Ngoc-Huynh HO

I'm

About

I got PhD in Department of AI Convergence with training on problem solving, project proposal, coding (Python, Matlab, C#, bash), and extensive experience in data analysis of human emotion recognition via multimedia (video, speech, physiology) based on deep learning algorithms. By applying AI techniques in healthcare, I proposed potential solutions for monitoring long-term disease's progression.

Post-doctoral Researcher

  • Birthday: 3 March 1992
  • Phone: +82 062.530.0332
  • City: Gwangju, S. Korea
  • Degree: PhD in AI Convergence

Resume

Download CV

Education

PhD in AI Convergence

2017 - 2021

Chonnam National UniversityGwangju, S. Korea

“A Study on Prediction of Alzheimer’s Disease Progression Using Bidirectional-Progressive Recurrent Networks”. 2020.

MS in Electrical Engineering

2015 - 2017

Kookmin UniversitySeoul, S. Korea

“Distance Estimation Considering Varying Walking Speed for Smartphone PDR Using Adaptive Step-Length Estimation”. 2016

BE in Telecommunications

2010 - 2015

Hochiminh City University of TechnologyHochiminh, Vietnam

“Impact of Channel Estimation Error on the Performance of Relay Selection in Cognitive Radio Networks”. 2014

Professional Experience

Post-doctoral Research Fellow

Chonnam National University Gwangju, S. Korea
2021-Current
  • Development of DL model to predict the progression of Alzheimer's Disease;
  • Development of DL model to recognize human emotion from multiple modalities (visual, audio, text, neuro-physiological signals, persionality, etc.) and social interaction context.

Teaching Assistant

Chonnam National University Gwangju, S. Korea
2021-2023
  • Supporting and evaluating students in class Advanced Project for AI Convergence.

Research Assistant

Chonnam National University Gwangju, S. Korea
2020 (5 months)
  • Research and analyze the applications of AI in enhancing the security of biometrics authentication;
  • Research on context-based emotion recognition in the wild.

Research Visit

University of Oulu Oulu, Finland
2019 (2 weeks)
  • Visiting the Center for Machine Vision and Signal Analysis at the University of Oulu to learn the professional working environment here.
  • Discussing and sharing opinions about current trend on emotion recognition topics using ML/DL;

Teaching Assistant

Chonnam National University Gwangju, S. Korea
2018 (4 months)
  • Conduct necessary exercises of Data Structures course;
  • Provide an overall understanding of the data structures as well as an understanding of the classroom process;
  • Directly identify students' problems and help them to understand concepts and tools for working with data and have experience in analyzing real data.

Research Assistant

Kookmin University Seoul, S. Korea
2015 (6 months)
  • Working as a researcher in Smart Embedded System Lab (SESL);
  • Doing a project of LED-color display through audio jack communication.

Outreach

Sport Festival

Vietnamese Student Association in Korea S. Korea
2015-2016-2018
  • Participating an annual sport festival hold by the Vietnamese Students’ Association in Korea (VSAK) to have a meet, communication and solidarity of student community.

Spring Intership

Southern Power Information Technology Company Hochiminh, Vietnam
2014 (3 months)
  • Learning about the organizational structure of the IT company;
  • Using devices in server room and deployment of software applications using C-sharp.

Skills

Operating Systems

Windows90%
Linux70%

Programming Languages

Python90%
Matlab85%
Bash80%
Csharp80%
Java75%

Text Editors

Office90%
Latex90%

Languages

VietnameseMothertongue
EnglishPre-advanced
KoreanBasic

Projects

Disease’s Progression Prediction

Modelling the progression of long-term disease |

Alzheimer’s Disease (AD) Detection

Predicting the status of AD : NC, MCI, and AD dementia | YouTube

Bone Tumor Detection

Detecting the status of bone tumor from radiographics | YouTube

Multimodal Emotion Recognition

Identifying human emotional states from multi-source media: visual, audio, text, and neuro-physiology |

Indoor Human Localization

Estimating human walking steps using a smartphone for PDR |

Publications

621

Citations

34

Research Papers

4

Patents

PhD Thesis

  1. Ngoc-Huynh HO.
    “A Study on Prediction of Alzheimer's Disease Progression Using Bidirectional-Progressive Recurrent Networks”. Presented 10 Dec 2020.

