Otilia Manta | Artificial Intelligence | Innovative Research Award

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

Otilia Manta at Romanian Academy/ Romanian American University | Romania

Otilia Manta, Prof. Dr., is a senior researcher and academic affiliated with the Romanian Academy and Romanian American University, whose work focuses on the intersection of economics, finance, and digital transformation. Her research addresses financial innovation, FinTech, artificial intelligence in management and education, sustainability, and economic resilience, with particular attention to policy design and institutional learning in emerging and European economies. Through bibliometric, empirical, and interdisciplinary approaches, she contributes to advancing knowledge on sustainable finance, digitalization, and evidence-based economic governance.

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Xiangyu Wang | Artificial Intelligence | Research Excellence Award

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Prof. Xiangyu Wang | Artificial Intelligence | Research Excellence Award

Executive director | East China Jiaotong University | China

Prof. Xiangyu Wang is a researcher at East China Jiaotong University whose work focuses on the intersection of applied mathematics, data analysis, and intelligent modeling. His research emphasizes statistical methods, optimization techniques, and quantitative analysis to address complex problems in engineering, economics, and management systems. He has contributed to studies involving data-driven decision-making, predictive modeling, and interdisciplinary applications of mathematical theory. Prof. Wang’s work supports the development of efficient analytical frameworks with practical relevance to real-world systems.

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Man Zhang | Artificial Intelligence | Best Researcher Award

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Prof. Dr. Man Zhang | Artificial Intelligence | Best Researcher Award

Professor | Beijing University of Civil Engineering and Architecture Artificial Intelligence | China

Prof. Dr. Man Zhang is a scholar at Beijing University of Civil Engineering and Architecture whose research focuses on the integration of artificial intelligence, spatial data analysis, and urban and architectural studies. His work spans cultural heritage preservation, knowledge graph construction, and smart city analytics, applying advanced models such as GIS-based spatial diagnostics, data field theory, and machine learning. He has made notable contributions to digital heritage documentation, sustainable historic district conservation, and urban transportation demand analysis. Through interdisciplinary methods, his research supports evidence-based urban planning and sustainable development.

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Ms. Shanazeer C K | Deep Learning | Best Researcher Award

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Ms. Shanazeer C K | Deep Learning | Best Researcher Award

Ms. Shanazeer C K | Pondicherry University Karaikal Campus | India

Dr. Shahnazeer C K is an accomplished academic and dedicated researcher in the field of Computer Science and Engineering, currently pursuing her research as a scholar at Pondicherry University, Karaikal Campus. With a strong academic foundation and an innovative research mindset, she has made significant contributions to computational intelligence and cloud computing, particularly focusing on developing frameworks that integrate artificial intelligence, deep learning, and federated learning for solving complex real-world problems. She combines her expertise in machine learning, data analytics, and cloud-based systems to create solutions that are not only technically advanced but also socially impactful. Her dedication to continuous learning and research excellence has established her as a promising researcher with a clear vision to contribute to advancements in computational technologies and intelligent systems.

Professional Profile

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Summary of Suitability

Dr. Shahnazeer C K is an accomplished researcher and scholar in the field of Computer Science and Engineering, specializing in Computational Intelligence, Machine Learning, and Cloud Computing. With  combined academic and industry experience, she has made significant contributions through impactful research, innovative frameworks, and technology-driven solutions, positioning her as a strong candidate for the Best Researcher Award.

Education

Dr. Shahnazeer C K holds a Bachelor of Technology (B.Tech.) in Information Technology from the Government Engineering College, Sreekrishnapuram, Kerala, which laid a strong foundation in computer science fundamentals and system design. She further enhanced her academic expertise by completing her Master of Technology (M.Tech.) in Information Technology from Anna University, Coimbatore, Tamil Nadu. Her postgraduate studies allowed her to specialize in advanced computing techniques, algorithms, and intelligent systems, equipping her with the technical and analytical skills essential for solving modern computational challenges. Currently, she is pursuing a Doctor of Philosophy (Ph.D.) in Computer Science and Engineering at Pondicherry University, Karaikal Campus, where her research work primarily focuses on computational intelligence and its applications in multi-disease prediction and federated learning frameworks.

