Akshaya Kumar Mandal | Machine learning | Best Researcher Award

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Dr. Akshaya Kumar Mandal | Machine learning | Best Researcher Award

Research Scholar, Assam University, India

Dr. Akshaya Kumar Mandal is a highly accomplished academic and researcher in the field of computer science. Currently serving as a Research Fellow at the Department of Computer Science, Assam University, India, he specializes in bio-inspired computing, machine learning, big data analytics, and bioinformatics. His research contributions span various interdisciplinary domains, focusing on solving complex problems in areas like disease detection, classification, and anomaly detection using innovative machine learning techniques. Dr. Mandal has an extensive educational background, holding a Ph.D. in Computer Science, along with M.Phil., M.Tech., and various other degrees, which have paved the way for his notable research career. His work is driven by a passion for developing practical, technology-driven solutions to pressing challenges in healthcare and beyond.

Profile

Education

Dr. Mandal’s academic journey reflects his deep commitment to learning and advancing knowledge in computer science. He obtained his Ph.D. from Assam University in 2024, with a thesis titled “Application of Bio-inspired Computing Techniques in Select Areas of Bioinformatics.” Prior to this, he completed his M.Phil. in Computer Science from F.M. University, Odisha in 2019, focusing on Ant Colony Optimization for solving NP-hard problems. He also holds an M.Tech. degree in Computer Science from Utkal University, Bhubaneswar, earned in 2007, where he conducted research on the comparison of multiple sequence alignment in DNA sequences. His educational foundation was laid with a Bachelor’s in Mathematics & Computer Applications from F.M. University, where he graduated with distinction. Dr. Mandal’s varied and comprehensive academic background has greatly contributed to his expertise in machine learning and bioinformatics.

Experience

Dr. Mandal has over 15 years of experience in teaching, research, and academic leadership. He served as a Senior Lecturer and Assistant Professor in the Department of Computer Science & Engineering at KIST, Bhubaneswar, from 2007 to 2018. During this time, he played a key role in delivering undergraduate and postgraduate courses, contributing to curriculum development, and mentoring students. Prior to this, he held lecturer positions at the Department of IT CET, Bhubaneswar, and the Department of Computer Science at NIIS Bhubaneswar. In addition to his teaching career, Dr. Mandal has an active research profile, with several years of experience as a Research Fellow in prominent institutions like Assam University, F.M. University, and Utkal University. His academic leadership and research endeavors have shaped his career trajectory in academia and research.

Research Interests

Dr. Mandal’s research interests are diverse, yet interconnected through a common theme of leveraging computational intelligence to solve real-world problems. His primary research areas include machine learning, bio-inspired computing, big data analytics, and bioinformatics. His work focuses on using machine learning for pattern recognition, anomaly detection, and disease classification, with applications in healthcare, such as heart disease prediction, skin disease detection, and disease diagnostics. Additionally, Dr. Mandal explores the intersection of biology and computation, particularly through bio-inspired algorithms like Ant Colony Optimization and Particle Swarm Optimization, to develop innovative solutions for bioinformatics problems, including DNA sequence alignment and codon selection. His interdisciplinary research aims to push the boundaries of artificial intelligence and computational biology.

Award

Based on the provided Curriculum Vitae, Dr. Akshaya Kumar Mandal appears to be a highly qualified and accomplished individual in the field of Computer Science, particularly in the areas of machine learning, bio-inspired computing, big data analytics, and bioinformatics. Below is a comprehensive evaluation of Dr. Mandal’s qualifications and contributions that make him a strong candidate for the Best Researcher Award.

Publication

Mandal, A.K., Dehuri, S., & Sarma, P.K.D. (2025). “Analysis of Machine Learning Approaches for Predictive Modeling in Heart Disease Detection Systems.” Biomedical Signal Processing and Control.

Mandal, A.K., & Sarma, P.K.D. (2024). “Usage of Particle Swarm Optimization in Digital Images Selection for Monkeypox Virus Prediction and Diagnosis.” Malaysian Journal of Computer Science.

Mandal, A.K., Sarma, P.K.D., & Dehuri, S. (2023). “A Study of Bio-inspired Computing in Bioinformatics: A State-of-the-art Literature Survey.” The Open Bioinformatics Journal.

Mandal, A.K., Sarma, P.K.D., & Dehuri, S. (2023). “Image-based Skin Disease Detection and Classification through Bioinspired Machine Learning Approaches.” International Journal on Recent and Innovation Trends in Computing and Communication.

Mandal, A.K., Mansur Barbhuiya, N., & Sarma, P.K.D. (2023). “A Hybrid Ant Colony Optimization Algorithm for Human Monkeypox DNA Codon Selection.” Journal of Propulsion Technology.

Mandal, A.K., Sarma, P.K.D., & Dehuri, S. (2024). “A Hybrid Machine Learning Based Cuckoo Search Clustering with Application of Image Recognition Techniques for Tomato Flu Skin Lesion Detection.” Machine Intelligence, Tools, and Applications.

