Mr. Abel chai Yu hao – DEEP LEARNING – Young Scientist Award

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Mr. Abel chai Yu hao - DEEP LEARNING - Young Scientist Award

SWINBURNE UNIVERSITY OF TECHNOLOGY SARAWAK CAMPUS - Malaysia

Author Profile

ORCID

Early academic pursuits 🎓

Abel chai Yu hao began his academic journey in electrical and electronics engineering at swinburne university of technology, sarawak campus, where he graduated with first-class honors in 2018, achieving an impressive cgpa of 3.97/4. his final year project, focused on wireless communication using led technology, sparked his interest in cutting-edge fields of wireless systems. prior to this, abel completed his malaysian higher school certificate (stpm) at smk sungai tapang in sarawak, malaysia, demonstrating early potential with a solid cgpa of 3.17/4.

Professional endeavors 🏢

Following his undergraduate success, abel advanced to a master's in engineering at swinburne university, specializing in wireless communication and rural connectivity. during this period, he further developed his technical expertise, contributing to initiatives that aimed at improving rural connectivity through wi-fi technologies. now, as a doctoral candidate at swinburne university, abel's research focuses on computer vision, machine learning, deep learning, and artificial intelligence, positioning him at the forefront of innovation in these fields.

Contributions and research focus 🔬

Abel’s primary research contributions lie in the field of artificial intelligence and wireless communications. during his master's program, he DEEP LEARNING focused on wireless networks in rural areas, where his work contributed to enhancing wi-fi-based solutions for remote connectivity. his current phd research explores the integration of computer vision and deep learning, investigating novel approaches to advance the capabilities of ai-driven systems. his work holds the potential to revolutionize both communication systems and intelligent automation processes.

Accolades and recognition 🏅

throughout his academic career, abel has been recognized for his academic excellence and research contributions. graduating with high distinction in his bachelor's program, abel’s achievements have earned him accolades from swinburne university. his dedication and research DEEP LEARNING potential have also led to his current pursuit of a phd, where he is recognized for his work in artificial intelligence and computer vision.

Impact and influence 🌍

Abel’s work, particularly in rural connectivity and artificial intelligence, has the potential to make a significant impact. by focusing on wireless communication solutions for underserved regions, abel has helped to bridge the digital divide. his ongoing research in ai and machine learning DEEP LEARNING could lead to advancements in automated systems that have applications across industries, including healthcare, security, and communications, bringing tangible benefits to society.

Legacy and future contributions 🔮

Abel chai yu hao’s academic and research journey reflects a strong commitment to pushing the boundaries of technology. his contributions to rural wireless connectivity and his current research in computer vision will continue to influence future technological developments. as he advances in his phd studies, his innovative ideas are set to leave a lasting legacy in the fields of ai and machine learning, and his work will undoubtedly inspire future generations of engineers and researchers.

Notable Publications

Beyond supervision: Harnessing self-supervised learning in unseen plant disease recognition 2024

Revolutionizing Plant Pathogen Conservation: The Past, Present, and Future of AI in Preserving Natural Ecosystems  2024

Prof. Hao tang – Computer Vision and Pattern Recognition – Best Researcher Award

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Prof. Hao tang - Computer Vision and Pattern Recognition - Best Researcher Award

Peking University - China

Author Profile

SCOPUS

📚 Early academic pursuits

Hao tang began his academic journey at peking university (pku), where he pursued a master’s degree in computer application technology under the mentorship of prof. hong liu from 2013 to 2016. his foundational education at pku laid the groundwork for his future endeavors in computer vision and artificial intelligence. during this period, he honed his skills in computer science, which later became pivotal in his research and professional career.

🏛️ Professional endeavors

after completing his m.s. at peking university, hao tang embarked on a diverse and global academic career. he earned his ph.d. at the university of trento, italy, under the guidance of prof. nicu sebe in the multimedia and human understanding group (mhug). following his ph.d., he joined eth zurich as a postdoctoral fellow, working closely with prof. radu timofte and prof. luc van gool at the computer vision laboratory (cvl). his postdoctoral journey continued at carnegie mellon university (cmu) in the usa, where he contributed to the robotics institute under prof. fernando de la torre. currently, hao tang serves as an assistant professor at the school of computer science at peking university, marking his return to his alma mater with a tenure-track position.

🔬 Contributions and research focus

hao tang’s research spans across multiple facets of artificial intelligence and computer science, with a strong focus on aigc (ai-generated content), ai4science, large language models (llm), computer vision, machine learning, and embodied ai. his work has been influential in advancing the Computer Vision and Pattern Recognition capabilities of ai in various domains, particularly in the intersection of machine learning and computer vision. his contributions are well-documented in his extensive list of publications, including significant papers on motion generation, medical image segmentation, and efficient pruning of large language models.