Experience

With over nine years of academic experience as an Assistant Professor in various engineering colleges across Kerala, Dr. Shahnazeer C K has consistently demonstrated her ability to impart quality education, mentor students, and contribute to curriculum development in computer science-related disciplines. In addition to her academic expertise, she has four years of industry experience, which provided her with practical exposure to real-time problem-solving, software development, and system integration. Her combined academic and industry background has enabled her to bridge the gap between theoretical concepts and practical implementations, making her a versatile and resourceful professional in the field of computer science. Her active involvement in teaching, research, and guiding students has positioned her as a key contributor to academic and research excellence.

Research Interests

Dr. Shahnazeer C K core research interests lie in Computational Intelligence, Cloud Computing, Machine Learning, and Federated Learning. Her ongoing research focuses on designing intelligent frameworks that leverage deep learning, transfer learning, and federated learning techniques to improve multi-disease prediction models while maintaining patient data privacy and security. One of her key contributions includes the development of a Federated Transfer Learning (FTL) Framework designed to predict multiple diseases such as heart, kidney, lung, and liver conditions using clinical and laboratory datasets. The framework integrates preprocessing techniques like normalization, feature selection, and imputation with advanced machine learning classifiers such as Support Vector Machines (SVM), delivering improved accuracy, robustness, and reliability. Her research is further enhanced by cloud-based deployments using Amazon Web Services (AWS), ensuring scalability and efficient data processing. Through her work, she aims to advance intelligent healthcare solutions by combining innovative computational methods with real-world applications.

Awards

Dr. Shahnazeer C K has authored four books with ISBN numbers, showcasing her expertise in emerging areas of computer science and engineering. She has also successfully filed two patents and has one patent under process, demonstrating her commitment to technological innovation and the development of novel computational solutions. As an active member of professional organizations such as the IEEE Computational Intelligence Society, IEEE Computer Society, IEEE Electron Devices Society, and IEEE Young Professionals, she stays engaged with the latest trends and contributes to the advancement of the research community. Her professional memberships enable her to collaborate with peers, exchange knowledge, and remain at the forefront of cutting-edge technologies. These achievements reflect her consistent efforts toward research excellence, innovation, and impactful contributions to society.

Publication Top Notes

Digital Misinformation and Fake News Detection using WoT Integration with Asian Social Networks Fusion-based Feature Extraction with Text and Image Classification by Machine
Year: 2022
Citations: 9

A TDMA-Based Smart Clustering Technique for VANETs
Year: 2014
Citations: 7

Efficient Multipath Routing Protocol for VANET using Path Restoration
Year: 2013
Citations: 6

6G Cyber Physical System-based Smart Healthcare Modelling by Mobile Edge Network and Artificial Intelligence
Year: 2024
Citations: 3

Increasing the Lifetime of Cluster Head using Improved Stability-based Clustering Approach in VANETs
Year: 2015
Citations: 1

Conclusion

Through her consistent research efforts, academic contributions, and innovations, Dr. Shahnazeer C K has established herself as an emerging leader in computational intelligence and cloud-based intelligent systems. Her ongoing work demonstrates a unique combination of technical expertise, practical applications, and social impact, particularly in the domain of multi-disease prediction frameworks and privacy-preserving healthcare analytics. With her growing portfolio of publications, patents, and books, she continues to contribute significantly to the scientific community and inspire future researchers. Her dedication to advancing computational intelligence makes her a highly deserving candidate for the Best Researcher Award, highlighting her commitment to excellence, innovation, and meaningful contributions to the field of computer science and engineering.

Khalifa Aliyu Ibrahim | Artificial Intelligence | Best Researcher Award

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Mr. Khalifa Aliyu Ibrahim | Artificial Intelligence | Best Researcher Award

PhD Researcher at Cranfield University, United Kingdom

Khalifa Aliyu Ibrahim is a distinguished academic and engineering professional currently serving as a Research Assistant at Cranfield University’s Centre for Energy Engineering. He is actively pursuing a PhD focused on the AI-driven design of high-frequency power electronics, aiming to establish a robust theoretical foundation and explore cutting-edge technologies in power electronic design through artificial intelligence. His career is marked by a seamless transition from theoretical and experimental physics to engineering, underscoring his versatility and dedication to advancing energy systems, power electronics, and thermal management. ​

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Education

Khalifa’s academic journey is characterized by excellence and a commitment to continuous learning. He earned a Master of Science in Energy Systems and Thermal Processes with Distinction from Cranfield University, UK, in 2021. Subsequently, he completed a Master’s by Research in Energy and Power at the same institution in 2023, where he conducted significant research on concentrated photovoltaic cooling design. Prior to his postgraduate studies, Khalifa graduated as the only first-class student in his cohort with a Bachelor of Science in Physics from Kaduna State University, Nigeria, in 2016, achieving a CGPA of 4.56/5.00.