Korean Patents

  1. HJ Yang, NH Ho, G Lee, SH Kim.
    “User emotion prediction system and method using deep learning-based graph fusion”. (March 09, 2023). DOI: 10-2023-0034012.
  2. HJ Yang, NH Ho, Jahae Kim.
    “A system and method for predicting progression of Alzheimer's Disease based on a Two-way network”. (April 27, 2021). DOI: 10-2019-0002323.
  3. HJ Yang, SH Kim, G Lee, NH Ho.
    “Voice emotion recognition method and system”. (February 23, 2021). DOI: 10-2019-0004760.
  4. HJ Yang, SH Kim, ST Jung, SD Joo, NH Ho, DS Tran.
    “System for detecting bone tumour”. (January 7, 2021). DOI: 10-2019-0002323.

Articles in Peer-Reviewed Journals

  1. AQ Duong, NH Ho, S Pant, S Kim, SH Kim, HJ Yang.
    “Residual Relation-Aware Attention Deep Graph-Recurrent Model for Emotion Recognition in Conversation”. In: IEEE Access 12 (2024), p. 11243. DOI: 10.1109/ACCESS.2023.3348518. IEEE
  2. NH Ho, HJ Yang, J Kim.
    “Multimodal multitask learning for predicting MCI to AD conversion using stacked polynomial attention network and adaptive exponential decay”. In: Scientific Reports 13 (2023), p. 11243. DOI: 10.1038/s41598-023-37500-7. Nature
  3. TD Tran, NH Ho, S Pant, HJ Yang, SH Kim, G Lee.
    “Cross-modality learning by exploring modality interactions for emotion reasoning”. In: IEEE Access 11 (2023), p. 56634-56648. DOI: 10.1109/ACCESS.2023.3283597. IEEE
  4. NH Ho, HJ Yang, J Kim, DP Dao, HR Park, S Pant.
    “Predicting progression of Alzheimer's disease using forward-to-backward bi-directional network with integrative imputation”. In: Neural Networks 150 (2022), p. 422-439. DOI: 10.1016/j.neunet.2022.03.016. Elsevier
  5. NH Ho, HJ Yang, SH Kim, G Lee, SB Yoo.
    “Deep Graph Fusion based Multimodal Evoked Expressions from Large-Scale Videos”. In: IEEE Access 9 (2021). DOI: 10.1109/ACCESS.2021.3107548. IEEE
  6. TD Tran, J Kim, NH Ho, HJ Yang, S Pant, SH Kim, G Lee.
    “Stress Analysis with Dimensions of Valence and Arousal in the Wild”. In: Applied Sciences 11.11 (2021), p. 5194. DOI: 10.3390/app11115194. MDPI
  7. DS Tran, NH Ho, HJ Yang, SH Kim, G Lee.
    “Real-time virtual mouse system using RGB-D images and fingertip detection”. In: Multimedia Tools and Applications 80 (2021), p. 10473-10490. DOI: 10.1007/s11042-020-10156-5. Springer
  8. NH Ho, HJ Yang, SH Kim, G Lee.
    “Multimodal approach of speech emotion recognition using multi-level multi-head fusion attention-based recurrent neural network”. In: IEEE Access 8 (2020), p. 61672-61686. DOI: 10.1109/ACCESS.2020.2984368. IEEE
  9. TLB Khanh, DP Dao, NH Ho, HJ Yang, ET Baek, G Lee, SH Kim, SB Yoo.
    “Enhancing U-Net with spatial-channel attention gate for abnormal tissue segmentation in medical imaging”. In: Applied Sciences 10.17 (2020), p. 5729. DOI: 10.3390/app10175729. MDPI
  10. DS Tran, NH Ho, HJ Yang, ET Baek, SH Kim, G Lee.
    “Real-time hand gesture spotting and recognition using RGB-D camera and 3D convolutional neural network”. In: Applied Sciences 10.2 (2020), p. 722. DOI: 10.3390/app10020722 MDPI
  11. NH Ho, HJ Yang, SH Kim, ST Jung, SD Joo.
    “Regenerative semi-supervised bidirectional W-network-based knee bone tumor classification on radiographs guided by three-region bone segmentation”. In: IEEE Access 7 (2019), p. 6825-6833. DOI: 110.1109/ACCESS.2019.2949125. IEEE
  12. TD Vu, NH Ho, HJ Yang, J Kim, HC Song.
    “Non-white matter tissue extraction and deep convolutional neural network for Alzheimer’s disease detection”. In: Soft Computing 22 (2018), p. 61672-61686. DOI: 10.1007/s00500-018-3421-5. Springer
  13. PH Truong, ND Nguyen, NH Ho, GM Jeong.
    “Nonparametric regression-based step-length estimation for arm-swing walking using a smartphone”. In: IJCCC 13.4 (2018), p. 566-573. DOI: 10.15837/ijccc.2018.4.3148. Univagora
  14. NH Ho, PH Truong, GM Jeong.
    “Step-detection and adaptive step-length estimation for pedestrian dead-reckoning at various walking speeds using a smartphone”. In: Sensors 16.9 (2016), p. 1423. DOI: 10.3390/s16091423. MDPI
  15. VK Ho, NK Doan, NH Ho.
    “Impact of channel estimation error on the performance of relay selection in cognitive radio networks”. In: Wireless Personal Communications 84 (2015), p. 2513–2536. DOI: 10.1007/s11277-015-2717-3. Springer

