Lili Nurliyana Abdullah – computer technology – Best Researcher Award

Published on 21/05/202421/05/2024 by Civil Engineering

Lili Nurliyana Abdullah - computer technology - Best Researcher Award

UPM - Malaysia

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Lili Nurliyana Abdullah's academic journey began with a Diploma in Computer Science from Universiti Pertanian Malaysia in 1990. She went on to earn a Bachelor's degree in Computer Science from Universiti Putra Malaysia in 1992, graduating with a 2nd Class Upper division. Her pursuit of higher education continued in the UK, where she obtained a Master in Engineering with a specialization in Telematics from the University of Sheffield in 1996. Lili's academic endeavors culminated in a Ph.D. in Information Science from the National University of Malaysia in 2007.

PROFESSIONAL ENDEAVORS

Lili's professional career spans various prestigious roles and institutions. She started as a tutor in Computer Science at UPM in 1993 and progressed to become a lecturer and then an Associate Professor in the Multimedia Department. She also served as the Head of the Multimedia Department at UPM from 2009 to 2012. Beyond academia, she worked as a Project Consultant at Catapult Studios and held teaching attachments and training roles at several universities, including Univ Taibah in Saudi Arabia and L.N. Gumilyov Eurasian National University in Kazakhstan.

CONTRIBUTIONS AND RESEARCH FOCUS

Lili Nurliyana Abdullah's research primarily focuses on computer technology and its applications. Her expertise in multimedia, digital content, and green computing has led to significant contributions in these fields. She has been actively involved in curriculum design, project consultancy, and professional development training, particularly in the areas of multimedia and STEM. Lili's dedication to green computing is evident through her certifications and her role in the Malaysian Communications and Multimedia Commission's Green IT initiatives.

IMPACT AND INFLUENCE

Lili's work has had a profound impact on both academic and professional communities. She has been recognized with numerous awards, including the Lifetime Achievement Award from the International Scientist Awards on Engineering, Science, and Medicine in 2022, and the Outstanding Educator Award from Lattice Science Publication in 2021. Her contributions to computer technology and green computing have influenced policy making, curriculum development, and environmental sustainability in IT practices.

ACADEMIC CITES

Lili's scholarly work is highly regarded, with numerous citations reflecting her influence in the academic community. Her research has been widely published and cited, contributing significantly to the fields of computer technology, green computing, and multimedia applications. She has also served as a peer reviewer and editorial board member for several esteemed journals and conferences, further establishing her reputation as a leading expert in her field.

LEGACY AND FUTURE CONTRIBUTIONS

Lili Nurliyana Abdullah's legacy lies in her pioneering contributions to computer technology and green computing. Her work has laid the foundation for future research and development in sustainable IT practices and multimedia technology. As she continues to innovate and collaborate, Lili's future contributions are expected to further advance these fields, fostering a more sustainable and technologically advanced society.

COMPUTER TECHNOLOGY

Throughout her career, Lili Nurliyana Abdullah has focused on advancing computer technology through her research, teaching, and professional endeavors. Her work on digital content and multimedia applications has enhanced the educational landscape, while her commitment to green computing has promoted sustainable IT practices. Lili's dedication to computer technology is reflected in her extensive professional engagements, certifications, and contributions to policy making and curriculum development in the field. As a recognized leader in computer technology, she continues to inspire and influence future generations of researchers and practitioners.

NOTABLE PUBLICATION

Students’ satisfaction levels of an immersive extended reality for engine assembly tasks in engineering empirical education 2023

Deep learning mango fruits recognition based on tensorflow lite 2023

Playing Gamelan Bonang in the Air: User Requirements for Designing a Digital Musical Instrument for the Malay Bonang 2022 (3)

Comparison of Edge Detection Algorithms for Texture Analysis on Copy-Move Forgery Detection Images 2022 (2)

GoMap: Combining step counting technique with augmented reality for a mobile-based indoor map locator 2023

Chang Su – Computer application – Best Researcher Award

Published on 04/05/2024 by Civil Engineering

Chang Su - Computer application - Best Researcher Award

Ocean University of China - China

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Chang Su's academic journey began at the Department of Information Science and Engineering at Ocean University of China. He showed promise from an early age, demonstrating a keen interest in computer applications. His pursuit of knowledge in this field laid the foundation for his future endeavors in academia and professional practice.