Experience

With over four years of experience in the academic sector, Khalifa has demonstrated expertise in both teaching and research. At Cranfield University, he has been instrumental in building and testing prototypes for small-scale green hydrogen plants and has supervised laboratory activities for MSc students. His previous roles include lecturing positions at Kaduna State University and Nuhu Bamalli Polytechnic in Nigeria, where he taught theoretical and experimental physics to large student cohorts. Additionally, he served as a Teaching and Laboratory Assistant at Umaru Musa Yar’adua University, contributing to both educational and administrative functions. ​

Research Interests

Khalifa’s research interests are deeply rooted in energy and power systems, with a particular focus on integrating artificial intelligence into power electronics design. He is also engaged in exploring sustainable hydrogen production methods, advanced cooling techniques for photovoltaic cells, and the development of scalable optical meta-surface designs for agricultural applications. His work aims to address contemporary challenges in energy efficiency and sustainability, reflecting a commitment to innovative solutions in the field. ​

Awards

Khalifa’s academic excellence and research contributions have been recognized through several prestigious awards. In 2021, he received the Petroleum Technology Development Fund Scholarship worth £31,000. The previous year, he was awarded a merit-based foreign scholarship by the Kaduna State Scholarship and Loan Board, Nigeria, valued at £27,000. Earlier in his academic journey, he secured a cash prize and a Certificate of Participation in the Nigeria Centenary Quiz Show in 2014, highlighting his longstanding dedication to academic and intellectual pursuits. ​

Publications

Khalifa has contributed to the academic community through several notable publications:​

“Harnessing Energy for Wearables: A Review of Radio Frequency Energy Harvesting Technologies” (2023, Energies). This paper reviews RF energy harvesting technologies for wearable devices. ​

“Cooling of Concentrated Photovoltaic Cells—A Review and the Perspective of Pulsating Flow Cooling” (2023, Energies). This article examines cooling methods for concentrated photovoltaic cells, emphasizing pulsating flow cooling. ​

“High-Performance Green Hydrogen Generation System” (2021, IEEE 20th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications). This conference paper presents a high-performance system for green hydrogen generation.

“The Effect of Solar Irradiation on Solar Cells” (2019, Science World Journal). This study investigates how solar irradiation impacts the performance of solar cells.

“Use of Azimuthal Square-Array Direct-Current Resistivity Method to Determine Geological Fractures” (2019, Journal of the Nigerian Association of Mathematical Physics). This research utilizes resistivity methods to identify geological fractures. ​

“Advancing Hydrogen: A Closer Look at Implementation Factors, Current Status and Future Potential” (2023, Energies). This paper explores the current status and future potential of hydrogen implementation. ​

“A Scalable Optical Meta-Surface Glazing Design for Agricultural Greenhouses” (2024, Physica Scripta). This article discusses a scalable design for optical meta-surface glazing in agricultural greenhouses. ​

Conclusion

Khalifa Aliyu Ibrahim exemplifies a blend of academic excellence, research innovation, and practical experience. His contributions to energy systems, power electronics, and sustainable technologies reflect a commitment to addressing global energy challenges through interdisciplinary approaches. As he continues his PhD research, his work is poised to make significant impacts in the fields of artificial intelligence and power electronics, further solidifying his role as a leading figure in contemporary energy research.

Engin Eren Kavak | Artificial Intelligence | Best Researcher Award

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Dr. Engin Eren Kavak | Artificial Intelligence | Best Researcher Award

M.D. at Etlik City Hospital, Turkey

Dr. Engin Eren Kavak is a dedicated specialist in internal medicine and medical oncology with a strong background in clinical research and patient care. Currently serving at Etlik City Hospital in the Department of Medical Oncology, Dr. Kavak has contributed significantly to advancements in cancer treatment through his participation in clinical trials and research initiatives. His expertise spans various oncological conditions, with a keen interest in immunotherapy and targeted therapy approaches.

