Prof. Dr. Otilia Manta | Artificial Intelligence | Innovative Research Award

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Prof. Dr. Otilia Manta | Artificial Intelligence | Innovative Research Award

Professor PhD, Romanian Academy, Romania

Prof. Dr. habil. Elena Otilia Manta  is a renowned economist, academic, and scientific researcher, currently serving as a Professor at the Romanian-American University and a Scientific Researcher at the Romanian Academy. With over two decades of experience in economic sciences, she is widely respected for her expertise in finance, FinTech, AI integration, and sustainable development. She also holds various leadership roles in international organizations, including Vice President of EUExperts in Brussels, reflecting her strong influence in policy and academic circles globally. 🌍💼

Publication Profile

🎓 Education Background

Prof. Manta holds a Ph.D. in Economics and the academic title of “habilitation,” enabling her to supervise doctoral research. Her education has been complemented by continuous development in areas like finance, international economic relations, and technological integration, laying a solid academic foundation for her contributions in both national and international academic communities. 🎓📖

💼 Professional Experience

Since 2014, Prof. Manta has been a Scientific Researcher at the Romanian Academy and since 2019, a full Professor at the Romanian-American University in Bucharest. She also serves as Vice President of the European Union Experts (EUExperts) and the International Research Institute for Economics and Management (IRIEM), among others. As founder and CEO of The Romanian Group for Investments and Consultancy (RGIC), she combines academic depth with real-world financial leadership. She has also served as an EU Expert and Rapporteur with the European Commission. 🌐🏛️📊

🏆 Awards and Honors

Prof. Manta has received numerous honors, including the “2006 Woman of the Year Commemorative Medal” by the American Biographical Institute. She is a respected honorary member of the Romanian-Italian Chamber of Commerce and holds various affiliations with prestigious academic, financial, and developmental organizations such as the UN HLPF Mechanism and the Financial Stability Oversight Council (NY). 🥇🎖️🌟

🔬 Research Focus

Her research focuses on FinTech, artificial intelligence integration in banking, sustainable economic development, academic transparency, and financial innovation. As an active participant in multidisciplinary fields, Prof. Manta is a frequent contributor to leading journals and conferences, continuously shaping discussions on the future of finance and digital transformation. 💡📈🤖

🔗 Publications – Top Notes

Banking Transformation Through FinTech and the Integration of Artificial Intelligence in Payments – FinTech, 2025 | DOI: 10.3390/fintech4020013 – A highly impactful paper exploring AI’s role in revolutionizing payment systems.

FinTech and AI as Opportunities for a Sustainable Economy – FinTech, 2025 | DOI: 10.3390/fintech4020010 – Widely cited for linking technology to green and inclusive finance.

The Transfer of Managerial Expertise in Romanian Companies through the Application of the DEMATEL Method – Journal for Future Society and Education, 2025 – Emphasizes decision science in corporate governance.

Ensuring Academic Integrity: Tools and Mechanisms for a Transparent Educational Environment – Preprints, 2025 – Focuses on digital tools fostering academic ethics.

🔚 Conclusion

Prof. Dr. habil. Otilia Manta is a distinguished leader, bridging the worlds of academia, finance, and international consultancy. Her career reflects a strong commitment to innovation, transparency, and global collaboration in economics. Through her scholarly research, institutional leadership, and consultancy, she continues to inspire future generations in both Romania and abroad. 🌟📘🌍

Prof. Dr. YiSheng Huang | Computer Science | Best Researcher Award

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Prof. Dr. YiSheng Huang | Computer Science | Best Researcher Award

Professor, National Ilan University/EE, Taiwan

Dr. Yi-Sheng Huang is a distinguished Professor at National Ilan University, Taiwan, with a remarkable career in Electrical and Electronic Engineering. Holding a Ph.D. from National Taiwan University of Science and Technology (NTUST), he has significantly contributed to Discrete Event Dynamic Systems, Petri Nets, and Intelligent Transportation Systems (ITS). Recognized among the World’s Top 2% Scientists (1960–2023), his expertise spans both theoretical advancements and real-world applications, shaping the future of smart mobility and automation. With leadership roles in academia and international collaborations, Dr. Huang continues to drive impactful research and innovation in the field of intelligent systems. 🚀

