Iyad Alomar | Aerospace Engineering | Aerospace Engineering Award

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Prof. Iyad Alomar | Aerospace Engineering | Aerospace Engineering Award

Aviation Engineering Program director, Transport and Telecommunication Institute, Latvia.

Dr. Iyad Alomar is a Syrian-born aerospace engineer and academic based in Riga, Latvia. He holds a Ph.D. in Engineering Sciences from the Transport and Telecommunication Institute (TTI), Riga, and an MSc in Aircraft Technical Maintenance from Riga Aviation University. Dr. Alomar has contributed significantly to the field of aviation engineering through his extensive research and publications. He is a member of the editorial board for the journal Aviation and serves on the scientific committee for the 13th International Conference on Transportation Science and Technology (TRANSBALTICA 2022). His work focuses on optimizing aircraft maintenance processes, enhancing operational efficiency, and integrating digital technologies in aviation. Dr. Alomar is also an active member of the International Advisory Board for the ICAA’21 conference on aeronautics and astronautics.

Profiles

🎓 Education

Dr. Iyad Alomar’s academic journey is marked by a strong foundation in aerospace engineering. He completed his Master of Science in Aircraft Technical Maintenance at Riga Aviation University in 1996. Building upon this, he pursued advanced studies at the Transport and Telecommunication Institute in Riga, where he earned his Doctor of Science in Engineering (Dr.Sc.Eng) in 2019. His doctoral research focused on optimizing aircraft maintenance processes and integrating digital technologies to enhance operational efficiency in the aviation industry. Throughout his academic career, Dr. Alomar has been committed to advancing knowledge in aerospace engineering, contributing to various international conferences and journals. His educational background has equipped him with the expertise to address complex challenges in aviation maintenance and operations.

💼 Experience

Dr. Iyad Alomar has a distinguished career in aerospace engineering, combining academic research with practical applications in the aviation industry. He is currently a faculty member at the Transport and Telecommunication Institute in Riga, Latvia, where he teaches and conducts research in aviation engineering. In addition to his academic role, Dr. Alomar serves on the editorial board of the journal Aviation and is a member of the scientific committee for the 13th International Conference on Transportation Science and Technology (TRANSBALTICA 2022). He is also an active member of the International Advisory Board for the ICAA’21 conference on aeronautics and astronautics. Dr. Alomar’s professional activities reflect his dedication to advancing the field of aerospace engineering through collaboration, research, and education.

🔬 Research Focus

Dr. Iyad Alomar’s research focuses on optimizing aircraft maintenance processes, enhancing operational efficiency, and integrating digital technologies in aviation. His work aims to reduce aircraft downtime and improve the overall performance of airline operations. Notable publications include studies on the optimization of aircraft on-ground (AOG) processes and the integration of artificial intelligence in airline operation control centers. Dr. Alomar has also contributed to research on fatigue management methodologies for flight crews and the impact of unpredictable major events on the aviation industry. His interdisciplinary approach combines engineering principles with digital technologies to address complex challenges in the aviation sector. Through his research, Dr. Alomar seeks to contribute to the development of more efficient and resilient aviation systems.

📚Publication Top Notes

  1. “Improvement of Fatigue Management Methodology Related to Flight Crew”
    Published: September 20, 2024, in Aviation
    DOI: 10.3846/aviation.2024.22146
    Summary: This study explores methodologies to enhance fatigue management among flight crews, aiming to improve their well-being and overall aviation safety.

  2. “Investigation of Performance Improvement of Gas Turbine Engine by Optimized Design of Blade Turbine Cooling Channels”
    Published: 2024
    Summary: This doctoral research focuses on optimizing the design of cooling channels within turbine blades to improve the performance of gas turbine engines.