Mandal, A.K., & Dehuri, S. (2020). “A Survey on Ant Colony Optimization for Solving Some of the Selected NP-Hard Problem.” Springer International Publishing.
These publications have been cited in various international articles, reflecting their significant contribution to the fields of machine learning and bioinformatics.

Conclusion

Dr. Akshaya Kumar Mandal’s academic and research journey demonstrates a deep commitment to advancing the field of computer science through innovative research and effective teaching. His work in bio-inspired computing, machine learning, and bioinformatics continues to make a notable impact on healthcare, bioinformatics, and computational biology. With an extensive teaching background and a solid record of research publications, Dr. Mandal is poised to contribute significantly to future developments in his areas of expertise. His passion for solving real-world problems using advanced computational techniques makes him a valuable asset to both academia and the broader scientific community.

Poonam Arora | Quantum Sensing | Best Researcher Award

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Dr. Poonam Arora | Quantum Sensing | Best Researcher Award

Senior Principal Scientist, CSIR-National Physical Laboratory, India

Dr. Poonam Arora is a distinguished physicist currently serving as Senior Principal Scientist and Head of the Indian Standard Time (IST) Division at CSIR-National Physical Laboratory (CSIR-NPL), India. With a career spanning over two decades, she has made significant contributions to applied optics, atomic clocks, and time dissemination. Her research has been instrumental in advancing high-precision metrology and time standards, impacting both scientific and industrial applications in India. Throughout her career, she has received numerous accolades and awards for her exceptional contributions to science and technology.

Profile

Scopus

Education

Dr. Arora pursued her undergraduate studies in Physics, Mathematics, and Electronics from Kurukshetra University, securing an impressive 84%. She then completed her M.Sc. in Physics from IIT Delhi, achieving a CGPA of 9.154/10. Furthering her expertise, she earned an M.Tech. in Applied Optics from IIT Delhi in 2004 with a perfect 10/10 CGPA, receiving the prestigious Gold Medal for academic excellence. Her doctoral research at the Technical University of Darmstadt, Germany, focused on “Design, Realization, and Applications of Dynamically Controllable Bragg Gratings,” earning her the best grade and a Certificate of Excellence in 2007.

Experience

Dr. Arora has a rich professional background, beginning as a Scientific Coworker at the Technical University of Darmstadt in 2008. She joined CSIR-NPL in 2009 as a Scientist and steadily rose through the ranks to become a Senior Principal Scientist in 2021. Throughout her tenure, she has led groundbreaking research projects in integrated optics, atomic frequency standards, and time dissemination. Her leadership at the IST Division has been pivotal in enhancing India’s time synchronization infrastructure, crucial for scientific, commercial, and defense applications.

Research Interests

Dr. Arora’s research primarily revolves around high-precision metrology, integrated optics, atomic clocks, and time dissemination. She has extensively worked on the development of Cesium Fountain Frequency Standards, uncertainty evaluation of time standards, and novel techniques in precision spectroscopy. Her work plays a crucial role in establishing reliable and accurate timekeeping systems in India, which are essential for finance, telecommunications, and space applications. She is also actively engaged in advancing optical and atomic physics methodologies for improving national and global timekeeping standards.

Award

Dr. Arora’s exemplary work has been recognized with several prestigious awards. She was honored with the Haryana Yuva Vigyan Ratna Award by the Government of Haryana in 2017 for her contributions to science and technology. The same year, she received the CSIR-NPL Technology Award. Her dedication as a researcher earned her the Outstanding Reviewer Award from Elsevier in 2018. She was also a recipient of the CSIR Young Scientist Award in 2012 and the URSI Young Scientist Award in 2011. Additionally, she has been awarded fellowships such as the DFG Fellowship (2004-2007) and the DAAD Fellowship in 2003.

Publication Top Note

High-resolution spectroscopy of Holmium Perchlorate: Establishment of a wavelength standard for spectrophotometers, published in Optics Materials (2023), cited by multiple metrology studies.

Indian Standard Time dissemination over the internet: A study on indigenous time synchronization devices, published in MAPAN – Journal of Metrology Society of India (2021), widely referenced in timekeeping research.

Uncertainty evaluation for frequency calibration of Helium Neon Laser Head: Published in MAPAN – Journal of Metrology Society of India (2021), focusing on Monte Carlo simulation techniques.

Detection and processing of fluorescence from cold atoms in Cesium Fountain Primary Frequency Standard: Published in MAPAN – Journal of Metrology Society of India (2020), cited in atomic timekeeping research.

Importance of accurate and traceable time in financial trading: Published in International Journal of Electrical Engineering (2018), referenced in financial market synchronization.

Necessity of Two Time Zones in India: A policy recommendation study published in Current Science (2018), influencing national discussions on time zone adjustments.

Experimental research on atomic frequency standards in India: Published in Asian Journal of Physics (2016), cited by researchers in atomic physics and metrology.

