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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 Master’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

🎓 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)

🏫 Professional Experience

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

🏆 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)

🌱 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: 306–310
    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: 666–673
    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.

🏆 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.

ABEL YU HAO CHAI | DEEP LEARNING | BEST RESEARCHER AWARD

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