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Education

Dr. Kavak’s academic journey began at Karadeniz Technical University Faculty of Medicine, where he earned his medical degree in 2010. He then pursued a specialization in internal medicine at Kırıkkale University Faculty of Medicine, completing his residency in 2016. Further honing his expertise, he undertook a fellowship in medical oncology at Ankara University Faculty of Medicine from 2020 to 2023. His rigorous academic training has equipped him with extensive knowledge in diagnosing and managing complex oncological cases.

Professional Experience

Dr. Kavak commenced his medical career as a General Practitioner at Ağrı State Hospital (2010–2012). He then advanced into internal medicine, serving as a resident at Kırıkkale University Faculty of Medicine (2012–2016). Following his specialization, he worked as an Internal Medicine Specialist at Yozgat City Hospital from 2016 to 2020. His pursuit of excellence led him to Ankara University Faculty of Medicine, where he trained as a Medical Oncology Fellow (2020–2023). Since 2023, he has been practicing as an Internal Medicine and Medical Oncology Specialist at Etlik City Hospital, contributing to both patient care and clinical research.

Research Interests

Dr. Kavak’s research focuses on optimizing cancer therapies, particularly in the realms of immunotherapy and precision medicine. He has been involved in multiple clinical trials evaluating novel therapeutic strategies for lung, prostate, bladder, and ovarian cancers. His work in these areas aims to improve patient outcomes through innovative treatment modalities and a personalized approach to oncology care.

Awards

Dr. Kavak has been recognized for his contributions to oncology research and clinical practice. His commitment to advancing medical knowledge has earned him accolades at various academic and professional conferences. He remains an active participant in medical forums dedicated to cancer research and treatment innovations.

Publications

Kavak EE et al. (2022). “Efficacy of Immunotherapy in Advanced Non-Small Cell Lung Cancer.” Journal of Oncology Research, cited by 45 articles.

Kavak EE et al. (2021). “Targeted Therapy in Prostate Cancer: A New Era.” International Journal of Cancer Treatment, cited by 38 articles.

Kavak EE et al. (2021). “Olaparib in Combination with Chemotherapy for Ovarian Cancer Patients Without BRCA Mutations.” European Oncology Review, cited by 30 articles.

Kavak EE et al. (2020). “Durvalumab as a Treatment Option for Urothelial Carcinoma.” Medical Oncology Journal, cited by 27 articles.

Kavak EE et al. (2020). “Combination Therapy Using Pembrolizumab in Metastatic Prostate Cancer.” Journal of Clinical Oncology Advances, cited by 33 articles.

Kavak EE et al. (2019). “Checkpoint Inhibitors in Bladder Cancer: Clinical Trial Outcomes.” Cancer Therapeutics Review, cited by 25 articles.

Kavak EE et al. (2018). “Role of Chemoradiotherapy in Advanced Bladder Cancer.” Oncology and Hematology Reports, cited by 20 articles.

Conclusion

Dr. Engin Eren Kavak’s contributions to medical oncology extend beyond clinical practice into the realms of research and innovation. His dedication to improving patient care through evidence-based treatments and participation in groundbreaking clinical trials underscores his commitment to the field. As he continues to advance oncology research and practice, his work remains instrumental in shaping future cancer treatment paradigms.

Petcharaporn Yodjai | Computer Science | Best Researcher Award

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Ms. Petcharaporn Yodjai | Computer Science | Best Researcher Award

Ph.D. Student at King Mongkut’s University of Technology Thonburi, Thailand

Petcharaporn Yodjai is a dedicated researcher in the field of applied mathematics, with a particular focus on image processing and mathematical modeling. Currently a Ph.D. candidate at King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand, she has made significant contributions to the development of advanced techniques in image inpainting and completion. Her work integrates theoretical mathematical principles with practical applications, offering innovative solutions in digital image processing. Yodjai’s academic journey is marked by excellence, as she earned her Bachelor of Science in Mathematics with First Class Honours from Maejo University. She has been the recipient of prestigious scholarships and fellowships, allowing her to conduct research at renowned institutions worldwide.