  3. “Modelling and Simulation of the Riga International Airport to Reduce Turnaround Times of Crucial Clearance Processes”
    Published: January 24, 2018, in Reliability and Statistics in Transportation and Communication
    DOI: 10.1007/978-3-319-74454-4_51
    Summary: This paper presents a simulation model aimed at reducing turnaround times for critical clearance processes at Riga International Airport.

  4. “Analysis of Riga International Airport Flight Delays”
    Published: January 24, 2018, in Reliability and Statistics in Transportation and Communication
    DOI: 10.1007/978-3-319-74454-4_50
    Summary: This study analyzes flight delays at Riga International Airport, identifying factors contributing to delays and suggesting improvements.

  5. “Simulation of Ground Vehicles Movement on the Aerodrome”
    Published: 2017, in Procedia Engineering
    DOI: 10.1016/j.proeng.2017.01.061
    Summary: This paper develops a simulation model to study the movement of ground vehicles on aerodromes, aiming to improve operational efficiency.

  6. “Vibroacoustic Soundproofing for Helicopter Interior”
    Published: 2023, in Aviation
    Summary: This study investigates methods for reducing vibratory and acoustic noise in helicopter interiors to enhance passenger comfort.

  7. “Comparative Statistical Analysis of Airport Flight Delays for the Period 2019–2020. Almaty International Airport Case Study”
    Published: 2022
    Summary: This research analyzes flight delays at Almaty International Airport, identifying contributing factors and proposing strategies to minimize delays.

Conclusion

Iyad Alomar presents a solid background in aviation and aerospace through education, international academic involvement, and advisory roles. These are valuable indicators of expertise and standing in the field. However, to be a strong contender for a Research in Aerospace Engineering Award, more emphasis should be placed

Kai Zhang | Mechanical Engineering | Best Researcher Award

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Assoc. Prof. Dr. Kai Zhang | Mechanical Engineering | Best Researcher Award

Associate Professor, Shenyang University of Chemical Technology, China

ZHANG Kai is an accomplished Associate Professor at Shenyang University of Chemical Technology, specializing in artificial intelligence algorithms, robotics, and mechanical system optimization. With a doctoral degree in mechanical engineering, he has made significant contributions to intelligent fault diagnosis, machine vision, and the reliability of rotating machinery. Over the past five years, he has authored more than 30 academic papers, including 9 SCI-indexed and 11 EI-indexed articles, with 7 appearing in top-tier JCR Q1 journals. Dr. Zhang has led a sub-project under China’s National Key R&D Program and participated in several National Natural Science Foundation initiatives. His innovative research in adaptive optimization algorithms has also resulted in four patents. Committed to academic excellence and engineering innovation, Dr. Zhang continues to mentor students and lead pioneering research that bridges AI and mechanical design. His work enhances predictive maintenance, system reliability, and intelligent manufacturing technologies.

Profile

Scopus

Education 

ZHANG Kai earned his Doctorate in Mechanical Engineering, focusing on intelligent systems and optimization algorithms. His academic foundation is grounded in multidisciplinary studies that bridge traditional mechanical principles with cutting-edge computer science, especially in artificial intelligence and robotics. During his postgraduate years, he explored complex optimization problems, laying the groundwork for future research in algorithm development and machine learning applications in mechanical systems. His doctoral thesis was recognized for its innovation in adaptive optimization strategies for mechanism design. Dr. Zhang’s education equipped him with both theoretical acumen and practical engineering problem-solving skills, which he has since applied across a range of high-impact projects in academia and applied research. His passion for teaching and mentoring has also led to the development of curricula that integrate AI tools into traditional mechanical engineering coursework.

Experience 

Currently serving as Associate Professor at the Shenyang University of Chemical Technology, ZHANG Kai has over a decade of experience in academia and research. He has led and participated in multiple national-level projects, including a key sub-project under the National Key Research and Development Program. Over the past five years, he has published more than 30 peer-reviewed papers, many of which have been recognized in prestigious SCI and EI journals. He specializes in intelligent fault diagnosis for rotating machinery, differential evolution algorithms, and machine vision systems. His engineering expertise extends to vibration analysis and online health monitoring technologies. Dr. Zhang is also a key contributor to various academic initiatives aimed at improving the integration of AI within traditional mechanical systems. He is deeply involved in supervising graduate students and promoting interdisciplinary research within his department.