Conclusion

Dr. Poonam Arora’s contributions to time standards, precision metrology, and applied optics have positioned her as a leading scientist in her field. Her work has significantly improved India’s time dissemination systems, impacting a broad spectrum of industries. Through her leadership at CSIR-NPL, she continues to drive advancements in atomic frequency standards, ensuring India remains at the forefront of global timekeeping research. Her dedication to scientific excellence, combined with her extensive publication record and numerous accolades, highlights her invaluable contributions to physics and metrology.

 

 

Mandana Sadat Ghafourian | Biomedical Engineering | Best Researcher Award

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Dr. Mandana Sadat Ghafourian | Biomedical Engineering | Best Researcher Award

Biomedical engineering, Ferdowsi University of Mashhad, Iran

Mandana Sadat Ghafourian is a dedicated and accomplished Biomedical Engineer whose academic journey and research contributions have been focused on cutting-edge fields like Machine Learning, Neuroscience, and Signal Processing. Born in Mashhad, Iran, she pursued her higher education with distinction, ranking first in her Bachelor’s program at Sajjad University, and later earning her Master’s degree at Khajeh Nasir University of Technology in Tehran. She is currently a Ph.D. candidate at Ferdowsi University of Mashhad. Her academic excellence is complemented by a significant research trajectory, where she explores the intersection of artificial intelligence with medical applications, specifically focusing on EEG and ECG signals, epilepsy prediction, and brain signal processing.

Profile

Scopus

Education

Mandana’s academic foundation began with a Bachelor of Science degree in Biomedical Engineering from Sajjad University, where she ranked first among 69 students, reflecting her dedication to excellence. She continued her studies with a Master’s degree in Biomedical Engineering from Khajeh Nasir University of Technology, where she further honed her skills in machine learning and biomedical applications. Her research skills were significantly enhanced through a joint scholarship, allowing her to spend a year conducting doctoral research in Neuroscience at the University of Picardy Jules Verne in France. Currently, she is pursuing her Ph.D. in Biomedical Engineering at Ferdowsi University of Mashhad, where her research focuses on EEG signal processing and the use of deep learning techniques for medical diagnoses.

Experience

Mandana has developed a strong teaching and professional background. As a lecturer at Sajjad University since 2018, she has taught a range of courses, including those on brain signal processing, artificial intelligence, bioelectric phenomena, and hospital medical equipment. Her role as a teacher has expanded to developing curricula and offering workshops on various technical topics such as artificial intelligence applications in healthcare. In addition to her teaching duties, she has also worked as a medical equipment specialist at Mashhad University of Medical Sciences, where she gained hands-on experience in the healthcare and medical device sectors. Her professional experience as a technical supervisor further strengthens her capacity to bridge the gap between theoretical research and real-world medical applications.

Research Interests

Mandana’s primary research interests lie in the application of artificial intelligence and machine learning to biomedical engineering. Her work explores the use of deep learning, reinforcement learning, and other AI techniques to address complex problems in neuroscience and medical diagnostics. Notably, she has contributed significantly to research on epilepsy detection, cancer treatment optimization, and stress control using physiological signals like EEG, ECG, and heart rate. She is particularly interested in the development of AI models that can predict medical conditions and control therapies in real time, such as optimizing warfarin dosages for diabetic patients and predicting seizures based on EEG signal analysis.

Award

Mandana’s dedication and academic excellence have earned her several prestigious awards. She ranked first in her undergraduate program, which led to her admission to the Ph.D. program through the Outstanding Talent pathway. Her recognition continued with her selection as a National Elites Foundation scholar in 2019-2020. Additionally, she received the prestigious Eiffel France Scholarship for advanced research in 2019, which allowed her to further expand her international research experience. Furthermore, Mandana’s contributions to the academic community have been recognized through awards for her research presentations, including the Best Poster Award at the 2nd International Razavi Epilepsy Congress.

Publication Top Note

“Optimizing warfarin dosing in diabetic patients through BERT model and machine learning techniques,” The Journal of Computers in Biology and Medicine, 2025.

“Development of Model Predictive Control by Reinforcement Learning to treat Cancer with Mixed of Chemotherapy and Anti-Angiogenic,” Advances in Hematology and Oncology Research, 2025.

“Detection of Epileptic Seizures Using EEG Signal Processing,” The Neuroscience Journal of Shefaye Khatam, 2018.

“Anxiety Control Using Q-Learning,” The Neuroscience Journal of Shefaye Khatam, 2016.

“Breast Cancer Lesion Detection Using Combination Classifiers Based on Ultrasound and Elastography Images,” Information Technology in Engineering Design.

“Seizure Prediction Based on Analysis of Extracting and Selecting EEG Features using Dominant Amplitude and Frequency Components,” The 2nd International Razavi Epilepsy Congress, Best Poster Award.

Conclusion

Mandana Sadat Ghafourian’s academic and professional journey exemplifies her dedication to the fields of Biomedical Engineering and Artificial Intelligence. With a rich background in education, research, and hands-on experience, she continues to make valuable contributions to the medical field. Her research, which bridges neuroscience and AI, holds significant promise for improving diagnostic and therapeutic processes in healthcare. Through her teaching, research, and professional achievements, Mandana is paving the way for future innovations in medical technologies, particularly in the areas of brain signal processing, machine learning, and medical diagnostics.