Publication Profile

📚 Academic Background

Dr. Yi-Sheng Huang earned his Ph.D. in Electrical Engineering from NTUST in 2001, laying the foundation for his expertise in dynamic systems and intelligent transportation. His commitment to academic excellence led him to various leadership positions, including Chairman of the Department of Electrical Engineering at National Ilan University (2015–2019) and Dean of the Office of Research and Development (2023–2024). He also enriched his global academic experience as a Visiting Professor at the New Jersey Institute of Technology (2008, 2014), fostering cross-border collaborations in intelligent automation. 🎓

🏢 Professional Experience

With over two decades of academic and research contributions, Dr. Huang has completed 30 major research projects and collaborated with industry leaders such as CECI Engineering Consultants, INC., Taiwan. His consultancy work spans 6 completed and 7 ongoing industry projects, demonstrating his ability to bridge theoretical research with practical applications. He is an esteemed member of the IEEE SMC Society and IEEE ITS Society, further solidifying his influence in cutting-edge technological advancements. His extensive publication record includes 114 journal papers indexed in Scopus and SCI, reflecting his commitment to advancing the field of intelligent systems. ⚡

🏆 Awards and Honors

Dr. Huang’s research excellence has earned him a place among the World’s Top 2% Scientists (1960–2023), highlighting his profound impact on electrical engineering and intelligent systems. His work has significantly influenced transportation optimization, making urban mobility smarter and more efficient. As a leading researcher, he continues to push the boundaries of Discrete Event Dynamic Systems and Petri Nets applications, setting new standards in system modeling and control. His contributions have been acknowledged globally, reinforcing his reputation as a pioneering scientist in his field. 🏅

🔬 Research Focus

Dr. Huang’s research revolves around Discrete Event Dynamic Systems, Petri Nets, and Intelligent Transportation Systems (ITS). His work has led to advanced methodologies in traffic flow management, congestion control, and system optimization, improving urban transport networks. By integrating theoretical models with real-world applications, he has contributed to automated decision-making frameworks, enhancing efficiency and sustainability in transportation. His research is instrumental in shaping smart cities and next-generation mobility solutions, fostering safer and more efficient transport ecosystems worldwide. 🚦

🔍 Conclusion

Dr. Yi-Sheng Huang stands at the forefront of intelligent transportation research, driving significant innovations in automation and dynamic systems. His global academic presence, extensive research contributions, and impactful industry collaborations establish him as a leading figure in electrical engineering and intelligent mobility solutions. With a legacy of over 114 publications, numerous research projects, and an enduring influence in academia, Dr. Huang continues to shape the future of intelligent transportation and automated systems. 🌍🚀

📝 Top Publications

A Petri net-based model for real-time traffic control in urban networks.

Optimization of discrete event systems using hybrid Petri nets.

Modeling and performance analysis of ITS using dynamic Petri nets.

Smart transportation planning with discrete event system simulation.

Enhancing automated transport systems using intelligent Petri nets.

 

Ching-Lung Fan | Deep Learning | Best Researcher Award

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Assoc. Prof. Dr. Ching-Lung Fan | Deep Learning | Best Researcher Award

Associate Professor, ROC Military Academy, Taiwan

Ching-Lung Fan is an associate professor in Civil Engineering at the Republic of China Military Academy. He completed his Ph.D. in 2019 from the National Kaohsiung University of Science and Technology. His professional journey reflects a strong dedication to advancing technology in the construction and civil engineering sectors, particularly through the application of machine learning and deep learning methods. 🏫

Publication Profile

Education

Dr. Fan holds a Master of Science (M.S.) from National Taiwan University (2006) and a Ph.D. from National Kaohsiung University of Science and Technology (2019). His academic background underscores his commitment to both theoretical and practical contributions to the field. 🎓

Experience

Dr. Fan started his academic career as an assistant professor at the Republic of China Military Academy in January 2019 and was promoted to associate professor in June 2022. His teaching and research experience has significantly impacted the study of civil engineering, especially through the integration of machine learning and data mining. 🏢

Awards and Honors

Ching-Lung Fan has received several prestigious awards, including the Phi Tau Phi Scholastic Honor (2019), Outstanding Paper Award (2021), Excellent Paper Award (2022), and Best Researcher Award (2024). In 2023, he was honored with membership in Sigma Xi, an esteemed scientific organization. 🏅

Research Focus

Dr. Fan’s research interests are primarily centered around machine learning, deep learning, data mining, construction performance evaluation, and risk management. His work integrates cutting-edge computational methods with civil engineering applications to enhance the quality and efficiency of construction projects. 🤖📊

Conclusion

Dr. Fan’s innovative contributions to civil engineering, particularly in the realm of AI-driven solutions, continue to shape the future of construction and infrastructure development. His ongoing research and recognition in the academic community highlight his expertise and impact in the field. 🌟

Publications

 Integrating image processing technology and deep learning to identify crops in UAV orthoimages. CMC-Computers, Materials & Continua. (Accepted).

