Khaled Elsayed – Innovation in Data Analysis – Best Researcher Award 

Mr. Khaled Elsayed - Innovation in Data Analysis - Best Researcher Award 

Universiti Kebangsaan Malaysia - Malaysia

Author Profile

Early Academic Pursuits

Mr. Khaled Elsayed's journey in civil engineering began with a strong academic foundation. Graduating with a Bachelor of Engineering (BEng) in Civil Engineering from Sohar University, his academic pursuits laid the groundwork for his future professional endeavors. During his undergraduate years, Elsayed demonstrated a keen interest in structural analysis, laying the groundwork for his later specialization in this field. His academic achievements during this period reflect his dedication to mastering the fundamentals of civil engineering, providing him with a solid framework for his future research and professional contributions.

Professional Endeavors

Following his undergraduate studies, Elsayed embarked on a path of professional development, gaining practical experience in the field of civil engineering. His tenure as an Associate Design Engineer at Al-Fajer Engineering Consultants in Al-Suwayq, Oman, provided him with invaluable experience in designing and analyzing structural components for various civil engineering projects. During this time, he honed his skills in project management and client collaboration, achieving a remarkable 95% client satisfaction rate through meticulous attention to detail and adherence to project requirements.

Subsequently, Elsayed transitioned to a role as a Construction Engineer at Axes International Trade & Contract in Al-Suwayq, Oman, where he further refined his project management expertise. Managing multiple construction projects with unwavering commitment to quality and efficiency, he successfully led cross-functional teams and implemented innovative methodologies that resulted in significant cost reductions and productivity improvements.

Contributions and Research Focus

Mr. Elsayed's passion for advancing construction methods and optimizing performance led him to pursue higher education, culminating in a Master of Engineering (MEng) and a Doctor of Philosophy (PhD) in Civil Engineering from The National University of Malaysia. During his graduate studies, he focused his research on the development of Prefabricated Prefinished Volumetric Construction (PPVC) modular steel constructions. His contributions in this area include the development of innovative inter-module connections, which not only improved construction efficiency by 30% but also resulted in a substantial reduction in costs. Furthermore, his research endeavors have been recognized through the publication of four high-impact papers in reputable journals, underscoring his commitment to advancing knowledge in his field.

Accolades and Recognition

Throughout his career, Elsayed's contributions have been met with recognition and accolades. His adept project management skills and dedication to excellence have earned him a reputation for delivering projects with 100% adherence to specifications and quality standards, garnering a commendable 95% client satisfaction rate. Moreover, his innovative solutions and research findings have been acknowledged through various awards and honors, highlighting his significant contributions to the field of civil engineering.

Impact and Influence

Mr. Elsayed's impact extends beyond individual projects and research endeavors, influencing the broader landscape of civil engineering through his commitment to excellence and innovation. By implementing efficient construction methodologies and pioneering advancements in PPVC modular steel constructions, he has set a precedent for sustainable and cost-effective construction practices. His research findings have not only contributed to academic discourse but also have practical implications for the construction industry, driving advancements in structural analysis and construction technology.

Legacy and Future Contributions

As Khaled Elsayed continues to make strides in the field of civil engineering, his legacy is characterized by a commitment to excellence, innovation, and continuous learning. With a solid foundation in both academia and industry, he is poised to further his contributions through ongoing research, collaborative endeavors, and mentorship of future generations of civil engineers. By leveraging his expertise in structural analysis, modular construction, and machine learning, he seeks to address pressing challenges in the field and drive engineering advancements that will shape the future of construction.

Notable Publication

Hugo Hervé-Côte – Machine Learning and AI Applications – Best Researcher Award 

Mr. Hugo Hervé-Côte - Machine Learning and AI Applications - Best Researcher Award 

Ecole de Technologie Supérieure - Canada 

Author Profile

Early Academic Pursuits

Mr. Hugo Hervé-Côté embarked on his academic journey with a strong foundation in mechanical and industrial engineering. He began his education at the prestigious Ecole Nationale Supérieure des Arts et Métiers (ENSAM) in Angers, France, where he pursued a Diploma in Mechanical, Industrial, and Energy Engineering. During his time at ENSAM, from September 2019 to July 2021, Hugo honed his expertise in various engineering disciplines, setting the stage for his future endeavors in artificial intelligence and machine learning.