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Education

Yodjai embarked on her academic journey at Maejo University, where she pursued a Bachelor of Science in Mathematics from July 2015 to April 2019. Her outstanding academic performance earned her First Class Honours. Continuing her passion for applied mathematics, she enrolled in the Ph.D. program at King Mongkut’s University of Technology Thonburi in July 2019. Throughout her doctoral studies, she has focused on developing mathematical methods for image processing, with an emphasis on structure propagation and sparse representation techniques. Her education has been supplemented by international research experiences through various exchange programs and fellowships.

Experience

Yodjai has accumulated significant research experience through international collaborations and exchange programs. In 2023, she conducted short-term research at the North University Center at Baia Mare, Technical University of Cluj-Napoca, Romania, followed by a long-term research stint at the University of Jaén, Spain, from September 2022 to February 2023. Earlier, she engaged in a research project at Gyeongsang National University, South Korea, in 2022. Additionally, she has served as a teaching assistant at KMUTT, assisting in undergraduate mathematics courses over multiple semesters, which has enhanced her pedagogical skills. Her participation in international conferences has allowed her to present her research findings and collaborate with experts in her field.

Research Interests

Yodjai’s research interests lie in applied mathematics, specifically in image processing, mathematical modeling, and computational methods. She has focused on developing efficient algorithms for image inpainting, structure propagation, and sparse representation. Her work incorporates techniques such as Bezier curves and deep learning segmentation to enhance image restoration processes. She is particularly interested in bridging the gap between mathematical theory and real-world applications, ensuring that her research contributes to advancements in digital imaging and computational science.

Awards and Scholarships

Yodjai has been recognized for her academic excellence and research contributions through several prestigious scholarships and awards. She is a recipient of the Royal Golden Jubilee Ph.D. Scholarship from the National Research Council of Thailand, which has supported her doctoral studies since 2019. She also received funding from the Japan Science and Technology Agency under the SAKURA Exchange Program in Science in 2023. Furthermore, she participated in the Erasmus+ program, funded by Romania, which facilitated her research collaboration with European institutions.

Publications

Yodjai, P., Kumam, P., & Martínez-Moreno, J. (2025). Image Completion Using Automatic Structure Propagation With Bezier Curves. Mathematical Methods in the Applied Sciences.

Jirakipuwapat, W., Sombut, K., Yodjai, P., & Seangwattana, T. (2025). Enhancing Image Inpainting With Deep Learning Segmentation and Exemplar-Based Inpainting. Mathematical Methods in the Applied Sciences.

Yodjai, P., Kumam, P., Martínez-Moreno, J., & Jirakitpuwapat, W. (2024). Image inpainting via modified exemplar-based inpainting with two-stage structure tensor and image sparse representation. Mathematical Methods in the Applied Sciences, 47(11), 9027-9045.

Awwal, A. M., Wang, L., Kumam, P., Sulaiman, M. I., Salisu, S., Salihu, N., & Yodjai, P. (2023). Generalized RMIL conjugate gradient method under the strong Wolfe line search with application in image processing. Mathematical Methods in the Applied Sciences, 46(16), 17544-17556.

Yodjai, P., Kumam, P., Kitkuan, D., Jirakitpuwapat, W., & Plubtieng, S. (2019). The Halpern approximation of three operators splitting method for convex minimization problems with an application to image inpainting. Bangmod International Journal of Mathematical and Computational Science, 5, 58-75.

Conclusion

Petcharaporn Yodjai’s research contributions in applied mathematics, particularly in image inpainting and completion, demonstrate her dedication to advancing computational methodologies. Through her international collaborations, numerous publications, and teaching experience, she has established herself as a promising scholar in the field. Her work continues to impact digital image processing, providing solutions that enhance the accuracy and efficiency of image restoration techniques. With her expertise and commitment to research, she is poised to make significant advancements in mathematical modeling and computational science in the coming years.

Behzad Imani | Machine Learning | AI & Machine Learning Award

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Assoc. Prof. Dr. Behzad Imani | Machine Learning | AI & Machine Learning Award

Associate Professor in Nursing at Hamadan University of Medical Sciences, Iran

Dr. Behzad Imani is a distinguished scholar in the field of nursing education with extensive experience in clinical research, education, and healthcare practice. With a strong background in nursing and pedagogy, Dr. Imani has significantly contributed to the development of educational tools and methodologies that enhance the training of clinical nurses. His work focuses on bridging the gap between theoretical knowledge and practical application, ensuring that nursing professionals are equipped with the necessary competencies to deliver high-quality patient care.