PROFESSIONAL ENDEAVORS

In his professional journey, Chang Su has showcased significant expertise in computer applications. His involvement in the National Key R&D Program of China, collaborating with South China Aero Engine Factory 331, exemplifies his commitment to advancing intelligent manufacturing technologies. This experience has not only enriched his skill set but has also provided valuable insights into real-world applications of computer science.

CONTRIBUTIONS AND RESEARCH FOCUS

Chang Su's research focus lies in intelligent manufacturing, a critical area within computer applications. His contributions to the National Key R&D Program of China, particularly in the manufacturing of aircraft engine casings and blades, highlight his dedication to advancing the field. His research endeavors aim to leverage computer applications to enhance efficiency and innovation in manufacturing processes.

IMPACT AND INFLUENCE

Chang Su's participation in conferences like the IEICE conference and the HCII 2020 underscores his growing influence in the academic community. By publishing manuscripts in reputable venues, he has contributed to the dissemination of knowledge and fostered collaboration among researchers in the field of computer applications.

ACADEMIC CITES

Chang Su's research publications and contributions to prestigious conferences have garnered academic attention and citations. His work serves as a testament to his expertise and scholarly contributions in the domain of computer applications, further solidifying his reputation as a promising researcher in the field.

LEGACY AND FUTURE CONTRIBUTIONS

As Chang Su continues his journey toward obtaining a Ph.D. in Computer Applications, his legacy lies in his dedication to advancing intelligent manufacturing technologies. Through his research, he aims to make significant contributions to the field, shaping the future of computer applications and its impact on various industries. His work will pave the way for continued innovation and progress in the realm of intelligent manufacturing.

NOTABLE PUBLICATION

Zinc-mineralized diatom biosilica/hydroxybutyl chitosan composite hydrogel for diabetic chronic wound healing 2024 (1)

The hierarchical porous structures of diatom biosilica-based hemostat: From selective adsorption to rapid hemostasis 2023 (7)

Diatom-Inspired Bionic Hydrophilic Polysaccharide Adhesive for Rapid Sealing Hemostasis 2023 (4)

PEG-mediated hybrid hemostatic gauze with in-situ growth and tightly-bound mesoporous silicon 2022 (4)

Jamin Rahman Jim – Generative AI – Young Scientist Award

Published on 02/05/2024 by Civil Engineering

Jamin Rahman Jim - Generative AI - Young Scientist Award

Advanced Machine Intelligence Research Lab - Bangladesh

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Jamin Rahman Jim's academic journey commenced with a Bachelor of Science degree in Computer Science and Engineering, with a major in Information Systems, from the American International University-Bangladesh. His exceptional academic performance, evidenced by a final grade of 3.96/4.00, was complemented by a thesis focusing on assessing Personalized Federated Learning Algorithms for Pattern Recognition Tasks.

PROFESSIONAL ENDEAVORS

Jamin Rahman Jim has established himself as a dedicated researcher in the field of artificial intelligence and machine learning. His roles as a Research Assistant at Deepchain Labs and subsequently as a Researcher at the Advanced Machine Intelligence Research Lab (AMIR Lab) reflect his commitment to advancing knowledge and contributing to cutting-edge research projects.

CONTRIBUTIONS AND RESEARCH FOCUS

With a focus on artificial intelligence and machine learning, Jamin Rahman Jim has made significant contributions to the field through his publications and projects. His research spans various domains, including the trustworthy metaverse, NLP-based sentiment analysis, deep learning for medical image segmentation, and user authentication and authorization in cybersecurity. Through preprints and published articles, he continues to explore innovative approaches and address challenges in the application of machine learning techniques.

