ABEL YU HAO CHAI | DEEP LEARNING | BEST RESEARCHER AWARD

Posted on by ScienceFather

Mr. ABEL YU HAO CHAI | DEEP LEARNING | BEST RESEARCHER AWARD

PHD at SWINBURNE UNIVERSITY OF TECHNOLOGY SARAWAK CAMPUS Malaysia

Abel Chai Yu Hao is a PhD candidate at Swinburne University of Technology Sarawak, specializing in computer vision, machine learning, and deep learning. His research focuses on developing interpretable deep learning models for plant disease identification, collaborating with CIRAD and INRIA on innovative agricultural projects. With a Masterā€™s degree in wireless communication, Abel has contributed to improving rural connectivity in Sarawak through cost-effective wireless solutions. He has co-authored numerous journal articles and conference papers on topics ranging from unseen plant disease recognition to wireless data transmission. Abel is a recipient of multiple awards, including the Gold Award at the Innovation Technology Exposition 2023, and is an active IEEE member.

scholar

šŸŽ“ Education

Doctor of Philosophy (2022 – Present) Swinburne University of Technology Sarawak Campus Research focus: Computer Vision, Machine Learning, Deep Learning, AI. Master of Engineering (2019 – 2021) Swinburne University of Technology Sarawak Campus Research focus: Wireless communication, Wi-Fi, Rural connectivity. Bachelor of Engineering (Honours), Electrical & Electronics Engineering (2014 – 2018) Swinburne University of Technology Sarawak Campus CGPA: 3.97/4 (High Distinction)

šŸ« Professional Experience

Teaching Assistant (2019 – Present) Swinburne University of Technology Sarawak Campus Assisting in course delivery, tutorials, and research guidance

šŸ† Awards & Scholarships

Gold Award in Innovation Technology Exposition (2023). Best Paper Award at International UNIMAS Engineering Conference (EnCon) (2020). Sarawak Energy External Scholarship (2015-2018). Swinburne Entrance Scholarship (2014)

šŸŒ± Research Projects

Plant Disease Identification with Deep Learning (2022 – ongoing) Collaborating with experts from CIRAD, INRIA, focusing on AI-based plant disease detection. Rural Internet Connectivity Solutions (2019 – 2021) Conducted cost-performance analysis for wireless solutions in partnership with Sarawak Multimedia Authority (SMA)

Publication

  • Pairwise Feature Learning for Unseen Plant Disease Recognition
    Conference: International Conference on Image Processing (ICIP)
    Year: 2023
    Pages: 306ā€“310
    Contributors: Hao Chai A.Y., Han Lee S., Tay F.S., Bonnet P., Joly A.

 

  • Unveiling Robust Feature Spaces: Image vs. Embedding-Oriented Approaches for Plant Disease Identification
    Conference: Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
    Year: 2023
    Pages: 666ā€“673
    Contributors: Ishrat H.A., Chai A.Y.H., Lee S.H., Then P.H.H.

 

  • Development and Application of Outdoor Router Cost Estimation with Parametric Modelling Technique
    Conference: IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
    Year: 2022
    Contributors: Chai A.Y.H., Lai C.H., Tay F.S., Lim N.C.Y., Vithanawasam C.K.

 

  • Model Study for Outdoor Data Transmission Performance
    Conference: IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
    Year: 2022
    Contributors: Chai A.Y.H., Then Y.L., Tay F.S., Lim N.C.Y., Vithanawasam C.K.

 

  • Parametric Model Study for Outdoor Routers Cost Estimation
    Conference: 13th International UNIMAS Engineering Conference (EnCon)
    Year: 2020
    Contributors: Hao Chai A.Y., Hung Lai C., Su H.T., Siang Tay F., Yong L.

šŸ† Conclusion:

Abel Chai Yu Hao is a highly qualified candidate for the Best Researcher Award, given his solid academic background, impactful publications, international collaborations, and ongoing contributions to the field of AI and wireless communication. With continuous focus on expanding his research and increasing engagement, his profile can only continue to rise.

Weihua Liu| AI | Best Researcher Award

Posted on by ScienceFather

Ā Dr. Weihua Liu| AI | Best Researcher Award

Ā Dr at AthenaEyesCO., LTD. China

With extensive contributions to academia and industry, I’ve authored over 20 influential papers and filed more than 80 patents, underscoring my commitment to innovation at the intersection of AI and healthcare. My career spans leadership in national science foundation projects and pioneering advancements in medical imaging and diagnostic technologies.

