Professor

Phạm Huy Hiệu

Affiliation: VinUni-Illinois Smart Health Center, Hanoi, Viet Nam

College of Engineering and Computer Science

hieu.ph@vinuni.edu.vn

Introduction

Dr. Pham Huy Hieu is a Teaching Fellow at the College of Engineering and Computer Science (CECS), VinUniversity, and a Research Fellow at VinUni-Illinois Smart Health Center. He received his Ph.D. in Computer Science from the Toulouse Computer Science Research Institute (IRIT), University of Toulouse, France, in 2019. Previously, he earned the Degree of Engineer in Industrial Informatics from Hanoi University of Science and Technology (HUST), Vietnam, in 2016. His research interests include Computer Vision, Machine Learning, Medical Image Analysis, and their applications in Smart Healthcare. He is the author, co-author of 30 scientific articles appeared in about 20 conferences and journals such as Computer Vision and Image Understanding, Neurocomputing, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Medical Imaging with Deep Learning (MIDL), IEEE International Conference on Image Processing (ICIP), and IEEE International Conference on Computer Vision (ICCV). He is also currently serving as Reviewers for MICCAI, ICCV, CVPR, IET Computer Vision Journal (IET-CVI), IEEE Journal of Biomedical and Health Informatics (JBHI), and Nature Scientific Reports. Before joining VinUniversity, Dr. Hieu worked at Vingroup Big Data Institute (VinBigData) as a Research Scientist and Head of the Fundamental Research Team. With this position, he led several research projects on Medical AI, including collecting various types of medical data, managing and annotating data, and developing new AI solutions for medical analysis. More details about his research and teaching works are available at https://huyhieupham.github.io/

Affiliation: VinUni-Illinois Smart Health Center, Hanoi, Viet Nam

Research Output

Human sleep position classification using a lightweight model and acceleration data

Vu Hoang-Dieu, Tran Duc-Nghia, Pham Huy-Hieu, Pham Dinh-Dat, Can Khanh-Ly, Dao To-Hieu, Tran Duc-Tan
  • Accelerometer-based wearable
  • Deep learning classification
  • GERD
  • Positional therapy
  • Sleep position monitoring
  • Sleep posture

SEMISE: Semi-Supervised Learning for Severity Representation in Medical Image

Tran Dung T., Vu Hung, Tran Anh, Hoang Tuan, Pham Hieu, Nguyen Hong, Nguyen Nam-Phong
  • Constractive Learning
  • Medical Image
  • Semi-Supervised Learning
  • Severity Representation

CT to PET Translation: A Large-Scale Dataset and Domain-Knowledge-Guided Diffusion Approach

Nguyen Dac Thai, Nguyen Trung Thanh, Nguyen Huu Tien, Nguyen Thanh Trung, Pham Huy Hieu, Nguyen Thanh Hung, Truong Thao Nguyen, Le Nguyen Phi

Machine learning techniques for coffee classification: a comprehensive review of scientific research

Motta Isabela V. C., Vuillerme Nicolas, Pham Huy-Hieu, de Figueiredo Felipe A. P.
  • Artificial intelligence
  • Coffee beans and leaves classification
  • Computer vision
  • Machinelearning

BG-GAN: Generative AI Enable Representing Brain Structure-Function Connections for Alzheimer’s Disease

Zhou Tong, Ding Chen, Jing Changhong, Liu Feng, Hung Kevin, Pham Hieu, Mahmud Mufti, Lyu Zhihan, Qiao Sibo, Wang Shuqiang, Tsang Kim-Fung, ...
  • Alzheimer’s Disease
  • balancer
  • Bidirectional mapping
  • brain imaging
  • graph generative adversarial network

IncepSE: Leveraging InceptionTime’s performance with Squeeze and Excitaion mechanism in ECG analysis

Cao Tue, Tran Nhat, Nguyen Le, Nguyen Hung, Pham Hieu
  • Computer vision
  • ECG
  • Inception
  • Squeeze and Excitation
  • Timeseries classification

FedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for Non-IID Data in Federated Learning

Nguyen Nang Hung, Nguyen Phi Le, Nguyen Thuy Dung, Nguyen Trung Thanh, Nguyen Duc Long, Nguyen Thanh Hung, Pham Huy Hieu, Truong Thao Nguyen
  • Data Heterogeneity
  • Deep Reinforcement Learning
  • Federated Learning

Deployment and validation of an AI system for detecting abnormal chest radiographs in clinical settings

Nguyen Ngoc Huy, Nguyen Ha Quy, Nguyen Nghia Trung, Nguyen Thang Viet, Pham Hieu Huy, Nguyen Tuan Ngoc-Minh
  • chest X-ray (CXR)
  • clinical validation
  • Computer-Aided Diagnosis
  • deep learning
  • Picture Archiving and Communication System (PACS)

Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels

Pham Hieu H., Le Tung T., Tran Dat Q., Ngo Dat T., Nguyen Ha Q.
  • Chest X-ray
  • CheXpert
  • Hierarchical learning
  • Label dependency
  • Label smoothing
  • Multi-label classification
  • Uncertainty label

Fingerprint

Keyphrases

  • Accelerometer-based wearable
  • Deep learning classification
  • GERD
  • Positional therapy
  • Sleep position monitoring
  • Sleep posture
  • Constractive Learning
  • Medical Image
  • Semi-Supervised Learning
  • Severity Representation
  • Artificial intelligence
  • Coffee beans and leaves classification
  • Computer vision
  • Machinelearning
  • Alzheimer’s Disease
  • balancer
  • Bidirectional mapping
  • brain imaging
  • graph generative adversarial network
  • ECG
  • Inception
  • Squeeze and Excitation
  • Timeseries classification
  • Data Heterogeneity
  • Deep Reinforcement Learning
  • Federated Learning
  • chest X-ray (CXR)
  • clinical validation
  • Computer-Aided Diagnosis
  • deep learning
  • Picture Archiving and Communication System (PACS)
  • Chest X-ray
  • CheXpert
  • Hierarchical learning
  • Label dependency
  • Label smoothing
  • Multi-label classification
  • Uncertainty label

Computer Science


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  • Otorhinolaryngology

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