Predicting the construction quality of projects by using hybrid soft computing techniques. CMES-Computer Modeling in Engineering & Sciences. (Accepted).

 Evaluation model for crack detection with deep learning—Improved confusion matrix based on linear features. Journal of Construction Engineering and Management (ASCE), 151(3): 04024210. (SCI).

 Evaluating the performance of Taiwan airport renovation projects: An application of multiple attributes intelligent decision analysis. Buildings, 14(10): 3314. (SCI).

Deep neural networks for automated damage classification in image-based visual data of reinforced concrete structures. Heliyon, 10(19): e38104. (SCI).

Multiscale feature extraction by using convolutional neural network: Extraction of objects from multiresolution images of urban areas. ISPRS International Journal of GeoInformation, 13(1): 5. (SCI).

Ground surface structure classification using UAV remote sensing images and machine learning algorithms. Applied Geomatics, 15: 919-931. (ESCI).

 Using convolutional neural networks to identify illegal roofs from unmanned aerial vehicle images. Architectural Engineering and Design Management, 20(2): 390-410. (SCI).

Evaluation of machine learning in recognizing images of reinforced concrete damage. Multimedia Tools and Applications, 82: 30221-30246. (SCI).

 Supervised machine learning–Based detection of concrete efflorescence. Symmetry, 14(11): 284. (SCI).

 

Prabakaran Raghavendran | Artificial Neural Network | Young Scientist Award

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Mr. Prabakaran Raghavendran | Artificial Neural Network | Young Scientist Award

Research Scholar, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology (Deemed to be University), India

Prabakaran Raghavendran is a dynamic researcher and Ph.D. candidate at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, specializing in Fractional Differential Equations, Integral Transforms, Functional Differential Equations, and Control Theory. With a strong academic foundation in Mathematics, he earned an M.Sc. in Mathematics with an impressive CGPA of 9.79 from the same institution in 2022. He is currently pursuing his Ph.D., contributing significantly to the field with several research publications, patents, and international conference presentations. 🌟

Publication Profile

Education:

Prabakaran completed his B.Sc. in Mathematics at Loyola College, Chennai, in 2020 with a CGPA of 9.25. He further advanced his academic career by obtaining an M.Sc. in Mathematics from Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology in 2022, where he excelled with a CGPA of 9.79. Currently, he is pursuing his Ph.D. at the same institution, expected to complete in 202X. 🎓📚

Experience:

Prabakaran has been actively engaged in the research and development of advanced mathematical models and algorithms. His experience spans across fractional differential equations, fuzzy analysis, cryptography, and artificial neural networks. Additionally, he has contributed to the development of innovative technologies, holding multiple patents in signal analysis, optimization, and medical applications. His work is widely recognized in the academic and research communities. 💼🔬

Awards and Honors:

Prabakaran’s academic excellence and dedication to research have earned him several prestigious awards, including the Best Paper Presentation Award for his work on Fractional Integro Differential Equations at the 7th International Conference on Mathematical Modelling, Applied Analysis, and Computation (ICMMAAC-24) in Beirut, Lebanon. He is also a life member of both the International Association of Engineers (IAENG) and the International Organization for Academic and Scientific Development (IOASD). 🏅🌍

Research Focus:

Prabakaran’s research focuses on Fractional Differential Equations, Integral Transforms, and Control Theory, with particular attention to their applications in various fields such as cryptography, artificial neural networks, and fuzzy analysis. He has developed new methodologies for solving complex mathematical models and is deeply involved in finding practical solutions for issues such as Parkinson’s disease prognosis, noise reduction in signals, and optimization in robotics. 🔍🔢

Conclusion:

Prabakaran Raghavendran is a passionate and dedicated researcher in the field of Mathematics, with a strong focus on fractional differential equations and control theory. His groundbreaking work in both theoretical and applied mathematics has earned him recognition through publications and patents. With his ongoing research contributions, he continues to push the boundaries of mathematical modeling and its applications in real-world problems. 🌐💡

Publications:

A Study on the Existence, Uniqueness, and Stability of Fractional Neutral Volterra-Fredholm Integro-Differential Equations with State-Dependent Delay. Fractal Fractional, 9 (1), 1-23. (2024) (SCIE-WoS & Scopus) (Q1).