IMPACT AND INFLUENCE

Jamin Rahman Jim's research has garnered attention within the academic community and beyond, as evidenced by his publications in reputable journals and his receipt of prestigious awards and grants. His work on generative AI in medical imaging, fusion-enhanced terrain detection, and explainable AI approaches has the potential to influence the development of AI systems in various domains, including healthcare, autonomous vehicles, and cybersecurity.

ACADEMIC CITES

Jamin Rahman Jim's publications in journals such as IEEE Access, Natural Language Processing Journal, and Computers and Electrical Engineering have been cited by fellow researchers, indicating the relevance and impact of his work. His research on generative AI in medical imaging, personalized federated learning algorithms, and lightweight human activity recognition frameworks has contributed to advancing knowledge in the field of artificial intelligence.

LEGACY AND FUTURE CONTRIBUTIONS

As Jamin Rahman Jim continues his academic and professional journey, his legacy lies in his dedication to advancing the field of artificial intelligence and machine learning. Through his ongoing research projects, publications, and collaborations, he aims to address critical challenges and contribute to the development of innovative AI solutions. His focus on generative AI in medical imaging underscores his commitment to leveraging AI for improved healthcare outcomes and societal impact.

NOTABLE PUBLICATION

Generative Adversarial Networks (GANs) in Medical Imaging: Advancements, Applications and Challenges 2024

Toward Trustworthy Metaverse: Advancements and Challenges 2023 (4)

Dajian Zhong – Scene Text Recognition – Best Researcher Award

Published on 26/04/2024 by Civil Engineering

Dajian Zhong - Scene Text Recognition - Best Researcher Award

Shanghai Maritime University - China

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Dr. Dajian Zhong's academic journey commenced with a strong foundation in Computer Science and Technology, beginning with a Bachelor's degree from Suzhou University of Science and Technology. He furthered his studies with a Master's degree from East China University of Science and Technology, specializing in Computer Science and Technology. Dr. Zhong's academic pursuits culminated in a Ph.D. in Computer Application Technology from East China Normal University. Throughout his educational journey, he exhibited a keen interest in advancing the field of computer vision, particularly in the domain of scene text recognition.

PROFESSIONAL ENDEAVORS

Dr. Zhong currently serves as a Lecturer in the College of Information Engineering at Shanghai Maritime University, where he imparts knowledge and expertise to aspiring students. His professional career is characterized by a commitment to excellence in research and education, with a focus on computer vision, text detection, and recognition. Through his role as a lecturer, Dr. Zhong continues to inspire and mentor the next generation of computer scientists and engineers.

CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Zhong's research is centered around the advancement of scene text recognition, a critical area within computer vision. His work explores novel algorithms and techniques to improve the accuracy and efficiency of text detection and recognition in complex scenes. By leveraging approaches such as semantic GANs, attention networks, and transformer networks, Dr. Zhong aims to address the challenges associated with arbitrarily oriented and shaped text in real-world environments. His contributions have been published in reputable journals and presented at international conferences, demonstrating his expertise and impact in the field.

IMPACT AND INFLUENCE

Dr. Zhong's research has made a significant impact on the field of scene text recognition, garnering recognition from peers and researchers worldwide. His innovative algorithms and methodologies have advanced the state-of-the-art in text detection and recognition, facilitating applications in various domains, including document analysis, image understanding, and augmented reality. Through his collaborative efforts and interdisciplinary approach, Dr. Zhong continues to shape the future of computer vision and inspire advancements in intelligent systems and technologies.

ACADEMIC CITES

Dr. Zhong's publications have received significant citations from researchers and practitioners in the field of computer vision, attesting to the relevance and impact of his work. His research findings have been instrumental in advancing the understanding and capabilities of scene text recognition systems, contributing to the development of more accurate and robust algorithms for real-world applications. Dr. Zhong's influence extends beyond academia, as his work continues to shape the landscape of computer vision research and technology.