Workeneh Negassa | UAV-Assisted Wireless Communication | Best Researcher Award

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Mr. Workeneh Negassa | UAV-Assisted Wireless Communication | Best Researcher Award

Student, Adama Science and Technology, Ethiopia

Workeneh Geleta Negassa is a prominent researcher and Ph.D. candidate in Electronics and Communication Engineering at Adama Science and Technology University, Ethiopia. He is a skilled professional with an extensive background in electronics, communication systems, embedded systems, and signal processing. Throughout his academic and professional journey, he has demonstrated a profound commitment to advancing research in wireless communication, industrial electronics, and UAV-assisted communication networks. His expertise spans several cutting-edge technological domains, which include embedded systems, computer networking, and industrial automation. He has consistently contributed to the field through research, conference presentations, and collaborations with international research teams, gaining recognition for his work in academia and industry.

Profile

Education

Dr. Workeneh Geleta Negassa’s academic journey reflects his commitment to mastering and advancing knowledge in electronics and communication. He began his educational pursuit at Adama University, where he earned his B.Ed. degree in Electrical and Electronics Technology in 2008. His passion for electronics and communication technology led him to pursue a Master of Science in Electronics and Communication Technology at Adama Science and Technology University in 2014. Currently, he is furthering his expertise as a Ph.D. candidate at the same institution, focusing on electronics and communication engineering, particularly in wireless communication systems and UAV-assisted networks.

Experience

Dr. Negassa has held significant academic and leadership positions. Between 2009 and 2012, he worked as a Senior Instructor at Wonji TVET College, where he taught Electrical and Electronics Technology. From 2014 to 2023, he held the position of College Dean at Wonji Polytechnic College. In this role, he was responsible for leading quality training programs, fostering technology transfer, industry collaboration, and supporting youth projects and job creation initiatives. His leadership and academic experience reflect his dedication to educational development and technical advancement in Ethiopia. Additionally, he has shared his expertise by presenting research at several international conferences.

Research Interests

Dr. Negassa’s research interests lie primarily in the fields of wireless communication systems, UAV-assisted wireless communication, and industrial electronics. He is particularly focused on the integration of machine learning techniques with UAV technologies to improve the localization and performance of wireless networks. His expertise also spans embedded systems, including the use of microcontrollers and real-time operating systems, and the application of signal processing techniques for various engineering challenges. Furthermore, his work includes exploring new solutions to enhance the performance and efficiency of indoor localization systems, as well as developing algorithms for medical image processing, particularly in the detection and classification of liver tumors.

Award

Based on the information provided in Workeneh Geleta Negassa’s curriculum vitae, I believe he is a highly suitable candidate for the Best Researcher Award. His extensive background in research, teaching, and industry collaboration demonstrates his commitment to advancing knowledge in the field of electronics, communication, and embedded systems.ty.

Publication Top Note

W. G. Negassa, D. J. Gelmecha, R. S. Singh, and D. S. Rathee, “Hybrid Machine Learning-Based 3-Dimensional UAV Node Localization for UAV-Assisted Wireless Networks,” Cognitive Robotics, 2025, DOI: 10.1016/j.cogr.2025.01.002.

Conclusion

Dr. Workeneh Geleta Negassa has made significant strides in the fields of electronics, communication systems, and embedded systems. His academic background, combined with his extensive professional experience, positions him as a valuable asset to the research community. His ongoing Ph.D. research on UAV-assisted wireless communication systems promises to contribute further to the advancement of this rapidly evolving field. Dr. Negassa’s passion for technology, his leadership in academia, and his commitment to developing practical, cutting-edge solutions continue to inspire students and researchers alike. As he moves forward in his career, he is poised to make even more substantial contributions to both the academic and technological landscapes of Ethiopia and beyond.

Wako Golicha Wako | Environmental Health | Best Researcher Award

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Mr. Wako Golicha Wako | Environmental Health | Best Researcher Award

PhD Researcher, University of Edinburgh, United Kingdom

Dr. Wako Golicha Wako is currently a PhD researcher at the School of Health in Social Sciences at The University of Edinburgh, UK. With a passion for improving public health outcomes in Sub-Saharan Africa, he has made significant contributions to research on maternal and child health, infectious diseases, and health system strengthening. His educational background includes a Master of Public Health (MPH) from Hawassa University, Ethiopia, and a Bachelor of Science in Public Health from the same institution. With extensive work experience as a lecturer, researcher, and public health consultant, he has played a pivotal role in academic and health program evaluations across Ethiopia. His research focuses on the health challenges faced by rural populations in Ethiopia and other parts of Sub-Saharan Africa. His work is aimed at creating evidence-based solutions to improve maternal and child health outcomes and strengthen health systems.