International Conferences/Proceedings

  1. NH Ho, HJ Yang, J Kim.
    “Prediction of Alzheimer's Disease Progression using Multiview Dense Residual Attention and Stack Polynomial Attention”. In: The 11th International Conference on Big Data Applications and Services. (BigDAS'23): Danang, Vietnam. August 16, 2023
  2. DP Dao, HJ Yang, G Lee, SH Kim, NH Ho, S Pant, SR Kang, IJ Oh.
    “Survival Analysis based on Lung Tumor Segmentation using Global Context-aware Transformer in Multimodality”. In: The 26th International Conference on Pattern Recognition. (ICPR'22): Montreal Quebec, Canada. August 21, 2022
  3. DK Nguyen, S Pant, NH Ho, G Lee, SH Kim, HJ Yang.
    “Affective Behavior Analysis using Action Unit Relation Graph and Multi-task Cross Attention”. In: The European Conference on Computer Vision Workshops. (ECCV'22): Tel Aviv, Israel. October 23, 2022
  4. AQ Duong, NH Ho, HJ Yang, G Lee, SH Kim
    “Multi-modal Stress Recognition Using Temporal Convolution and Recurrent Network with Positional Embedding”. In: The 2nd Multimodal Sentiment Analysis Challenge (MuSe'21): Chengdu, China, October 24, 2021. ACM Multimedia 2021.
  5. NH Ho, HJ Yang, J Kim, DP Dao, S Pant.
    “RASurv: Residual Attention-aware Method for Progression-free Survival of Alzheimer’s Disease”. In: The 5st International Conference on Big data, IoT, and Cloud Computing (BIC'21): Jeju Island, S. Korea, August 16-18, 2021.
  6. HD Le, HJ Yang, NH Ho, S Pant.
    “Attention-based Image and Text Fusion for Deep Multimodal Classification in Disaster Analysis”. In: The 5st International Conference on Big data, IoT, and Cloud Computing (BIC'21): Jeju Island, S. Korea, August 16-18, 2021.
  7. DP Dao, NH Ho, J Kim, HJ Yang.
    “Improving Recurrent Gate Mechanism For Time-to-Conversion Prediction Of Alzheimer’s Disease”. In: The 9th International Conference on Smart Media and Applications (SMA'20): Jeju Island, S. Korea, September 17-19, 2020.
  8. NH Ho, HJ Yang, HC Song, J Kim.
    “ADeepTool: Application Tool for Alzheimer’s Disease Diagnosis Based on Deep Learning Approach”. In: The 7th International Conference on Big Data Applications and Services (BigDAS'19): Jeju Island, S. Korea, August 21-24, 2019.
  9. NH Ho, HJ Yang, LN Do, SH Kim, G Lee.
    “Early Fusion-based Emotion Recognition Using Multiple Audio Features from GMM Supervector and Deep Convolutional Neural Network”. In: The 6th International Conference on Big Data Applications and Services (BigDAS'18): Zhengzhou, China, August 19-22, 2018.
  10. DS Tran, HJ Yang, SH Kim, GS Lee, LN Do, NH Ho, VQ Nguyen.
    “Audio-based emotion recognition using GMM supervector an SVM linear kernel”. In: The 2nd International Conference on Machine Learning and Soft Computing (ICMLSC'18): Phu Quoc Island, Vietnam, February, 2018.
  11. LN Do, HJ Yang, NH Ho, SH Kim, G Lee.
    “A Fusion Model for Emotion Recognition from Audio- Video Data”. In: The 5th International Conference on Big Data Applications and Services (BigDAS'17): Jeju Island, S. Kore, November 23-25, 2017.
  12. TD Vu, NH Ho, JM Joo, SH Kim, YC Kim, HJ Yang, J Kim, HC Song.
    “Detect Alzheimer’s disease by Multimodal Deep Learning Network using Convolutional Autoencoder”. In: The 1st International Conference on Big data, IoT, and Cloud Computing (BIC'17): Jeju Island, S. Korea, August 22-24, 2017.