Following his graduation from ENSAM, Hugo continued to build on his technical knowledge and skills by pursuing a Master's degree in Automated Production Engineering (M.Sc.A) at the Ecole de Technologie Supérieure (ETS) in Montreal, Canada. From September 2021 to December 2023, he delved deeper into advanced engineering concepts and specialized in machine learning and computer vision. This dual-degree experience equipped him with a robust academic background and practical skills, making him a versatile engineer ready to tackle complex challenges in the industry.

Professional Endeavors

Mr. Hugo's professional journey has been marked by significant contributions to the fields of non-destructive testing (NDT) and industrial inspection. His career began with a notable role as an Artificial Intelligence Engineer at EddyFi Technologies in Quebec, Canada, from December 2023 to March 2024. In this position, Hugo focused on the development and implementation of machine learning models for analyzing eddy current images in non-destructive testing. He was instrumental in creating a user-friendly interface for visualizing and labeling complex magnetic data, and he developed a comprehensive data pipeline for training, validating, and testing machine learning models. His work culminated in a proof of concept that demonstrated the effectiveness of these models in real-world applications.

Prior to his role at EddyFi Technologies, Hugo gained valuable experience as a Student Researcher in Ultrasonic Inspection using Machine Learning at ETS and in collaboration with Nucleom. From September 2021 to December 2023, he worked on detecting defects in ultrasonic images, developing a standardized database for ultrasonic imaging, and addressing industrial challenges through regular project progress meetings with Nucleom and EddyFi. His efforts contributed to the advancement of ultrasonic inspection techniques and the integration of machine learning in this domain.

Contributions and Research Focus

Mr. Hugo's research focus has been centered on the application of machine learning and artificial intelligence in non-destructive testing and industrial inspection. His master's thesis involved the development of a tool for analyzing ultrasonic images using machine learning. This project, conducted from September 2021 to December 2023, included the acquisition of defect data from welds using Full Matrix Capture (FMC) and the development of algorithms for image reconstruction and defect detection. Hugo also created a significant labeled database of over 100,000 images, which served as a foundation for training deep learning models. His work was presented at conferences such as OnDuty in Windsor, ON (2022) and Toronto, ON (2023), and was published in the scientific journal Ultrasonics.

Hugo's research contributions extend to developing post-processors for CNC machines and designing cryogenic tool mounts. His projects have involved the practical application of engineering principles to solve real-world problems, demonstrating his ability to bridge the gap between theory and practice.

Accolades and Recognition

Mr. Hugo Hervé-Côté's work has been recognized both academically and professionally. His publication in Ultrasonics, titled "Automatic flaw detection in sectoral scans using machine learning," has garnered attention in the scientific community, showcasing his expertise in applying advanced technologies to improve industrial inspection processes. This publication is a testament to his dedication to research and innovation in the field of non-destructive testing.

Throughout his academic and professional career, Hugo has demonstrated excellence in his field, earning the respect of his peers and supervisors. His involvement in various projects and his ability to present his findings at conferences highlight his commitment to advancing knowledge and contributing to the engineering community.

Impact and Influence

Mr. Hugo's work has had a significant impact on the field of non-destructive testing and industrial inspection. By integrating machine learning techniques into traditional inspection methods, he has contributed to the development of more accurate and efficient defect detection processes. His research on ultrasonic imaging and eddy current testing has the potential to revolutionize how industries approach quality control and maintenance, leading to safer and more reliable infrastructure.

Hugo's contributions have also influenced the development of standardized databases and formats for storing and analyzing inspection data, facilitating collaboration and knowledge sharing among researchers and industry professionals. His efforts to create user-friendly interfaces and data pipelines have made advanced technologies more accessible to engineers and technicians, promoting the adoption of machine learning in industrial applications.