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Education

Dr. Imani earned his Ph.D. in Nursing Education from Tarbiat Modares University of Tehran between 2013 and 2017. His doctoral research centered on the development and psychometric validation of an emotional intelligence assessment tool designed for clinical nurses. This study has played a pivotal role in advancing the understanding of emotional intelligence in healthcare settings, emphasizing its impact on patient care and workplace dynamics. Dr. Imani’s academic journey reflects his commitment to elevating nursing education through rigorous research and evidence-based practices.

Experience

With a career spanning over two decades, Dr. Imani has served in various academic and clinical capacities, fostering the professional growth of nurses and healthcare practitioners. His experience includes teaching at renowned medical universities, designing curricula for nursing programs, and supervising graduate research projects. Dr. Imani has also worked in clinical settings, where he has applied his expertise in patient care, surgical nursing, and healthcare management. His multidisciplinary approach integrates education, clinical practice, and research to enhance healthcare delivery and nursing competence.

Research Interests

Dr. Imani’s research primarily focuses on nursing education, emotional intelligence, patient care strategies, and occupational health among healthcare workers. His studies explore the psychological and emotional aspects of nursing, emphasizing the importance of mental well-being in professional practice. Additionally, he has investigated topics such as work engagement among surgical technologists, the impact of surgical smoke on healthcare personnel, and strategies for improving operating room safety. His work aims to improve both the educational experiences of nursing students and the working conditions of healthcare professionals.

Awards

Dr. Imani has been recognized for his contributions to nursing education and research through numerous awards and honors. His innovative research on emotional intelligence in nursing has garnered attention at academic conferences and medical symposiums. Additionally, he has received accolades for his teaching excellence and dedication to mentoring students in the field of nursing and healthcare management. His work has also influenced policy recommendations on improving occupational health standards in clinical environments.

Publications

Dr. Imani has authored multiple research articles and books in both Persian and English. Below are some of his notable publications:

Imani, B., Zandi, S., Mostafayi, M., Zandi, F. (2022). “Presentation of a model of the work engagement in surgical technologists: A qualitative study.” Perioperative Care and Operating Room Management, 26, 100235. [Cited: X times]

Merajikhah, A. M., Imani, B., Khazaei, S., Bouraghi, H. (2022). “Impact of Surgical Smoke on the Surgical Team and Operating Room Nurses and its Reduction Strategies: A Systematic Review.” Iran J Public Health, 51(1), 27-36. [Cited: X times]

Bastami, M., Imani, B., Koosha, M. M. (2022). “Operating room nurses experience about patient care for laparotomy surgeries: A phenomenological study.” Journal of Family Medicine and Primary Care. [Cited: X times]

Imani, B., Zandi, S., Khazaei, S., Mirzaei, M. (2021). “The lived experience of HIV-infected patients in the face of a positive diagnosis: A phenomenological study.” AIDS Research and Therapy, 18(1), 95. [Cited: X times]

Mostafayi, M., Imani, B., Zandi, S., Jongi, F. (2021). “Impact of Maternal Anxiety and Hemodynamic Parameters during a Cesarean Section on the Neonatal Apgar Score.” Acta Scientific Women’s Health, 3(6). [Cited: X times]

Mahdood, B., Imani, B., Khazaei, S. (2022). “Effects of inhalation aromatherapy with Rosa damascena on state anxiety and sleep quality of operating room personnel during the COVID-19 pandemic: A randomized controlled trial.” Journal of PeriAnesthesia Nursing. [Cited: X times]

Shirdel, Z., Imani, B., Manafi, B. (2021). “The Effect of Home Care Training on Anxiety and Vital Signs Levels in Coronary Artery Bypass Grafting Patients: A Randomized Clinical Trial.” Journal of PeriAnesthesia Nursing, 36, 393-397. [Cited: X times]

Conclusion

Dr. Behzad Imani is a leading figure in nursing education and clinical research, with a profound impact on the academic and healthcare sectors. His work in emotional intelligence, occupational health, and nursing education has contributed to advancements in training methodologies and patient care practices. Through his dedication to research, teaching, and clinical application, Dr. Imani continues to shape the future of nursing by fostering a generation of competent and emotionally intelligent healthcare professionals. His contributions extend beyond academia, influencing policies and practices that enhance the well-being of both nurses and patients in clinical environments.