Research Focus

ZHANG Kai’s research lies at the intersection of mechanical engineering and artificial intelligence. His primary interests include the development of adaptive evolutionary algorithms, fault diagnosis techniques for rotating machinery, and intelligent machine vision systems. He applies AI-based solutions such as particle swarm optimization and differential evolution to solve multi-constraint mechanical design problems. His studies have enhanced the accuracy and efficiency of vibration monitoring, online health diagnostics, and fault tolerance systems in industrial equipment. With a growing emphasis on smart manufacturing, Dr. Zhang aims to bridge theoretical algorithm development with real-world mechanical applications. His research has far-reaching implications in industrial automation, robotics, and mechanical system reliability. He also works on improving the robustness and flexibility of mechanical optimization through novel algorithmic approaches. As industries increasingly seek to implement predictive maintenance and automation, his research offers critical tools and strategies for system sustainability and innovation.

Publication Top Notes

  1. Zhang K, Yang M, Zhang Y, et al.
    Title: Error feedback method (EFM) based dimension synthesis optimisation for four-bar linkage mechanism
    Journal: Applied Soft Computing, 2023: 110424
    Summary: Introduced an innovative error feedback method to enhance dimension synthesis in mechanical linkages, improving mechanical efficiency through intelligent correction algorithms.

  2. Kai Zhang, Eryu Zhu, et al.
    Title: A multi-fault diagnosis method for rolling bearings
    Journal: Signal, Image and Video Processing, 2024, 18: 8413-8426
    Summary: Developed a multi-fault detection model using signal processing and AI classification to improve maintenance systems in rotating equipment.

  3. Kai Zhang, Jiahao Zhu, Yimin Zhang, Qiujun Huang
    Title: Optimization method for linear constraint problems
    Journal: Journal of Computational Science, 2021, 51: 101315
    Summary: Proposed a new optimization framework for solving mechanical design issues with linear constraints using a hybrid computational approach.

Conclusion:

Associate Professor ZHANG Kai’s academic output, innovative methodologies, and active leadership in key research initiatives position him as a highly deserving candidate for the Best Researcher Award. His contributions significantly advance knowledge in AI-based mechanical systems and engineering reliability. Recognizing his work through this award would not only honor his individual achievements but also encourage further interdisciplinary research within his field.

István Gaál | Number Theory | Best Researcher Award

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Prof. István Gaál | Number Theory | Best Researcher Award

Professor, University of Debrecen, Hungary

Prof. Dr. István Gaál, born on December 17, 1960, in Debrecen, Hungary, is a distinguished mathematician at the Institute of Mathematics, University of Debrecen. With over 30 years in academia, he has contributed significantly to number theory and algebra, focusing on Diophantine equations and algebraic number fields. He completed his studies at Kossuth Lajos University, Debrecen, before obtaining his PhD and later his Doctorate of Academy. Prof. Gaál has received numerous accolades for his work, including being a Fellow of the Alexander von Humboldt Foundation. His academic leadership and contributions to mathematical research have established him as a prominent figure in Hungary and internationally.

Profile

Orcid

Education

Prof. Dr. István Gaál began his academic journey at Kossuth Lajos University, Debrecen, where he studied Mathematics from 1979 to 1984. He earned a University Doctorate in December 1987, with his thesis on “Inhomogeneous decomposable form equations and their applications.” He continued his academic progression by earning a PhD in June 1990, focusing on “Decomposable polynomial equations and their applications.” In 1995, he obtained his PhD degree, followed by his habilitation in 1998. His scholarly pursuits culminated in a Doctor of Academy degree in 2003, for his thesis on “Constructive methods for solving Diophantine equations.”