Legacy and Future Contributions

Mr. Hugo Hervé-Côté's legacy lies in his innovative approach to solving complex engineering problems through the application of machine learning and artificial intelligence. His work has paved the way for future advancements in non-destructive testing and industrial inspection, setting a high standard for integrating cutting-edge technologies into practical applications.

Looking ahead, Hugo's future contributions are likely to continue shaping the field of engineering. His strong foundation in mechanical and industrial engineering, combined with his expertise in artificial intelligence, positions him as a leader in the development of next-generation inspection techniques. As industries increasingly rely on data-driven solutions, Hugo's work will remain at the forefront of technological innovation, driving progress and improving safety and efficiency across various sectors.

Notable Publication

Ch Rajyalakshmi | Deep learning using medical image data | Best Researcher Award

Mrs Ch Rajyalakshmi - B V Raju Institute of Technology - Deep learning using medical image data

Mrs Ch Rajyalakshmi : Deep learning using medical image data

Professional profile:

Early Academic Pursuits:

Mrs. Ch. Rajyalakshmi's academic journey commenced with a Bachelor's degree in Computer Science and Information Technology from NEC, Narsaraopeta, in 2004. This laid the foundation for her pursuit of a Master's degree in Computer Science and Engineering at AVIET, Narsipatnam, in 2011. Building on her academic prowess, she is currently pursuing a Ph.D. at JNTU Kakinada, with her thesis focusing on "HIGH SPECTRAL SATELLITE IMAGE SEGMENTATION WITH DEEP LEARNING UNET BASED TECHNIQUES FOR GENERATING FLOOD INUNDATION."

Professional Endeavors:

With a teaching experience spanning 18 years, Dr. Rajyalakshmi has played pivotal roles in various academic institutions. She has been an Associate Professor at BVRIT, Narsapur, since 2011, following roles as an Assistant Professor at CMRIT Engg College, Hyderabad, and a Lecturer at Narsaraopeta Engineering College, Narsaraopeta, earlier in her career.

Contributions and Teaching Experience:

Mrs. Rajyalakshmi's expertise in computer science is evident through the diverse range of courses she has taught. From Artificial Intelligence and Machine Learning to Database Design and Operating Systems, she has contributed significantly to the education of students. Her teaching extends to areas such as Computer Networks, Software Engineering, Multimedia and Design, and Human-Computer Interaction.

Research Focus and Publications:

Mrs. Rajyalakshmi's research interests primarily revolve around the application of Deep Learning architectures for spatial data, particularly in processing high spectral satellite images for water body identification. Her publications in renowned journals and conferences reflect the depth of her contributions to the field. Some notable publications include works on satellite image data extraction using classification techniques and the detection of active attacks in Mobile Ad Hoc Networks (MANETs).

Accolades and Recognition:

Mrs. Rajyalakshmi's academic achievements include being FET Qualified in 2011 and GATE Qualified in 2006. Her commitment to excellence is also evident in her completion of various NPTEL courses and Coursera certifications, covering topics such as Machine Learning, Database Management Systems, Deep Learning, and Artificial Intelligence.

Impact and Influence:

Through her research and teaching endeavors, Mrs. Rajyalakshmi has made a significant impact on the academic community. Her publications and patents attest to her dedication to advancing knowledge in computer science and related domains.

Legacy and Future Contributions:

As a seasoned educator and researcher, Mrs. Rajyalakshmi continues to shape the academic landscape. Her administrative responsibilities, including course coordination, involvement in accreditation processes, and leadership roles in various committees, showcase her commitment to the holistic development of educational institutions. With an ongoing Ph.D. pursuit and an impressive list of publications and patents, she is poised to leave a lasting legacy in the realms of computer science, education, and research. Her multifaceted contributions highlight a career marked by continuous growth, learning, and impactful contributions to academia.

Notable Publications: