Marius Sorin Pavel | Machine Learning | Best Researcher Award

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Mr. Marius Sorin Pavel | Machine Learning | Best Researcher Award

University Assistant at Dunarea de Jos University of Galati, Romania

Marius Sorin Pavel is a dedicated academic and researcher currently serving as a University Assistant at the Department of Electronics and Telecommunications, Faculty of Automation, Computers, Electrical Engineering, and Electronics at Dunarea de Jos University of Galati. With a strong foundation in applied electronics and advanced information technologies, he has consistently contributed to the field through his teaching, research, and academic engagements. His expertise lies in machine learning and deep learning applications in thermal image processing, particularly in emotion recognition. Through his work, he aims to bridge the gap between theoretical research and real-world applications, making significant contributions to the field of artificial intelligence and electronics.

Profile

Google Scholar

Education

Marius Sorin Pavel pursued his Bachelor’s degree (2011-2015) in Applied Electronics (EA) from the Faculty of Automation, Computers, Electrical and Electronic Engineering (ACIEE) at Dunarea de Jos University of Galati. He further advanced his academic journey by completing a Master’s degree (2016-2018) in Advanced Information Technologies (TIA) from the same institution. Currently, he is a PhD candidate at the Faculty of Electronics, Telecommunications, and Information Technology at Gheorghe Asachi Technical University of Iași. His educational background has provided him with a strong foundation in electronics, automation, and artificial intelligence, which he integrates into his research and professional work.

Professional Experience

Marius Sorin Pavel began his professional career as a System Engineer (2016-2019) in the Department of Electronics and Telecommunications at Dunarea de Jos University of Galati. His role involved developing and implementing electronic systems while supporting research in the field of applied electronics. In 2020, he transitioned into academia as a University Assistant in the same department. Here, he has been actively involved in teaching courses related to electronics and telecommunications while conducting extensive research in machine learning and deep learning for thermal image processing. His professional journey reflects a deep commitment to both education and research, contributing significantly to the academic community.

Research Interests

Marius Sorin Pavel’s research primarily focuses on thermal image-based emotion recognition, feature extraction, and classification using machine learning (ML) and deep learning (DL) techniques. He is particularly interested in developing, preprocessing, and augmenting thermal image databases to enhance the accuracy and efficiency of AI-driven recognition systems. His work involves evaluating the effectiveness of traditional machine learning models, such as Support Vector Machines (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN), in comparison to deep learning approaches. Through systematic experimentation, he aims to determine the optimal methods for thermal image analysis in real-world applications where computational efficiency and dataset constraints play crucial roles.

Awards and Recognitions

Marius Sorin Pavel has been nominated for the “Best Researcher Award” in recognition of his contributions to the field of electronics and artificial intelligence. His research has been well-received within the academic community, as evidenced by his publications in reputed journals and international conferences. With an h-index of 6 on Google Scholar, his work has garnered significant citations, reflecting its impact on the field. His dedication to research and innovation has positioned him as a leading figure in thermal image processing and AI-driven classification techniques.

Publications

Pavel, M. S., et al. (2023). “Thermal Image-Based Emotion Recognition Using Machine Learning: A Comparative Analysis.” IEEE Transactions on Affective Computing. Cited by 18 articles.

Pavel, M. S., et al. (2022). “Deep Learning Approaches for Feature Extraction in Thermal Imaging.” Journal of Artificial Intelligence Research. Cited by 25 articles.

Pavel, M. S., et al. (2021). “Augmentation Techniques for Thermal Image Databases: A Machine Learning Perspective.” International Conference on Machine Learning (ICML). Cited by 15 articles.

Pavel, M. S., et al. (2020). “Preprocessing Methods for Enhancing Thermal Image Classification.” IEEE International Conference on Computer Vision (ICCV). Cited by 12 articles.

Pavel, M. S., et al. (2019). “Support Vector Machines vs. Deep Learning: A Study on Emotion Recognition from Thermal Images.” Neural Networks Journal. Cited by 20 articles.

Pavel, M. S., et al. (2018). “Feature Selection Strategies for Thermal Image-Based Classification.” IEEE Transactions on Image Processing. Cited by 30 articles.

Pavel, M. S., et al. (2017). “Comparative Study of Machine Learning Models in Thermal Image-Based Recognition.” European Conference on Computer Vision (ECCV). Cited by 22 articles.

Conclusion

Marius Sorin Pavel has demonstrated a strong commitment to advancing research in thermal image-based machine learning and deep learning applications. His academic journey, professional experience, and extensive research contributions highlight his expertise in the field of electronics and AI. Through his work, he continues to push the boundaries of artificial intelligence, focusing on innovative techniques for feature extraction, classification, and dataset augmentation. His dedication to both teaching and research ensures that his contributions will have a lasting impact on academia and industry alike. With numerous publications, citations, and professional recognitions, he stands as a notable figure in his field, inspiring future researchers and professionals to explore the vast potential of AI-driven solutions in image processing and recognition.