Profile

  1. Orcid

šŸŽ“Education

Post-Doctoral Research Beijing Institute of Technology, School of Medical Technology (Nov 2021 – Jun 2024) Co-supervisor: Chen Duanduan, Focus: Construction and Application of Medical Multi-modal Large Models. PhD in Computer Science Beijing Institute of Technology, School of Computer Science (Sep 2014 – Jun 2021) Supervisor: Liu Xiabi Dissertation: “Deep Network Structure and Its Learning Method Based on Pulmonary Nodule Detection and Lung Parenchyma Segmentation”. Bachelor’s and Master’s Degrees Changsha University of Science and Technology, School of Computer and Communication Engineering Bachelor’s Degree in Computer Science and Technology (Sep 2002 – Jun 2006), Master’s Degree in Software Engineering and Theory (Graduated Jun 2009), Research Focus: Image Processing and Pattern Recognition

šŸ”¬Research Projects

National Natural Science Foundation of China Project: Research on Intelligent Assessment Method for Stroke Risk Based on High-Risk Carotid Plaque-Complex Blood Flow Image Feature Analysis (2023-2026). Beijing Natural Science Foundation Project: Research on the Model of Acute Respiratory Distress Syndrome Assisted Diagnosis and Treatment Based on AI and Data Mining (2023-2026). Changsha Major Science and Technology Special Project Research and Application of Trustworthy Intelligent Vision Key Technologies in 5G Environment (2020-2023)

šŸš€ Professional Experience:

As an AI Algorithm Scientist at 3M’s Beijing Research and Development Center, I spearheaded the development of the BAX framework, a unified cross-platform AI deployment system widely adopted in biometric intelligence systems globally.

šŸ’” Patents:

I’ve filed over 80 patents, showcasing my innovations in areas like multimodality-based medical models, facial recognition, and medical identity authentication.

šŸŒŸ Research Expertise:

With a profound focus on AI and healthcare intersections, I bring extensive theoretical knowledge in biometric technology, physiological and psychological computing, and medical assistant diagnosis.

Publications Top Notes šŸ“

  • Shape-margin knowledge augmented network for thyroid nodule segmentation and diagnosis
    • Year: 2024
    • Authors: Liu, Weihua; Lin, Chaochao; Chen, Duanduan; Niu, Lijuan; Zhang, Rui; Pi, Zhaoqiong
    • Source: Computer Methods and Programs in Biomedicine

 

  • A pyramid input augmented multi-scale CNN for GGO detection in 3D lung CT images
    • Year: 2023
    • Authors: Liu, Weihua; Liu, Xiabi; Luo, Xiongbiao; Wang, Murong; Han, Guanghui; Zhao, Xinming; Zhu, Zheng
    • Source: Pattern Recognition

 

  • Stone needle: A general multimodal large-scale model framework towards healthcare
    • Year: 2023
    • Authors: Liu, Weihua; Zuo, Yong
    • Source: arXiv preprint arXiv:2306.16034

 

  • Contraction Mapping of Feature Norms for Data Quality Imbalance Learning
    • Year: 2022
    • Authors: Liu, Weihua; Liu, Xiabi; Li, Huiyu; Lin, Chaochao
    • Source: Available at SSRN 4250246

 

  • Integrating lung parenchyma segmentation and nodule detection with deep multi-task learning
    • Year: 2021
    • Authors: Liu, Weihua; Liu, Xiabi; Li, Huiyu; Li, Mincan; Zhao, Xinming; Zhu, Zheng
    • Source: IEEE Journal of Biomedical and Health Informatics

 

  • A new three-stage curriculum learning approach for deep network based liver tumor segmentation
    • Year: 2020
    • Authors: Li, Huiyu; Liu, Xiabi; Boumaraf, Said; Liu, Weihua; Gong, Xiaopeng; Ma, Xiaohong
    • Source: 2020 International Joint Conference on Neural Networks (IJCNN)

 

  • URDNet: a unified regression network for GGO detection in lung CT images
    • Year: 2020
    • Authors: Liu, Weihua; Ren, Yuchen; Li, Huiyu
    • Source: Wireless Communications and Mobile Computing

 

  • Content-sensitive superpixel segmentation via self-organization-map neural network
    • Year: 2019
    • Authors: Wang, Murong; Liu, Xiabi; Soomro, Nouman Q; Han, Guanhui; Liu, Weihua
    • Source: Journal of Visual Communication and Image Representation

 

  • Hybrid resampling and multi-feature fusion for automatic recognition of cavity imaging sign in lung CT
    • Year: 2019
    • Authors: Han, Guanghui; Liu, Xiabi; Zhang, Heye; Zheng, Guangyuan; Soomro, Nouman Qadeer; Wang, Murong; Liu, Weihua
    • Source: Future Generation Computer Systems