Profile

Orcid

Education

Dr. Wako’s academic journey began at Hawassa University, Ethiopia, where he completed his Bachelor of Science in Public Health in 2012, graduating with a CGPA of 3.79/4. He went on to pursue a Master in Public Health at the same institution, where he excelled academically with a CGPA of 3.94/4. Currently, he is pursuing a PhD in Health in Social Science at The University of Edinburgh, UK. His doctoral research is focused on understanding and addressing public health challenges within the Ethiopian context, particularly in rural and underserved communities.

Experience

Dr. Wako has a wealth of experience in teaching, research, and consultancy within the public health sector. He has worked as an assistant professor at Bule Hora University and Woklite University in Ethiopia, where he lectured on public health topics such as epidemiology, research methods, and health systems. In addition, he has served as a research assistant and consultant for multiple international organizations, including Forcier Consulting LLC and Nutrition International, where he played a key role in conducting research on public health programs. His consultancy work has involved evaluating health interventions aimed at improving maternal and child health, managing communicable diseases, and addressing public health emergencies. Through his work with institutions such as UNICEF and Emory University, Dr. Wako has developed expertise in qualitative and quantitative research methods, contributing significantly to the public health landscape in Ethiopia.

Research Interests

Dr. Wako’s primary research interests include maternal and child health, health system strengthening, and epidemiology. His work focuses on identifying and addressing the public health challenges faced by vulnerable populations in Ethiopia and Sub-Saharan Africa, particularly in rural and marginalized areas. He is particularly interested in neonatal care practices, the impact of maternal education on breastfeeding practices, health system diagnostic delays, and the response to public health emergencies such as the COVID-19 pandemic. Through his research, Dr. Wako seeks to generate evidence that informs policy and practice, aiming to improve health outcomes in the region. He also focuses on the role of community-based health interventions and the integration of health systems in rural Ethiopia.

Award

Dr. Wako’s academic excellence has been recognized through various awards. In 2012, he received a Certificate of Academic Excellence from Hawassa University for ranking first among 55 students in his cohort. This acknowledgment highlights his commitment to high standards in public health education and research. He continues to contribute to the field through his dedication to advancing knowledge and public health practice in Ethiopia and beyond.

Publication Top Note

Wako WG, Beyene BN, Wayessa ZJ, Fikrie A, Amaje E. “Assessment of Neonatal Thermal Cares: Practices and Beliefs among Rural Women in West Guji Zone, South Ethiopia: A Cross-sectional Study.” PLOS Glob Public Health, 2022: 2:e0000568.

Wako WG, Wayessa ZJ, Fikrie A. “Effects of Maternal Education on Early Initiation and Exclusive Breastfeeding Practices in Sub-Saharan Africa: A Secondary Analysis of Demographic and Health Surveys from 2015-2019.” BMJ Open, 2022; 12: e054302.

Wayessa ZJ, Wako WG. “Factors Associated with Knowledge of Health Care Workers Toward COVID‐19 in Health Facilities West Guji Zone, Southern Ethiopia, 2020.” J Edu Health Promot, 2022: 11:43.

Wako WG, Wasie A, Wayessa Z, Fikrie A. “Determinants of Health System Diagnostic Delay of Pulmonary Tuberculosis in Gurage and Siltie Zones, South Ethiopia: A Cross-sectional Study.” BMJ Open, 2021; 11(10):e047986.

Fikrie A, Amaje E, Wako WG. “Social Distancing Practice and Associated Factors in Response to COVID-19 Pandemic at West Guji Zone, Southern Ethiopia, 2021: A Community Based Cross-sectional Study.” PLOS One, 2021; 16(12):e0261065.

Abebaw Wasie Kasahun, Haimanot Abebe Adane, Tadele Girum, Wako WG. “Effects of Scaling Up Family Planning on Maternal Survival in Ethiopia: Spectrum Modeling.” International Journal of Women’s Health, 2021; 13:711–716.

Zelalem Jabessa Wayessa, Girma Tufa Melesse, Elias Amaje Hadona, and Wako WG. “Prevalence of Depressive Symptoms Due to COVID-19 and Associated Factors Among Healthcare Workers in Southern Ethiopia.” SAGE Open Medicine, 2021; 9:1–10.

Conclusion

Dr. Wako Golicha Wako’s career exemplifies a commitment to improving public health through research, teaching, and consultancy. With a strong academic background, valuable professional experience, and a focus on addressing pressing health challenges in Sub-Saharan Africa, particularly Ethiopia, he continues to contribute to the field of public health. His research on neonatal care, maternal health, and health systems has gained recognition and serves as a foundation for ongoing public health improvements. Through his work, Dr. Wako is dedicated to translating research into actionable solutions that can lead to better health outcomes in his region and beyond.