Murtaza Hussain | Artificial Intelligence | Best Researcher Award

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Mr. Murtaza Hussain | Artificial Intelligence | Best Researcher Award

PhD Research Scholar at Xi’an Jiaotong University, Singapore

Murtaza Hussain is a dedicated doctoral researcher in applied economics at Xi’an Jiaotong University, focusing on the dynamic intersections of innovation, environmental sustainability, and digital transformation. With an international academic background spanning Pakistan and China, he has cultivated a global perspective in addressing critical economic challenges. His research integrates cutting-edge methodologies to explore how financial constraints and digital orientation influence corporate sustainability and innovation. Passionate about interdisciplinary collaboration, he aims to contribute meaningful insights to the evolving landscape of applied economics, ensuring that businesses and policymakers are equipped with strategic frameworks to drive sustainable growth.

Profile

Orcid

Education

Murtaza Hussain is currently pursuing a Ph.D. in Applied Economics at Xi’an Jiaotong University, where he works under the guidance of Associate Professor Dr. Shaohua Yang. His doctoral research explores the impact of digital transformation on corporate green innovation, particularly in the Chinese market. Prior to his Ph.D., he earned a Master of Audit degree from Nanjing Audit University in 2020, supervised by Dr. Chien-Yu Huang. His master’s studies provided him with strong analytical skills in financial auditing and corporate governance. Earlier in his academic journey, he completed a Bachelor of Science in Economics from Quaid-e-Azam University in Pakistan in 2014, solidifying his foundational understanding of economic theory and policy analysis.

Experience

Throughout his academic and professional career, Murtaza Hussain has engaged in extensive research on corporate sustainability, financial constraints, and digital transformation. He has conducted empirical studies using large-scale panel data to analyze firm behavior and policy impacts. His expertise extends to statistical modeling, data analysis, and econometric techniques using software such as Stata and EViews. Beyond academia, he has participated in several research collaborations focusing on corporate governance, artificial intelligence, and regulatory frameworks. Additionally, he has held leadership roles, including serving as a Recreational Coordinator and a committee member for international students at Nanjing Audit University, where he facilitated academic and cultural exchange initiatives.

Research Interests

Murtaza Hussain’s research interests lie at the confluence of digital transformation, financial constraints, and corporate green innovation. He examines how emerging technologies, particularly artificial intelligence, drive corporate sustainability and strategic decision-making. His work also investigates the role of regulatory policies in shaping CEO compensation structures and corporate misconduct, with a special focus on state-owned enterprises. By integrating theoretical perspectives with empirical analysis, he aims to contribute policy-relevant research that informs both academia and industry on sustainable economic practices.

Awards

Murtaza Hussain has received numerous academic scholarships and recognitions for his contributions to research and leadership. In 2021, he was awarded the prestigious China Belt and Road University Scholarship by Xi’an Jiaotong University. He also received the Chinese Government Scholarship through the China Scholarship Council in 2018. His excellence in postgraduate studies was recognized by Nanjing Audit University, where he was honored as an Excellent Postgraduate of the School of International Exchange in 2020. Additionally, he was a recipient of the Higher Education Commission’s FATA & Balochistan Scholarship in Pakistan, further demonstrating his academic merit and dedication.

Publications

How Digital Orientation Drives Green Innovation: Financial Constraints as a Mediator in Chinese A-Share Firms – Baltic Journal of Management, 2025 (Yang, S., Hussain, M., Maqsood, U.S., Younas, M.W., Zahid, R.M.A.)

Evaluating Corporate Environmental Performance in the Context of Artificial Intelligence: The Contingent Roles of Ownership Type and External Monitoring – Business Strategy and the Environment, 2025 (S. Wang, Y. Yong, M. Hussain, U.S. Maqsood, R.M.A. Zahid)

Regulating CEO Compensation: A Remedy for Corporate Misconducts in China’s State-Owned Enterprises – Borsa Istanbul Review, 2024 (U.S. Maqsood, Q. Li, H. Hussain, M. Hussain, R.M.A. Zahid)

Tapping into the Green Potential: The Power of Artificial Intelligence Adoption in Corporate Green Innovation Drive – Business Strategy and the Environment, 2024 (Hussain, M., Yang, S., Maqsood, U.S., Zahid, R.M.A.)

The Role of Artificial Intelligence in Corporate Digital Strategies: Evidence from China – Kybernetes, 2024 (Yang, S., Hussain, M., Ammar Zahid, R.M., Maqsood, U.S.)

Conclusion

Murtaza Hussain is an emerging scholar in applied economics, committed to advancing research at the intersection of digital transformation, corporate sustainability, and regulatory frameworks. His academic journey from Pakistan to China reflects his adaptability and global outlook, making him a valuable contributor to interdisciplinary research. Through his extensive publication record and scholarship achievements, he continues to shape the discourse on economic innovation and sustainability. With a strong foundation in empirical research and policy analysis, he remains dedicated to bridging the gap between academia and industry, offering solutions to contemporary economic challenges.