LEGACY AND FUTURE CONTRIBUTIONS

As Dr. Zhong continues to pursue his research endeavors, his focus remains on pushing the boundaries of scene text recognition and computer vision. Through ongoing collaborations, mentorship, and knowledge dissemination, he seeks to further advance the field and foster innovations that benefit society at large. Dr. Zhong's legacy lies in his dedication to excellence, his passion for advancing knowledge, and his commitment to addressing real-world challenges through cutting-edge research in scene text recognition.

NOTABLE PUBLICATION

LRATNet: Local-Relationship-Aware Transformer Network for Table Structure Recognition 2024

NDOrder: Exploring a novel decoding order for scene text recognition 2024

Salim Chehida – Smart grid security – Best Researcher Award

Published on 28/03/202428/03/2024 by Civil Engineering

Salim Chehida - Smart grid security - Best Researcher Award

VERIMAG - Université Grenoble alpes - France

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Salim Chehida's academic journey commenced with an Engineer Degree in Computer Science from the University of Mostaganem, Algeria. He furthered his studies with a Magister Degree in Information Systems Engineering and eventually pursued a Ph.D. in Computer Science specializing in Software Engineering and Systems Security from the University of Oran 1 in Algeria in collaboration with the University of Grenoble Alpes in France.

PROFESSIONAL ENDEAVORS

Dr. Salim Chehida has had a diverse professional career, starting as a Software Engineer at the Finance Direction in Algeria and later transitioning to roles as a Scientific Researcher and Assistant Professor at the University of Mostaganem, Algeria. Currently, he serves as a Research and Development Expert at the University of Grenoble Alpes in France, contributing significantly to the fields of Software Engineering and Deep Learning.

CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Chehida's expertise lies in Software Engineering, particularly in the design, development, security, verification, and validation of software systems. He has made notable contributions to various innovative projects, including those related to cyber-physical systems (CPS) and Internet of Things (IoT) systems. His research focuses on deep learning applications, including image classification, segmentation, and object detection, as well as smart grid security.

IMPACT AND INFLUENCE

Dr. Chehida's research and development work have had a significant impact on academia and industry, particularly in the domains of software engineering and deep learning. His involvement in numerous projects, collaborations with companies and institutions worldwide, and contributions to conferences and publications have established him as a respected expert in his field.

ACADEMIC CITES

Dr. Chehida's publications and technical reports have been widely cited, reflecting the importance and relevance of his research contributions. His work in smart grid security and deep learning applications has garnered attention from researchers and professionals in academia, industry, and government organizations.

LEGACY AND FUTURE CONTRIBUTIONS

As Dr. Chehida continues to advance his research and development endeavors, his legacy in the fields of software engineering and deep learning is assured. His future contributions are expected to further enhance our understanding and application of smart grid security measures and deep learning techniques, addressing critical challenges in cybersecurity and artificial intelligence for years to come.

NOTABLE PUBLICATION

Model-based Self-adaptive Management in a Smart Grid Substation 2023 (2)

Generation and verification of learned stochastic automata using k-NN and statistical model checking 2022 (1)

Learning and analysis of sensors behavior in IoT systems using statistical model checking 2022 (5)

BRAIN-IoT Architecture and Platform for Building IoT Systems 2022 (2)

Micheal Sakr – Structural Health Monitoring – Best Researcher Award

Published on 14/03/2024 by Civil Engineering

Micheal Sakr - Structural Health Monitoring - Best Researcher Award

Western University of Ontario - Canada

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Micheal Sakr commenced his academic journey with a Bachelor of Science in Civil Engineering from the University of Balamand, Lebanon, where he achieved outstanding academic performance, earning a cumulative average of 90.06% and graduating with distinction. He further enriched his academic background with graduate coursework in Structural Engineering at the University of Western Ontario, Canada, where he is currently pursuing a Ph.D. under the supervision of Dr. Ayan Sadhu. His research focus revolves around Digital Twins for Structural Health Monitoring, showcasing his commitment to advancing the field of structural engineering.

PROFESSIONAL ENDEAVORS

Throughout his academic career, Micheal has demonstrated versatility and excellence, serving as a Teaching Assistant at Western University, where he contributed to courses such as Engineering Statics, Advanced Structural Dynamics, and Professional Communication for Engineers. Additionally, his experience as an AutoCAD Drafter equipped him with practical skills in handling structural detailing and drawings for civil engineering projects.