Korean Journals/Conferences/Proceedings

  1. TC Do, HJ Yang, NH Ho.
    “Application of Deep Recurrent Q Network with Dueling Architecture for Optimal Sepsis Treatment Policy”. In: Smart Media Journals 10 (2021). 10.30693/SMJ.2021.10.2.48. 스마트미디어저널
  2. AQ Duong, NH Ho, HJ Yang, SH Kim, G Lee, AR Oh.
    “Multimodal Deep Graph Fusion for Evoked Expression Recognition in Large-Scale Videos”. In: 2021 Conference of Korea Computer Congress (KCC'21): Jeju Island, S. Korea, June 23-25, 2021.
  3. NH Ho, HJ Yang, J Kim, H Jeong.
    “A Comparative Study for Estimation of Time to Alzheimer's Disease based on Machine Learning Regressors”. In: 2020 Spring Conference of Korean Institute of Smart Media (KISM'20): Gwangju, S. Korea, May 22-23, 2020.
  4. NH Ho, HJ Yang, SH Kim, G Lee.
    “Group-based Cohesion Prediction using Multi-Task Learning and Confidence of Adaptive Ranging”. In: 2019 August Conference of Korean Institute of Smart Media (KISM'19): Gwangju, S. Korea, November 07-08, 2019.
  5. NH Ho, HJ Yang, SH Kim, G Lee.
    “Textual Emotion Recognition Based on Recurrent Neural Network for Conscious Conservation”. In: 2019 Spring Conference of Korean Institute of Smart Media (KISM'19): Chungju, S. Korea, April 26-27, 2019.
  6. NH Ho, HJ Yang, SH Kim, ST Jeong, SD Joo.
    “End-to-end Knee Bone Tumor Classification from Radiographs Based on Semi-Supervised Ensemble Wnet”. In: 2018 August Conference of Korean Multimedia Society (KMS'18): Gwangju, S. Korea, October 20, 2018.
  7. NH Ho, DS Tran, JM Joo, HJ Yang, SH Kim, ST Jung, SD Joo.
    “Bone Area Segmentation in X-Ray images using an Adaptable U-Net”. In: 2018 Conference of Korea Computer Congress (KCC'18): Jeju Island, S. Korea, June 20-22, 2018.

References

Hyung-Jeong YANG

Professor

Department of AI Convergence

Chonnam National University

SCLab

Gu-Min Yeong

Professor

School of Electrical Engineering

Kookmin University

SESLab

Soo-Hyung Kim

Professor

Department of AI Convergence

Chonnam National University

PRLab

Jahae Kim

Assistant Professor

Department of Nuclear Medicine

Chonnam National University Hospital

Contact

Use the following - or the ones at the top of the page - to get in touch

Location:

SCLab, Chonnam National University, Gwangju, S. Korea

Call:

+82 062.530.0332