Wearable Sensing and Human Safety
IMU sensor placement, fall-direction classification, multimodal sensing, and practical human detection systems.
RESEARCH / PUBLICATIONS / SCHOLAR
Research that connects intelligent systems with people, language, and education.
I study practical deep-learning systems across wearable sensing, human safety, medical imaging, computer vision, and VR-based research on child development and mental well-being. This page combines my verified Google Scholar record with my current research directions.
01 / RESEARCH DIRECTIONS
Core areas of inquiry.
Medical and Clinical AI
Deep-learning systems for ultrasound plane prediction and interpretable medical image analysis.
Computer Vision for Agriculture
Visual recognition for plant health, leaf-disease classification, and intelligent smart-farm applications.
Generative and Secure Imaging
Image generation, information security, coverless steganography, and applied deep-learning architectures.
Child Development and Mental Well-being in VR
VR-based interactive content, behavioral observation, and AI-assisted analysis to study developmental patterns and mental well-being in children.
CURRENT FOCUS / VR & CHILD DEVELOPMENT
Human-centered VR for understanding child development.
I am exploring how carefully designed VR content and behavioral data can support the analysis of children's developmental patterns and mental well-being, with an emphasis on age-appropriate experiences, responsible interpretation, and human-centered evaluation.
Immersive contentDevelopmental analysisMental well-being
02 / METHODS
A practical research toolkit.
My work moves from sensor and image data through feature design, model development, and careful evaluation, with an emphasis on useful systems for health, safety, child development, and agriculture.
01Machine learning
02Feature engineering
03Computer vision
04Multimodal sensing
05Medical image analysis
06Human-centered evaluation
07VR/XR experience design
08Behavioral data analysis
03 / PUBLICATIONS
Google Scholar publication list.
Six publications verified from the public Scholar profile. Citation counts below are a October 2026 snapshot; Scholar remains the live source.
01
Artificial intelligence assisted common maternal fetal planes prediction from ultrasound images based on information fusion of customized convolutional neural networks
F. Rauf, M. Attique Khan, H. M. Albarakati, K. Jabeen, S. Alsenan, A. Hamza, et al.
02
Analyzing optimal wearable motion sensor placement for accurate classification of fall directions
S. Teng, J. Y. Kim, S. Jeon, H. W. Gil, J. Lyu, E. H. Chung, K. S. Kim, Y. Nam
03
A new generative mathematical model for coverless steganography system based on image generation
A. H. Seddik, M. Salah, G. Behery, A. El-harby, A. I. Ebada, S. Teng, Y. Nam, et al.
04
Fruit and Vegetable Leaf Disease Recognition based on a Novel Custom Convolutional Neural Network and Shallow Classifier
S. A. F. Naqvi, M. A. Khan, A. Hamza, S. Alsenan, M. Alharbi, S. Teng, Y. Nam
05
A novel interpreted deep network for Alzheimer’s disease prediction based on inverted self attention and vision transformer
W. Ibrar, M. A. Khan, A. Hamza, S. Rubab, O. Alqahtani, M. T. H. Alouane, et al.
06
Multi-sensor-based fall detection and direction classification
다중 센서 기반의 낙상 검출 및 방향 분류
H. J. Shin, S. Teng, Y. Nam, J. Y. Woo
Research identity
Deep learning and ICT research spanning sensing, vision, health, safety, child development, immersive technology, and agricultural applications.
Khmer perspective
A Cambodian research identity expressed through clear communication, cultural design, and globally relevant AI work.
Education bridge
Translate research into understandable articles, resources, lectures, and future learning modules.