Experience

Prof. Gaál’s career spans several decades, during which he has held notable academic and administrative positions. He served as an Assistant Professor at Kossuth Lajos University from 1987 to 1990 and was promoted to Associate Professor in 1993. He became a full Professor at the University of Debrecen in 2004. His leadership roles include Vice Director at the Institute of Mathematics and Informatics (1993-1999), Vice Dean of the Faculty of Natural Sciences (1999-2004), and Vice Rector of the University of Debrecen (2014-2015). He also served as Head of the Department of Algebra and Number Theory from 2005 to 2016. Prof. Gaál has been an editor and reviewer for major mathematical journals, including Zentralblatt für Mathematik and Mathematical Reviews, while managing several prominent research projects.

Awards and Honors

Prof. Dr. István Gaál has been honored with several prestigious awards throughout his career. He received the Kató Rényi Memory Prize (1984) for outstanding mathematical research and the Géza Grünwald Memory Prize (1988) for his contributions to number theory. In 1992, he shared the Academy Prize, reflecting his profound impact on Hungarian mathematics. Additionally, Prof. Gaál earned the Széchenyi Professor Scholarship (1998-2001) and served as a Fellow of the Alexander von Humboldt Foundation in 1991-1993. In 2020, he was awarded the Prize for Teacher Training by the University of Debrecen, recognizing his excellence in educating future generations. He also received the Brassai Sámuel Art Prize in 2020 for his overall contribution to the arts and sciences.

Research Focus

Prof. Dr. István Gaál’s research focuses primarily on number theory, with an emphasis on Diophantine equations and the monogenity of number fields. He has contributed significantly to understanding power integral bases and the algebraic structures within number theory. His work on decomposable polynomial equations and inhomogeneous decomposable form equations has advanced the field by providing new methods for solving complex equations. Additionally, his research has explored the monogenity of quartic number fields, particularly the relations within pure quartic relative extensions. Prof. Gaál’s extensive publications include influential journal articles and books that continue to shape mathematical research in these areas. His expertise in constructive methods for solving Diophantine equations is well recognized within the global academic community.

Publication Top Notes

  • On the Monogenity of Quartic Number Fields Defined by x4ax2b++ (2025) 📝
  • Monogenity and Power Integral Bases: Recent Developments (2024) 🔎
  • On the Monogenity of Pure Quartic Relative Extensions of $\mathbb{Q}(i)$ (2023) 🔢

 

Haydar ARAS | Energy Optimization | Excellence Award (Any Scientific field)

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Prof. Dr. Haydar ARAS | Energy Optimization | Excellence Award (Any Scientific field)

Prof.Dr., Eskişehir Osmangazi University, Turkey

Prof. Haydar Aras is a distinguished academic and researcher in the field of Mechanical Engineering, currently serving as a Professor at Eskisehir Osmangazi University, Turkey. He holds multiple research IDs, including ORCID (0000-0001-8131-6426) and ScopusID (6603029093). With over three decades of experience, his research interests span various aspects of energy systems, thermodynamics, and sustainable energy technologies. Prof. Aras has been actively involved in both academic and administrative roles, including as the Head of the Department of Mechanical Engineering and a member of the Senate at Eskisehir Osmangazi University. His work in energy optimization and thermodynamic analysis has earned him global recognition, reflected in the numerous citations of his publications. His contributions continue to impact the development of innovative energy systems for sustainable practices.

Profile

Education

Prof. Haydar Aras completed his education at Anadolu University and Eskisehir Osmangazi University. He earned his doctorate degree in Mechanical Engineering from Eskisehir Osmangazi University in 1996. Prior to that, he obtained his postgraduate degree in Mechanical Engineering from Anadolu University in 1991. His academic journey began with an undergraduate degree in Mechanical Engineering from Anadolu University’s Faculty of Engineering and Architecture, which he completed in 1989. His scholarly foundation in mechanical engineering has provided him with a deep understanding of energy systems, thermodynamics, and mechanical design, which he continues to develop and apply in his ongoing research. His dissertation work focused on natural gas combustion systems and heat recovery, a subject that marked the beginning of his long-standing interest in energy efficiency and optimization.