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.

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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.

Deepak Parashar | Deep Learning | Best Researcher Award

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Dr. Deepak Parashar | Deep Learning | Best Researcher Award

Associate Professor | GSFC University Vadodara Gujarat | India

Dr. Deepak Parashar is an accomplished academician and researcher specializing in Artificial Intelligence and Machine Learning. He is currently serving as an Associate Professor in the Department of Computer Science & Engineering at the School of Technology, GSFC University, Vadodara, Gujarat, India. With over 14 years of academic and research experience, Dr. Parashar has contributed significantly to the field of medical image analysis and computer vision. His expertise lies in developing AI-driven diagnostic solutions, particularly for glaucoma detection. Throughout his career, he has been dedicated to fostering research, mentoring students, and advancing technological innovation in healthcare.

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Scopus

Education

Dr. Parashar holds a Ph.D. in AI & Machine Learning, with a specialization in medical imaging, from Maulana Azad National Institute of Technology (NIT), Bhopal, India, awarded in February 2022. His thesis focused on improving the classification of glaucoma in retinal fundus images using image decomposition techniques under the supervision of Dr. D. K. Agrawal. He completed his M.Tech. from SGSITS Indore in 2011 and earned his B.E. degree from Indira Gandhi Government Engineering College, Sagar, in 2008. His academic journey started at Jawahar Navodaya Vidyalaya, Ratlam, MP, India, where he completed his schooling under the CBSE Board.

Experience

Dr. Parashar has held various academic and research positions throughout his career. Before joining GSFC University in May 2024, he served as an Assistant Professor at SIT Pune, Symbiosis International University, from 2022 to 2024. He was a Research Fellow at the Image Processing Research Lab, NIT Bhopal, from 2018 to 2022. Previously, he worked as an Assistant Professor in the Department of Electronics and Communication Engineering at G H Patel College of Engineering and Technology (2012-2017) and Shri Vaishnav Institute of Technology and Science (2011-2012). His career began as a Lecturer at Government Engineering College, Ujjain, in 2008.

Research Interests

Dr. Parashar’s research focuses on Artificial Intelligence, Machine Learning, Image Processing, and Medical Image Analysis. His primary interest is in developing automated diagnostic systems for medical applications, particularly in ophthalmology and dermatology. His work on glaucoma detection using AI-based techniques has contributed significantly to the field. He is currently involved in an AI-driven project for early melanoma detection, funded by the Indian Council of Medical Research (ICMR). His research aims to enhance the accuracy and efficiency of medical diagnostics through advanced computational techniques.

Awards and Achievements

Dr. Parashar has received numerous accolades for his contributions to research and academia. He was awarded a Doctoral Fellowship for the TEQIP-III funded project at NIT Bhopal from 2018 to 2022. He has also been recognized as a Senior Member of IEEE and is a GATE-qualified professional. Additionally, he has received the SERB-OVDF Fellowship acceptance and has been an active peer reviewer for reputed SCI journals and conferences hosted by IEEE, Elsevier, and Springer. His early achievements include recognition in the National Mathematics Olympiad Contest (2001) and the All India UN Information Test (1999).

Publications

Dr. Parashar has published extensively in high-impact journals and conferences.

“2-D Compact Variational Mode Decomposition Based Automatic Classification of Glaucoma Stages from Fundus Images” – IEEE Transactions on Instrumentation and Measurement, 2021.

“Automatic Classification of Glaucoma Stages Using Two-Dimensional Tensor Empirical Wavelet Transform” – IEEE Signal Processing Letters, 2021.

“Automated Classification of Glaucoma Stages Using Flexible Analytic Wavelet Transform from Retinal Fundus Images” – IEEE Sensors Journal, 2020. His research has been widely cited, contributing significantly to advancements in medical AI.

Conclusion

Dr. Deepak Parashar is a dedicated academician and researcher committed to advancing AI-driven solutions in medical imaging. With extensive experience in teaching and research, he has significantly contributed to the fields of AI, Machine Learning, and Computer Vision. His ongoing research and publications continue to impact the scientific community, making strides in automated healthcare diagnostics. As an educator and mentor, he remains focused on fostering student growth and innovation in technology, ensuring a positive and lasting influence on the future of AI applications in medicine.