CONTRIBUTIONS AND RESEARCH FOCUS

Micheal's research interests center on Structural Health Monitoring, a field critical for ensuring the safety and integrity of civil infrastructure. His work involves utilizing specialized equipment for structural testing, such as displacement sensors, accelerometers, and acoustic emission sensors, to assess the strength and response of various structural elements. By actively participating in research projects and mentoring initiatives, Micheal demonstrates his dedication to advancing knowledge and addressing real-world engineering challenges.

IMPACT AND INFLUENCE

Micheal's contributions to the field of Structural Health Monitoring have the potential to make a significant impact on civil engineering practices, particularly in ensuring the safety and resilience of infrastructure systems. His involvement in community aid groups and volunteer activities further underscores his commitment to making a positive difference in society.

ACADEMIC CITES

Micheal's academic achievements, including his outstanding performance in coursework and research, have positioned him as a promising scholar in the field of structural engineering. His contributions to research projects and mentorship activities reflect his dedication to academic excellence and professional development.

LEGACY AND FUTURE CONTRIBUTIONS

As Micheal continues to pursue his Ph.D. and engage in research endeavors, he is poised to leave a lasting legacy in the field of Structural Health Monitoring. His passion for innovation, coupled with his strong academic foundation and practical skills, sets the stage for future contributions that will advance the safety, sustainability, and resilience of civil infrastructure worldwide.

NOTABLE PUBLICATION

Sareer Ul Amin – Computer Science and Engineering – Excellence in Research

Published on 14/03/202414/03/2024 by Civil Engineering

Sareer Ul Amin - Computer Science and Engineering - Excellence in Research

Chung Ang University - South Korea

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Sareer Ul Amin embarked on his academic journey at Islamia College Peshawar (ICP), Pakistan, where he pursued a Bachelor of Science in Computer Science, graduating with distinction. His academic excellence continued as he pursued a Master's degree at Chung-Ang University (CAU) in Seoul, Republic of Korea, achieving an outstanding CGPA of 4.18/4.5.

PROFESSIONAL ENDEAVORS

Sareer Ul Amin's professional journey is marked by significant contributions to the field of Computer Science and Engineering. He served as a Research Assistant at the Graphics Realization Lab, CAU, contributing to various industrial and research projects. Prior to this, he held the role of Lab Coordinator at the Digital Image Processing Lab, ICP, where he effectively managed projects and mentored students.

CONTRIBUTIONS AND RESEARCH FOCUS

Sareer Ul Amin's research focus lies in AI & Computer Vision, with a specialization in Advanced Machine Learning, Deep Learning, and Anomaly Detection in Surveillance Video. His research contributions include the development of efficient strategies for anomaly detection, active learning techniques for data annotation, and robust hand gesture recognition systems. His work has been published in esteemed journals and conferences, showcasing his expertise in the field.

IMPACT AND INFLUENCE

Sareer Ul Amin's research findings have had a significant impact on the field of Computer Science and Engineering, particularly in the areas of anomaly detection, image analysis, and machine learning. His publications have garnered citations and recognition, highlighting the relevance and influence of his research contributions in academia and industry.

ACADEMIC CITES

Sareer Ul Amin's research publications have been well-received in the academic community, with his work cited in reputable journals and conferences. His contributions to the development of efficient deep learning models and active learning techniques have advanced the state-of-the-art in computer vision and machine learning.

LEGACY AND FUTURE CONTRIBUTIONS

Sareer Ul Amin's legacy in the field of Computer Science and Engineering is characterized by his dedication to research excellence and innovation. His future contributions are poised to further advance the frontier of AI and Computer Vision, with a focus on addressing complex challenges and developing practical solutions for real-world applications.

NOTABLE PUBLICATION

An Efficient and Robust Hand Gesture Recognition System of Sign Language Employing Finetuned Inception-V3 and Efficientnet-B0 Network. 2023 (6)