Experience

Prof. Haydar Aras has extensive experience in both academia and administration at Eskisehir Osmangazi University, where he has worked since 1997. Currently, he holds the position of Professor in the Department of Mechanical Engineering, part of the Faculty of Engineering and Architecture. He has previously served as an Associate Professor (2006-2012) and Assistant Professor (1997-2006). Prof. Aras has held leadership roles as the Head of the Department of Mechanical Engineering from 2023 to present and from 2024 to the present, guiding academic programs and strategic developments. He has also served as a Director of the Research Center within the university and participated in the university Senate. His comprehensive teaching experience includes courses in heat transfer, thermodynamics, and energy systems, reflecting his expertise in energy efficiency and sustainable technologies. Throughout his career, Prof. Aras has consistently contributed to the advancement of engineering knowledge and energy optimization.

Research Focus

Prof. Haydar Aras’s research primarily revolves around energy systems, energy optimization, thermodynamics, and sustainable technologies. His research interests include energy efficiency, thermodynamic analysis, and the application of exergy and exergoeconomics in various energy systems, such as combined heat and power (CHP) systems, trigeneration systems, and natural gas applications. Prof. Aras has significantly contributed to the evaluation and optimization of energy systems for residential, industrial, and power generation purposes. His work also focuses on the utilization of alternative fuels and renewable energy sources, including solar and wind energy. In addition, his studies on heat recovery and insulation technologies have provided insights into reducing energy consumption and improving environmental sustainability. Prof. Aras’s research is recognized internationally, with numerous publications and citations that contribute to the global discourse on sustainable energy technologies.

Publication Top Notes

  • Multi-criteria selection for a wind observation station location using analytic hierarchy process 🌬️
  • Determination of optimum insulation thicknesses for Turkey’s different degree-day regions 🏠
  • Evaluation of alternative fuels for residential heating in Turkey using analytic network process 🔋
  • Exergoeconomic analysis of a combined heat and power (CHP) system 💡
  • Forecasting residential natural gas demand 🌍
  • Thermodynamic and thermoeconomic analyses of a trigeneration (TRIGEN) system with a gas-diesel engine 🔥
  • Estimating the horizontal diffuse solar radiation over the Central Anatolia Region of Turkey 🌞
  • Exergetic performance evaluation of a combined heat and power (CHP) system in Turkey 🌱
  • Advanced exergy analysis of an electricity-generating facility using natural gas ⚡
  • Wind energy status and its assessment in Turkey 🌪️

 

 

Armughan Ali | Engineering | Best Researcher Award

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Mr. Armughan Ali | Engineering | Best Researcher Award

Lab Demonstrator, Wah Engineering College, Pakistan

Armughan Ali is a driven and innovative software engineer with a deep focus on artificial intelligence (AI) and its applications in solving real-world challenges. With expertise spanning software development, machine learning (ML), deep learning (DL), and natural language processing (NLP), he specializes in building intelligent systems that enhance efficiency and improve user experiences. Armughan thrives in collaborative environments, leveraging his knowledge of software engineering to create impactful AI-driven solutions. His passion for technology drives him to contribute to cutting-edge projects, making meaningful contributions to the future of AI. He is a published researcher and actively works to bridge the gap between AI theory and practice.