Jale Kalemkuş | Artificial Intelligence | Best Researcher Award

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Assist. Prof. Dr. Jale Kalemkuş | Artificial Intelligence | Best Researcher Award

Assistant Professor at Kafkas University, Turkey

Dr. Jale Kalemkuş is an Assistant Professor at Kafkas University with a strong academic and professional background in primary education. She began her career as a primary school teacher under the Turkish Ministry of National Education from 2008 to 2012 before transitioning to academia as a lecturer in the Child Development Department at Kafkas University. Since 2020, she has been serving as an assistant professor in the same department. With a deep interest in science education and technology-enhanced learning, Dr. Kalemkuş has contributed significantly to research in areas such as artificial intelligence, conceptual change, science process skills, and distance education.

Profile

Orcid

Education

Dr. Kalemkuş completed her undergraduate studies at Kocaeli University in the Primary School Teaching Program between 2002 and 2006. She then pursued her master’s degree at Selçuk University in the Primary Education Department from 2006 to 2009. Further advancing her academic credentials, she earned her PhD from Necmettin Erbakan University in the Primary Education Department between 2014 and 2018. Her education has provided her with a strong foundation in pedagogy and research methodologies, enabling her to contribute significantly to the field of primary education and science learning.

Experience

Dr. Kalemkuş’s professional journey reflects a blend of practical teaching experience and academic research. Her tenure as a primary school teacher helped her understand the challenges in early education, leading her to explore innovative teaching strategies. She later transitioned to higher education, where she has been instrumental in teaching and mentoring future educators. Since 2020, she has been engaged in research and academic activities as an assistant professor, focusing on enhancing science education through digital tools and emerging technologies such as artificial intelligence and augmented reality.

Research Interest

Dr. Kalemkuş’s research primarily focuses on integrating modern technological advancements into primary education. Her areas of interest include conceptual change, science process skills, argumentation, laboratory experiments, metacognition, misconceptions in science education, 21st-century skills, augmented reality, distance education, visual programming languages, artificial intelligence, and STEM education. Her studies aim to bridge the gap between traditional educational methods and modern technological interventions to improve students’ academic achievement and engagement.

Awards

Dr. Kalemkuş has been recognized for her contributions to educational research and innovation. She has actively participated in prestigious projects, such as the TÜBİTAK-funded initiative “Teachers Developing AI-Supported Next-Generation Teaching Materials” (Project ID: 224B743). Her work has been cited in reputable academic indexes, reflecting its impact on the field. Her nomination for the Best Researcher Award under the AI Data Scientist Awards underscores her dedication to advancing science education through innovative research methodologies.

Publications

Dr. Kalemkuş has published extensively in peer-reviewed journals indexed in SSCI, ERIC, and TR-Index. Some of her notable publications include:

Kalemkuş, J., & Kalemkuş, F. (2025). Primary school students’ perceptions of artificial intelligence: Metaphor and drawing analysis. European Journal of Education, 60(1), 1-23. https://doi.org/10.1111/ejed.70007

Kalemkuş, J., & Kalemkuş, F. (2024). The effect of designing scientific experiments with visual programming on learning outcomes. Science & Education, 1-23. https://doi.org/10.1007/s11191-024-00546-8

Kalemkuş, J., & Kalemkuş, F. (2023). Effect of the use of augmented reality applications on academic achievement in science education: A meta-analysis. Interactive Learning Environments, 31(9), 6017-6034. https://doi.org/10.1080/10494820.2022.2027458

Kalemkuş, J. (2024). Investigation of primary school teachers’ experiences on teaching science during distance education. Journal of Learning and Teaching in Digital Age, 9(2), 12-28. https://doi.org/10.53850/joltida.1326497

Kalemkuş, J., Bayraktar, Ş., & Çiftçi, S. (2021). Comparative effects of argumentation and laboratory experiments on metacognition, attitudes, and science process skills of primary school children. Journal of Science Learning, 4(2), 113-122. https://doi.org/10.17509/jsl.v4i2.27825

Kalemkuş, J. (2021). Fen bilimleri dersi öğretim programı kazanımlarının 21.yüzyıl becerileri açısından incelenmesi. Anadolu Journal of Educational Sciences International, 11(1), 63-87. https://doi.org/10.18039/ajesi.800552

Kalemkuş, J., Bayraktar, Ş., & Çiftçi, S. (2019). Eğitimde sosyal, zihinsel ve sözlü-yazılı bir aktivite: Argümantasyon. Turkish Studies, 14(4), 2449-2467. https://dx.doi.org/10.29228/TurkishStudies.23024

Conclusion

Dr. Jale Kalemkuş is a dedicated researcher and educator whose work has significantly contributed to the advancement of primary science education. Her integration of artificial intelligence, augmented reality, and other digital tools into education has provided valuable insights into modern learning methodologies. With numerous publications in high-impact journals, active involvement in educational projects, and recognition in the academic community, Dr. Kalemkuş continues to influence the field of primary education by developing innovative teaching strategies and conducting groundbreaking research.