🏆 Accolades and recognition

hao tang’s work has garnered recognition in the global academic community. his academic journey is marked by prestigious positions at some of the world’s leading institutions, including eth zurich, carnegie mellon university, and peking university. his publications, often featured in high-impact journals and conferences, reflect his significant contributions to the field of computer science. the impact of his research is further Computer Vision and Pattern Recognition highlighted by his role as a corresponding author on several influential papers.

🌍 Impact and influence

the influence of hao tang’s research extends beyond academia, contributing to the broader field of artificial intelligence and its applications in science and technology. his work on aigc and ai4science, in particular, has paved the way for innovative approaches in ai-driven content Computer Vision and Pattern Recognition generation and scientific discovery. his research on large language models and computer vision has had a profound impact on the development of more efficient and effective ai systems, influencing both academic research and practical applications in the industry.

🧠 Legacy and future contributions

hao tang’s career is still in its early stages, but his contributions have already left a lasting legacy in the field of computer science. as an assistant professor at peking university, he is poised to continue his research and mentor the next generation of computer scientists. his work promises to push the boundaries of ai and machine learning, with potential future contributions that could further revolutionize these fields. his ongoing research and academic endeavors suggest a bright future filled with impactful discoveries and innovations.

Notable Publications

Graph Transformer GANs with Graph Masked Modeling for Architectural Layout Generation 2024

Monocular Expressive 3D Human Reconstruction of Multiple People  2024

Quasar-ViT: Hardware-Oriented Quantization-Aware Architecture Search for Vision 2024

G2P-DDM: Generating Sign Pose Sequence from Gloss Sequence with Discrete Diffusion Model 2024

Mining and Unifying Heterogeneous Contrastive Relations for Weakly-Supervised Actor-Action 2024

Dr. Yosr Ghozzi – Deep learning – Excellence in Research

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Dr. Yosr Ghozzi - Deep learning - Excellence in Research

University of Sfax - Tunisia

AUTHOR PROFILE

SCOPUS

ORCID

EARLY ACADEMIC PURSUITS 🎓

Yosr Ghozzi embarked on her academic journey with a strong focus on technological innovation and medical applications. She earned her Ph.D. from the National Engineering School of Sfax (ENIS) in 2022, which marked the beginning of her career as a teacher-researcher. Her academic background is rooted in artificial intelligence, deep learning, and medical imaging, laying the foundation for her future contributions to the field.

PROFESSIONAL ENDEAVORS 🏥

Since 2022, Yosr has been a dedicated teacher and researcher at ISIMS/University of Sfax in Tunisia. Her work is characterized by a strong focus on artificial intelligence and its applications in medical diagnostics. Her role as a researcher has allowed her to contribute significantly to both academic and industrial projects, with a notable project being the KAFSS, which involves molecular kits and digital applications for facial prediction and dysmorphia.

CONTRIBUTIONS AND RESEARCH FOCUS 🔬

Yosr's research is at the intersection of artificial intelligence and medical imaging. She has made significant strides in the use of deep learning Deep learning combined with fuzzy logic to address the challenges of content-based image retrieval (CBIR) systems. Her work in this area is particularly relevant for computer-aided diagnosis, where CBIR systems can aid in detecting abnormalities and classifying medical images based on their content and medical context.

ACCREDITATIONS AND RECOGNITION 🏆

Yosr's contributions to research have not gone unnoticed. In 2022, she was awarded the prestigious title of Best Innovative Researcher at TICAD 8. Her research has also been published in two journals indexed by SCI and Scopus, and she has been involved in the editorial process of six Deep learning conferences, further establishing her as a recognized figure in her field.

IMPACT AND INFLUENCE 🌍

Yosr's research has a significant impact on the medical and technological fields, particularly in the development of advanced diagnostic tools. Her collaboration with international researchers from the University of Essex and the University of Johannesburg highlights her global influence. Her Deep learning work in AI and deep learning contributes to improving the accuracy and efficiency of medical diagnostics, potentially saving lives through early detection and intervention.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Yosr Ghozzi is set to leave a lasting legacy in the fields of artificial intelligence and medical imaging. Her innovative approaches to using deep learning for medical applications position her as a pioneer in her field. As she continues her research, Yosr's contributions will likely inspire future advancements in AI-driven healthcare solutions, ensuring her work's lasting impact on both academia and the medical community.

NOTABLE PUBLICATIONS

Interval Type-2 Beta Fuzzy Near Sets Approach to Content-Based Image Retrieval 2022(13)

Competencies based curricula (Electro-Mechanical Department Case Study) 2019(1)

A beta-fuzzy-near-sets approach to research for visually similar content images 2017(3)

A novel method for resemblance images using near fuzzy set 2016(2)

Modelling and numerical simulation of thick sheet double slitting process using continuum 2014(7)