Khadija Javed | Artificial Intelligence | Excellence in Research Award

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Dr. Khadija Javed | Artificial Intelligence | Excellence in Research Award

Assistant Professor| Lanzhou University | China

Dr. Khadija Javed is a prominent researcher at Lanzhou University, specializing in Artificial Intelligence with a focus on data-driven modeling, bioinformatics, and computational analysis. Her work integrates AI techniques with interdisciplinary applications, contributing to impactful research in healthcare, environmental studies, and intelligent systems, supported by a strong global citation record and academic influence.

Citation Metrics (Google Scholar)

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Featured Publications

Minimum redundancy feature selection from microarray gene expression data
– Journal of Bioinformatics and Computational Biology, 2005 | Citations: 4067
Effect of early tranexamic acid administration on mortality in women with post-partum haemorrhage
– The Lancet, 2017 | Citations: 1841
Origin of antibiotics and antibiotic resistance: impacts on drug development
– Pharmaceuticals, 2023 | Citations: 1330
Use of chest CT with negative RT-PCR for COVID-19 diagnosis
– Radiology, 2020 | Citations: 801
Heavy-metal-induced reactive oxygen species and phytotoxicity in plants
– Environmental Toxicology Review, 2014 | Citations: 741

Pascal Lorenz | Internet of Things (IoT) Data | Research Excellence Award

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Prof. Dr. Pascal Lorenz | Internet of Things (IoT) Data | Research Excellence Award

Professor| University of Haute Alsace | France

Prof. Dr. Pascal Lorenz is a distinguished researcher in Internet of Things (IoT) and data-driven network systems, recognized for advancing secure, energy-efficient communication technologies. His work spans wireless networks, IoT architectures, and intelligent routing protocols, contributing significantly to academic research and real-world applications, earning him recognition for research excellence.

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Featured Publications

Lightweight semantic compression visual cryptography for secure medical image transmission in IoT systems
– Scientific Reports, 2026 | Citations: 0

Optimized Route Selection in RPL: Static and Dynamic Parent Evaluation for Energy-Efficient IoT Networks
– Journal of Network and Systems Management, 2026

SARP: A Secure and Adaptive Machine Learning-Driven Routing Protocol for Dynamic IoT Networks
– Journal of Network and Systems Management, 2026

Li-Fi Range Challenge: Improvement and Optimization
– Telecom, 2026

An Efficient Post-Quantum Lattice-Based Encryption Scheme for Secure Communication in Vehicular Ad-Hoc Networks
– IEEE Transactions on Vehicular Technology, 2026

Anas Rao | Data-Driven Decision Making | Best Researcher Award

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Dr. Anas Rao | Data-Driven Decision Making | Best Researcher Award

Lecturer | UET Lahore | Pakistan

Dr. Anas Rao is a researcher at UET Lahore, Pakistan, specializing in data-driven decision making for advanced energy and mechanical systems. His work integrates machine learning, artificial intelligence, and statistical modeling to optimize hydrogen-enriched internal combustion engines, with a strong focus on NOx emission prediction, combustion analysis, and performance optimization. He applies ANNs, SVMs, and hybrid AI models to experimental and simulation data, enabling accurate, real-time decision support for cleaner and more efficient engine design and operation.

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778

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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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Citations
551

Documents
76

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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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Dr. Pankaj Kumar | Machine learning | Best Researcher Award

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Dr. Pankaj Kumar | Machine learning | Best Researcher Award

Assistant Professor, National Institute of Technology, Hamirpur

Dr. Pankaj Kumar is a researcher specializing in operations research, optimization methods in finance, interval optimization, machine learning and crop area planning. He earned a Ph.D. in Optimization Methods in Finance from the Indian Institute of Technology Kharagpur with his thesis on interval optimization methods for portfolio selection, and holds earlier advanced degrees in operations research and mathematics. Dr. Pankaj Kumar has served in research and teaching roles—most recently as Assistant Professor—focusing on modelling of portfolio optimization, multi-objective programming, time-series forecasting, and risk measures such as mean-VaR. His professional experience includes supervising research students, contributing to international and national collaborative projects, participating in workshops and conferences, and Dr. Pankaj Kumar’s scholarly output includes more than thirty peer-reviewed papers published in high-impact journals indexed by SCIE, Scopus, and Web of Science, and his work has attracted more than 360 citations with an h-index of 10, reflecting consistent academic influence. His research skills include mathematical modelling, statistical methods, algorithm design, programming in C and R, use of optimisation tools and applying machine learning regression techniques in finance contexts. Among his awards and honors are travel grants, junior/senior research fellowships, editorial board membership, and recognition for teaching and research excellence at his institution. In conclusion, Dr. Pankaj Kumar is positioned to further impact the fields of financial optimization and decision science through high-quality publications, interdisciplinary collaborations, and mentoring, likely to increase his citation profile, visibility, and leadership in both academic and applied settings.

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Featured Publications

Behera, J., & Kumar, P. (2025). An approach to portfolio optimization with time series forecasting algorithms and machine learning techniques. Applied Soft Computing, 170, 112741.

Sahu, B. R. B., & Kumar, P. (2025). Portfolio rebalancing model utilizing support vector machine for optimal asset allocation. Arabian Journal for Science and Engineering, 50(14), 10939–10965.

Sahu, B. R. B., Bhurjee, A. K., & Kumar, P. (2024). Efficient solutions for vector optimization problem on an extended interval vector space and its application to portfolio optimization. Expert Systems with Applications, 249, 123653.

Behera, J., & Kumar, P. (2024). Implementation of machine learning-based sparse Sharpe ratio portfolio optimization: A case study on Indian stock market. Operational Research, 24(4), 62.

Patel, M., Behera, J., & Kumar, P. (2024). Parametric approach for multi-objective enhanced interval linear fractional programming problem. Engineering Optimization, 56(5), 740–765.

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.

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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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.