Profile

Google Scholar

Education

Armughan Ali is currently pursuing a Bachelor of Science in Software Engineering at HITEC University, Taxila, Pakistan (2020–2024), where he has excelled in both academic and practical aspects of software engineering. His foundation in engineering principles, coupled with a strong interest in artificial intelligence, positions him as a rising star in the field. Prior to this, Armughan completed his FSC (Pre-Engineering) from Punjab College, Wah-Cantt (2017–2019), where he honed his analytical skills and gained a solid grounding in the sciences. His academic journey has been marked by a commitment to excellence and a passion for emerging technologies, with a focus on AI, machine learning, and software development.

Experience

Armughan Ali’s professional journey includes diverse roles that showcase his versatility and expertise. As a Lab Demonstrator at Wah Engineering College (2024–present), he imparts knowledge to students and fosters a collaborative learning environment. He also serves as a Web Developer on Fiverr (2020–present), where he customizes and develops responsive websites for clients. In his previous role as a Graphic Designer at Graphic Saloon (2023–2024), he created on-brand visuals and marketing materials. Additionally, he contributed to digital solutions as a Digital Solutions Specialist at Ever-Green Corporation (2023), focusing on enhancing the company’s digital presence. He also conducted Front-End Development workshops at HITEC University in 2023, training participants on web technologies like HTML, CSS, and JavaScript. These varied experiences underscore his technical, teaching, and leadership capabilities.

Awards and Honors

Armughan Ali has received numerous accolades, affirming his talent and leadership in the tech community. He is the founder and organizer of the prestigious “CodeWar” event at HITEC University, which has become a significant programming competition. His leadership and dedication have been recognized across multiple seasons, including CodeWar Season I, II, and III (2022-2024). In addition to his role as an organizer, Armughan’s talent in math and programming has earned him awards such as the Math Genius and Speed Programming titles at TECTIQS’ 19 and 18 (IQRA University). These honors highlight his exceptional problem-solving skills and contributions to academic and extracurricular activities. His achievements reflect his commitment to advancing his skills and fostering a culture of innovation.

Certifications

Armughan Ali has demonstrated a strong commitment to expanding his technical knowledge through numerous certifications in the fields of software engineering, artificial intelligence, and machine learning. Notable certifications include IBM Full Stack Software Developer (2024), Machine Learning (2024), and Google Advanced Data Analytics (2024). Additionally, he has completed training in AI/ML, .NET FullStack Development, and deep learning, further honing his skills in these advanced domains. His continuous learning approach also led him to certifications in cybersecurity, project management, and various front-end technologies. These certifications attest to his technical proficiency and eagerness to stay ahead of industry trends. Armughan’s focus on continuous education empowers him to tackle complex challenges with confidence and agility.

Research Focus

Armughan Ali’s research interests lie at the intersection of artificial intelligence, machine learning, and healthcare. His work focuses on applying AI to solve complex real-world problems, particularly in disease detection and classification. He has co-authored several research papers on topics such as Alzheimer’s disease prediction, fake news classification, and skin cancer detection using deep learning techniques. His recent research involves the use of vision transformers for medical imaging, including cancer detection and stomach gastric detection. Armughan is also exploring the use of ensemble learning models for improving the accuracy of AI systems in real-world applications. His contributions to AI-driven healthcare research aim to advance the potential of technology in improving patient outcomes. With a deep interest in creating explainable AI models, Armughan strives to enhance transparency in AI decision-making processes.

Publication Top Notes

  1. X-News Dataset for Online News Categorization 📊
  2. xCViT: An Improved Vision Transformer Network for Skin Disease Classification 🧑‍⚕️
  3. An Optimized Weighted Voting-Based Ensemble Learning Approach for Fake News Classification 📰
  4. Enhancing Disability-Inclusive Communication Through DynaFuseNet and Transformer Models for Sign Language Interpretation 🦻
  5. Convolutional Transformer-Based Few-Shot Learning for Stomach Gastric Detection 🍽️
  6. Alzheimer’s Disease Prediction at Early Stage Using Vision Transformer Architecture 🧠
  7. An Efficient Approach for Plant Leaf Disease Detection Using Vision Transformer Architecture 🌿