Analytical Study of Existence, Uniqueness, and Stability in Impulsive Neutral Fractional Volterra-Fredholm Equations.  Journal of Mathematics and Computer Science, 38 (3), 313-329. (2024) (WoS & Scopus) (Q1).

Application of Artificial Neural Networks for Existence and Controllability in Impulsive Fractional Volterra-Fredholm Integro-Differential Equations. Applied Mathematics in Science and Engineering, 32 (1), 1-21. (2024) (SCIE-WoS-Scopus).

Existence and Controllability for Second-Order Functional Differential Equations With Infinite Delay and Random Effects.  International Journal of Differential Equations, 5541644, 2024, 1-9. (2024) (WoS & Scopus).

Solving the Chemical Reaction Models with the Upadhyaya Transform. Orient J Chem, 2024; 40(3). (WoS) (WoS).

Sara Tehsin | Deep learning | Best Researcher Award

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Ms. Sara Tehsin | Deep learning | Best Researcher Award

PhD Student, National University of Sciences and Technology, Islamabad, Pakistan

Sara Tehsin is a motivated and results-driven professional with over ten years of experience in Image Processing and Machine Learning. As an Engineering Lecturer at HITEC University in Taxila, Pakistan, she excels in delivering high-quality educational experiences and has a proven track record of producing outstanding results through her strong work ethic, adaptability, and effective communication skills. She is passionate about academic development and seeks opportunities to contribute her expertise while furthering her professional growth. 📚💻

Publication Profile

Google Scholar

Education

Sara Tehsin is currently pursuing a PhD in Computer Engineering at the National University of Sciences and Technology (NUST), Islamabad, where she has achieved a remarkable GPA of 3.83/4.00. Her research focuses on Digital Forensics, Deep Learning, and Digital Image Processing. She holds a Master’s degree in Computer Engineering from NUST, where she graduated with a GPA of 3.7/4.0, and a Bachelor’s degree from The Islamia University of Bahawalpur, with a GPA of 3.36/4.00. 🎓🌟

Experience

Sara has extensive teaching experience, currently serving as an Engineering Lecturer at HITEC University since September 2019, where she develops engaging curriculum and delivers lectures aligned with international standards. Previously, she was a Computer Science Lecturer at Sharif College of Engineering and Technology, and she also served as a Teaching Assistant at NUST and a Lab Engineer at Foundation University. Her roles have encompassed curriculum development, practical instruction, and student support in various computer science subjects. 👩‍🏫🔧

Research Interests

Sara’s research interests encompass Digital Forensics, Deep Learning, Digital Image Processing, and Machine Learning. She focuses on developing innovative solutions for image recognition and forgery detection, contributing significantly to the fields of computer vision and machine learning. Her work aims to enhance the accuracy and efficiency of image processing systems. 🧠🔍

Publications

Self-organizing hierarchical particle swarm optimization of correlation filters for object recognition
S. Tehsin, S. Rehman, M.O.B. Saeed, F. Riaz, A. Hassan, M. Abbas, R. Young, …
IEEE Access, 5, 24495-24502 (2017)
Cited by: 21

Improved maximum average correlation height filter with adaptive log base selection for object recognition
S. Tehsin, S. Rehman, A.B. Awan, Q. Chaudry, M. Abbas, R. Young, A. Asif
Optical Pattern Recognition XXVII, 9845, 29-41 (2016)
Cited by: 18

Fully invariant wavelet enhanced minimum average correlation energy filter for object recognition in cluttered and occluded environments
S. Tehsin, S. Rehman, F. Riaz, O. Saeed, A. Hassan, M. Khan, M.S. Alam
Pattern Recognition and Tracking XXVIII, 10203, 28-39 (2017)
Cited by: 12

Comparative analysis of zero aliasing logarithmic mapped optimal trade-off correlation filter
S. Tehsin, S. Rehman, A. Bilal, Q. Chaudry, O. Saeed, M. Abbas, R. Young
Pattern Recognition and Tracking XXVIII, 10203, 22-37 (2017)
Cited by: N/A