Lei Chen | High pressure flow | Best Researcher Award

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Prof. Lei Chen | High pressure flow | Best Researcher Award

Professor, Xi’an Jiaotong University, China

Lei Chen is a prominent professor and doctoral supervisor at Xi’an Jiaotong University in China, specializing in thermal-fluid science and engineering. With a broad expertise in energy technologies, his research is focused on advancing energy efficiency, enhancing heat transfer systems, and integrating AI into energy solutions. He has earned recognition for his significant contributions to energy science, including being a recipient of the Shaanxi Outstanding Youth Fund. As a leader in his field, he is actively involved in various national and provincial projects, serving as the Executive Director of the Thermal Flow Science and Engineering Innovation Practice Studio and the Interdisciplinary Innovation Platform for Energy and Chemical Engineering. He is also a respected member of technical committees, further establishing his role as an influential figure in the energy sector.

Profile

Scopus

Education

Professor Lei Chen holds a Ph.D. in Thermal Fluid Science and Engineering from Xi’an Jiaotong University, where he also earned his Master of Science in Mechanical Engineering and his Bachelor of Science in Energy and Power Engineering. His educational background has laid a solid foundation for his extensive research career, allowing him to explore a variety of topics within energy systems, fluid dynamics, and thermal management. Over the years, his commitment to higher education has made him an influential mentor, guiding future researchers in the field.

Experience

With over 20 years of experience in academia and research, Professor Chen has held several key positions, demonstrating both leadership and expertise in energy systems. He is the Executive Director of the Thermal Flow Science and Engineering Innovation Practice Studio and the Interdisciplinary Innovation Platform for Energy and Chemical Engineering, where he oversees multiple research initiatives. Additionally, he serves as the Deputy Director of the Xi’an Key Laboratory of Energy Conservation and Low Carbon Technology for Data Centers. Professor Chen has also contributed to numerous high-impact projects, securing funding from national and provincial sources, and engaging in interdisciplinary research with practical implications for energy conservation, sustainability, and low-carbon technologies.

Research Interests

Professor Lei Chen’s research spans a range of topics related to energy systems, focusing on areas such as heat transfer enhancement, fuel cells, lithium batteries, energy efficiency assessments, and artificial intelligence applications in energy technologies. His work involves advanced numerical simulations to study fluid dynamics and heat transfer in various energy systems. He has also made significant contributions to improving energy storage solutions, such as fuel cells and lithium batteries, and has explored the integration of AI into energy Internet technologies. His multidisciplinary approach aims to improve energy system performance and sustainability in the face of global challenges.

Award

Based on the provided information, Lei Chen seems to be a highly qualified and accomplished individual, making him a strong candidate for the Best Researcher Award.

Publication Top Note

Zhang, J., Shen, J., Fang, J., Wang, C., Che, D., Chen, L., “Study on NOx formation and ash characteristics during co-combustion of semi-coke and biomass under O2/CO2 conditions,” Fuel, 2025.

Wang, Y., Zhang, T., Chen, L., Tao, W., “Multi-objective optimization of laser perforated fuel filter parameters based on artificial neural network and genetic algorithm,” Particuology, 2025.

Zhang, Z., Yao, J., Pan, Y., Chen, L., Xie, T., “Strong metal-support interaction induced excellent performance for photo-thermal catalysis methane dry reforming over Ru-cluster-ceria catalyst,” Nano Energy, 2025.

Wang, Y., Wang, Q., Chen, L., Tao, W., “Numerical investigation of performance and multiparameter prediction model of high-pressure fuel filters and cavitation at filtration orifices considering variable fluid properties,” International Journal of Heat and Mass Transfer, 2024.

Conclusion

Professor Lei Chen is an outstanding scholar in the field of thermal-fluid science and engineering. His innovative research has significantly contributed to advancements in energy systems, heat transfer, and sustainability technologies. With numerous accolades in both teaching and research, he continues to shape the future of energy science through his leadership, academic mentorship, and groundbreaking work. His commitment to improving energy efficiency, reducing carbon emissions, and fostering interdisciplinary research positions him as a key figure in the global effort to address energy challenges.

 

 

Ye Dai | Advanced laser processing | Best Researcher Award

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Prof. Dr. Ye Dai | Advanced laser processing | Best Researcher Award

Professor, Shanghai University, China

Ye Dai is a Professor at the Department of Physics, Shanghai University, with a distinguished career in laser physics and ultrafast laser processing. He is recognized for his pioneering work in ultrafast laser micro/nanofabrication technologies, focusing on the creation of 3D self-organized nanogratings and their applications in various domains. Throughout his career, Dai has led significant research projects, including several funded by the National Natural Science Foundation of China (NSFC), to study ultrafast dynamics in laser-induced microstructures. His research has contributed substantially to advancing laser technology, particularly in the areas of nanofabrication, transparent material processing, and laser-induced phenomena.

Profile

Education

Ye Dai completed his M.Sc. in Physics Electronics & Optoelectronics from Shaanxi University of Science and Technology in 2002. He further pursued his academic journey, earning a Ph.D. in Radio Physics from Shanghai University in 2008. His deep academic background in physics laid the foundation for his future work in ultrafast laser processing and nanotechnology. The combination of his robust educational qualifications and hands-on experience has made him a leading figure in the field of laser physics.

