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. ​

Profile

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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.

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.

Profile

Scopus

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.

Profile

Orcid

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.

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.

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.

Profile

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.

Luigi Bibbo’ | Artificial Intelligence | AI & Machine Learning Award

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Dr. Luigi Bibbo’ | Artificial Intelligence | AI & Machine Learning Award

Research Fellow | Mediterranea University of Reggio Calabria | Italy

Dr. Luigi Bibbò is a distinguished researcher and academician specializing in electronic and computer engineering. With a strong foundation in biomedical engineering, he has contributed significantly to the fields of sensors, photonics, artificial intelligence, and nanotechnology. His extensive research experience spans multiple institutions across Italy, China, and the United States, where he has worked on cutting-edge technologies for biomedical applications, environmental monitoring, and robotics. Dr. Bibbò is actively involved in research projects focusing on big data analysis, forecasting systems, and healthcare-related AI applications.

Profile

Orcid

Education

Dr. Bibbò holds a PhD in Electronic and Computer Engineering from the Second University of Naples, awarded in 2015. His doctoral research focused on the development of sensors based on plasmon resonance in polymer optical fibers and photonic crystals. Prior to his PhD, he obtained a Master’s degree in Biomedical Engineering from Federico II University of Naples in 2009, where he specialized in organic semiconductor-based OFET for biomedical applications. His academic journey began with a Bachelor’s degree in Biomedical Engineering from the same institution in 2006, focusing on innovative cardiac diagnostic technologies using multislice computed tomography. He later qualified as a professional engineer in 2010.

Experience

Dr. Bibbò has held various research positions at prestigious institutions. Since April 2024, he has been a Research Fellow at the Mediterranean University of Reggio Calabria, working on big data analysis and forecasting systems for climate change adaptation under the TECH4YOU project. From March 2023 to March 2024, he was a Research Fellow at the University of Florence, contributing to the Pharaon Project, which focuses on robotic technologies, IoT, and artificial intelligence for biomedical applications. Prior to this, he served as an Assistant Professor (RTDA) at the Mediterranean University of Reggio Calabria from 2019 to 2022, leading projects on elderly monitoring and localization systems. His international experience includes research fellowships at Shenzhen University, China (2016-2019), where he developed metasurfaces for OAM beam generation, and a visiting scientist role at Tufts University, USA (2013-2014), working on plasmonic-photonic hybrid crystal sensors.

Research Interests

Dr. Bibbò’s research interests encompass a wide range of interdisciplinary fields, including sensors, photonics, fiber optics, MEMS, metamaterials, nanotechnology, artificial intelligence, neural networks, virtual reality, and augmented reality. He has led multiple projects involving CNN-based image classification, predictive modeling using Random Forest Regressor, and AI-driven motion analysis in healthcare. His work integrates fundamental engineering principles with advanced computational techniques to develop innovative solutions for biomedical and environmental challenges.

Awards

Dr. Bibbò has been recognized for his outstanding contributions to research and technology development. He was the winner of the Technologist I° competition at the Mediterranean University of Reggio Calabria. Additionally, he has been a fellow of the Engineering Research Council (FERC) and an active member of Frontiers in Neuroscience. His research has earned him invitations to prestigious international conferences and collaborations with leading scientific journals as a guest editor and reviewer.

Publications

Dr. Bibbò has authored several influential publications in high-impact journals.

Bibbò, L., et al. (2023). “Human Activity Recognition in Healthcare: A Machine Learning Approach.” MDPI Applied Sciences. Cited by 45 articles.

Bibbò, L., et al. (2022). “Development of AI-driven Motion Analysis for Biomedical Applications.” IEEE Access. Cited by 38 articles.

Bibbò, L., et al. (2021). “Nanophotonic Metasurfaces for Orbital Angular Momentum Beam Generation.” Journal of Optics. Cited by 56 articles.

Bibbò, L., et al. (2020). “Plasmonic Nanoparticles and Tunable Dielectric Matrix for Optical Sensing.” Journal of Physics D: Applied Physics. Cited by 72 articles.

Bibbò, L., et al. (2019). “Indoor Navigation System for Dementia Patients Using Augmented Reality.” Frontiers in Neuroscience. Cited by 33 articles.

Bibbò, L., et al. (2018). “Integration of MEMS Sensors for Real-Time Tracking in Smart Environments.” Nanotechnology. Cited by 41 articles.

Bibbò, L., et al. (2017). “Plasmonic-Photonic Hybrid Crystal Sensors for Biochemical Detection.” Journal of Optical Society of America B. Cited by 60 articles.

Conclusion

Dr. Luigi Bibbò’s career is marked by a dedication to advancing electronic and computer engineering through interdisciplinary research. His contributions to biomedical applications, nanotechnology, and artificial intelligence have positioned him as a leading researcher in his field. Through his extensive publication record, international collaborations, and innovative projects, he continues to push the boundaries of technology to improve healthcare, environmental monitoring, and human-computer interaction. His ongoing work at the Mediterranean University of Reggio Calabria and other institutions highlights his commitment to cutting-edge research and knowledge dissemination in engineering and applied sciences.