of Wooden Cultural Assets using EfficientNet model", Proc. of the Korea Society of Computer and Informaton Summer Conference 2021, Jeju, Korea, 2021.
• Jaeyong Kang, Inki Kim, Hyunseok Lim, Jeonghwan Gwak, "A Bulge Detection Model in Cultural Asset images using Ensemble of Deep Features", Proc. of the Korea Society of Computer and Informaton Summer Conference 2021, Jeju, Korea, 2021.
• Jaeyong Kang, Inki Kim, Hyunseok Lim, Jeonghwan Gwak, "An Embedding Similarity-based Model for Detecting Displacement in Cultural Asset Images", Proc. of the Korea Society of Computer and Informaton Summer Conference 2021, Jeju, Korea, 2021.
• Jaeyong Kang, Inki Kim, Hyunseok Lim, Jeonghwan Gwak, "A Displacement Detection Model in Cultural Asset Images using Object-centric Augmentation", Proc. of the Korea Society of Computer and Informaton Summer Conference 2021, Jeju, Korea, 2021.
• Jaeyong Kang, Inki Kim, Hyunseok Lim, Jeonghwan Gwak, "An Ensemble Deep Learning Model for Measuring Displacement in Cultural Asset images", Proc. of the Korea Society of Computer and Informaton Summer Conference 2021, Jeju, Korea, 2021.
• Hyunseok Lim, Inki Kim, Jaeyong Kang, Jeonghwan Gwak, "Anomaly detection performance improvement technique through weight matrix-based optical flow equalization", Proc. of the Korea Society of Computer and Informaton Summer Conference 2021, Jeju, Korea, 2021.
• Jaeyong Kang, Hyunseok Lim, Dongwook Min, Zahid Ullah, Jeonghwan Gwak, "Anomaly detection system using ResUNet++ based image inpainting method", Next Generation Computing Conference 2021, Gwangju, Korea, 2021.
• Jaeyong Kang, Hyunseok Lim, Xufeng Hu, Jeonghwan Gwak, "Embedding similarity-based crowd anomaly detection using object centric augmentation", Next Generation Computing Conference 2021, Gwangju, Korea, 2021. (Best paper award)
• Jaeyong Kang, Hyunseok Lim, Inki Kim, Zahid Ullah, Jeonghwan Gwak, "Effective data preprocessing for a reconstruction model-based anomaly detection", Next Generation Computing Conference 2021, Gwangju, Korea, 2021.
• Dongwook Min, Hyunseok Lim, Thi Kieu Khanh Ho, Jaeyong Kang, Jeonghwan Gwak, "Cough Detection System Using Deep Learning", Next Generation Computing Conference 2021, Gwangju, Korea, 2021.
• Hyunseok Lim, Mingyu Kim, Jaeyong Kang, Jeonghwan Gwak, "Performance Comparison of SSIM loss function applied in the GAN-based anomaly detection system", Next Generation Computing Conference 2021, Gwangju, Korea, 2021.
• Inki Kim, Hyunseok Lim, Thi Kieu Khanh Ho, Jaeyong Kang, Jeonghwan Gwak, "Imbalanced Dataset training techniques with Hard negative mining and Sample Selection", Next Generation Computing Conference 2021, Gwangju, Korea, 2021.

Patents

• Hyunju Lee, Jaeyong Kang, “Method for Modeling User Interest in Social Media” (2017) (Korean Domestic; 1017679510000)