Experience

Dai’s academic and professional career has been marked by significant milestones. From 2008 to 2012, he worked as a Lecturer in the Department of Physics at Shanghai University. During this time, he began to establish himself as a scholar in ultrafast laser research. He advanced to the position of Associate Professor in 2012, where he continued his research and played a key role in developing the university’s laser technology research initiatives. In 2014–2015, he was a Visiting Scholar at the Optoelectronics Research Centre (ORC) at the University of Southampton, further expanding his research network and expertise. Since 2020, Dai has been serving as a Professor at Shanghai University and is currently the Vice Dean of the College of Science.

Research Interests

Ye Dai’s research interests primarily revolve around the development of ultrafast laser processing technologies. He established the Ultrafast Laser Processing Lab at Shanghai University, where he investigates the dynamic processes of laser-induced microstructures in materials, especially glasses. A key focus of his work is understanding the ultrafast dynamics and mechanisms of femtosecond and picosecond laser pulses in creating micro/nanostructures. His group is particularly interested in 3D self-organized nanograting formation and its diverse applications. Dai’s work aims to push the boundaries of material science and laser technology to create more efficient and precise fabrication techniques.

Award

Ye Dai appears to be a highly suitable candidate for the Research for Best Researcher Award. His significant contributions to the field of ultrafast laser processing and nanofabrication are reflected through his various prestigious roles and academic qualifications, including his position as a Professor at Shanghai University and his leadership in establishing an ultrafast laser processing lab

Publication Top Note

Zihuai Su, Bingbin Liu, Yulu Zhang, Juan Song, Bin Qian, Wei Liu, Shengzhi Sun, Jianrong Qiu, Ye Dai, Precision processing of Nb-Si alloy via water-jet guided laser: Realization of inhibited-oxidation and small-taper, Optics & Laser Technology, 187, 112853 (2025).

Heng Yao, Diego Pugliese, Matthieu Lancry, and Ye Dai, Ultrafast Laser Direct Writing Nanogratings and their Engineering in Transparent Materials, Laser & Photonics Reviews, 18(9), 2300891 (2024).

Heng Yao, Qiong Xie, Maxime Cavillon, Ye Dai, Matthieu Lancry, Materials roadmap for inscription of nanogratings inside transparent dielectrics using ultrafast lasers, Progress in Materials Science, 142, 101226 (2024).

Juan Song, Hongjian Wang, Xinxiang Huang, Weiyi Yin, Qian Yao, Ye Dai, In-situ study of laser-induced novel ripples formation on SiC surface by an oblique-illumination high-resolution imaging setup, Optics & Laser Technology, 169, 110095 (2024).

Qian Yao, Juan Song, Weiyi Yin, Huaiqiang Shi, Heng Yao, Zihuai Su, and Ye Dai, Optimization of fs + ps double-pulse sequence parameters for laser-assisted chemical etching of microchannels in fused silica, Journal of Physics D: Applied Physics, 56, 265101 (2023).

Ying Sun, Weiyi Yin, Qian Yao, Xiangyu Ren, Juan Song, Ye Dai, Temporal modulation towards femtosecond laser-induced nonlinear ionization process, Optics Letters, 47(23), 6045-6048 (2022).

Wencheng Zhang, Qinxiao Zhai, Juan Song, Kongyu Lou, Yuedong Li, Zhongmin Ou, Quanzhong Zhao, Ye Dai, Manipulation of self-organized nanograting for erasing and rewriting by ultrashort double-pulse sequences irradiation in fused silica, Journal of Physics D, 53, 165106 (2020).

Conclusion

Ye Dai’s career has been marked by his commitment to advancing ultrafast laser technology and its applications in material processing. As a professor and researcher, he continues to push the boundaries of science with his innovative work in laser fabrication. His significant contributions have not only elevated his profile within the academic community but have also provided critical insights into laser-induced microstructural changes in materials. Through his research, Dai has cemented his position as a leader in the field, making lasting impacts on both academic research and practical applications in ultrafast laser processing.

Wenliang Wu | Food Chemistry | Best Researcher Award

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Dr. Wenliang Wu | Food Chemistry | Best Researcher Award

Lecturer | Northwest A&F University | China

Wenliang Wu is a Lecturer at the College of Information Engineering, Northwest A&F University, China. With an academic background in Computer Science and Technology, Wu completed a Ph.D. from Northwestern Polytechnical University in 2022. His research interests primarily focus on unmanned swarm systems, collective intelligence, and evaluation methods for autonomous systems. Wu’s academic journey includes a Master’s degree from Inner Mongolia University and a Bachelor’s degree from Inner Mongolia University of Technology. His current role involves both teaching and leading research in the area of intelligent evaluation of unmanned systems.

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Education

Wenliang Wu’s educational trajectory is rooted in Computer Science and Technology. He began his academic pursuit at Inner Mongolia University of Technology, where he earned his Bachelor’s degree in 2014. Continuing his studies, Wu obtained a Master’s degree in the same field from Inner Mongolia University in 2017. His dedication to the field culminated in a Ph.D. from Northwestern Polytechnical University, which he completed in December 2022. During his Ph.D., Wu specialized in the development of intelligent evaluation models for unmanned swarm systems.

Experience

Dr. Wu’s academic career has progressed steadily, marked by significant research contributions. Since February 2023, he has been a Lecturer at the College of Information Engineering, Northwest A&F University. His primary responsibilities include conducting cutting-edge research on unmanned systems and delivering lectures on related topics. Wu’s research in this field is aimed at improving the intelligence and operational efficiency of autonomous systems, particularly in unmanned swarm technologies. His academic experience is complemented by his leadership role in several research projects, where he has pioneered work on swarm system evaluations and intelligence assessment methodologies.

Research Interests

Dr. Wu’s research interests lie at the intersection of artificial intelligence, autonomous systems, and swarm intelligence. Specifically, he focuses on the development of comprehensive evaluation systems for unmanned swarm intelligence. Wu’s work is largely concerned with methods to assess the collective intelligence of unmanned systems, a crucial element for their successful operation in complex environments. He has been involved in creating models based on the OODA (Observe, Orient, Decide, Act) loop, group extension cloud models, and CRITIC-based evaluation methods. His goal is to develop robust systems that allow for more accurate and reliable performance evaluations for unmanned swarm systems.

Award

Though Wu has not yet received formal academic awards, his work has significantly contributed to the field of unmanned swarm intelligence. His publications in top-tier journals, such as Connection Science and Automation Acta, highlight the recognition of his research within the academic community. Furthermore, his leadership in research projects, including those at the doctoral research stage, demonstrates his growing influence in the field of intelligent systems and swarm technologies.

Publication Top Note

Wu, W., Zhou, X., & Shen, B. (2022). Comprehensive evaluation of the intelligence levels for unmanned swarms based on the collective OODA loop and group extension cloud model. Connection Science, 34(1), 630-651. (Cited by 15 articles).

Shen, B., Wu, W., Yang, G., & Zhou, X. (2023). Intelligent evaluation model and method for unmanned swarm systems based on group OODA. Acta Aeronautica et Astronautica Sinica, 44(14), 328003-1-328003-15. (Cited by 10 articles).

Wu, W., Zhou, X., Shen, B., & Zhao, Y. (2022). Review of evaluation research for swarm robot systems. Acta Automatica Sinica, 48(5), 1153-1172. (Cited by 20 articles).

Wu, W., Wang, C., Tuo, M., & Zhou, X. (2022). An accurate and robust comparison method of intelligence for unmanned swarms based on improved CRITIC and hypothesis test. Proceedings of the 2022 International Conference on Autonomous Unmanned Systems, Xi’an, China. (Cited by 7 articles).

Wu, W., & Zhou, X. (2020). An intelligent evaluation method for the application scenario complexity level of unmanned swarms. Proceedings of the 19th International Conference on Ubiquitous Computing and Communication, Exeter, UK. (Cited by 5 articles).

Conclusion

Dr. Wenliang Wu has made remarkable strides in the field of unmanned swarm systems, with a particular focus on the evaluation and improvement of their intelligence. With a solid educational background and a growing body of influential work, he is emerging as a key figure in the realm of autonomous systems. His research, especially his work on intelligent evaluation models, contributes to the development of smarter and more reliable unmanned technologies. As he continues to push the boundaries of swarm intelligence and autonomous system evaluations, Wu’s work holds the promise of transforming how unmanned systems are deployed and assessed in real-world scenarios.

Yamina Mebdoua Lahmar | Materials sciences | Women Researcher Award

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Dr. Yamina Mebdoua Lahmar | Materials sciences | Women Researcher Award

Research Director | Advanced Technology Development Center | Algeria

Yamina Mebdoua-Lahmar is a prominent researcher and academic in the field of materials science and surface treatment, with a focus on thermal spraying techniques. Currently serving as the Director of Research at the Centre de Développement des Technologies Avancées (CDTA) in Algeria, she has made significant contributions to the development of advanced coatings and surface treatments. Her academic journey spans several decades, during which she has attained advanced degrees and built a distinguished career. Her research interests and leadership have positioned her as an expert in the areas of materials characterization, surface engineering, and applied physics.

Profile

Education

Dr. Mebdoua-Lahmar holds a comprehensive academic background. She obtained her Doctorate in Ceramic Materials and Surface Treatment from the University of Limoges, France, in 2008. Before this, she earned a Magister in Physics, specializing in Astrophysics, from the University of Blida in 1998. Her advanced studies culminated in an Habilitation in Physics from the University of Blida in 2014. Additionally, Dr. Mebdoua-Lahmar completed a Diplôme d’Etudes Supérieures in Physics at the University of Algiers in 1992. She also holds a Baccalaureate in Mathematics from 1987.

Experience

Dr. Mebdoua-Lahmar has an extensive career at CDTA, spanning over two decades. She started as a Research Attaché in 1998 and progressed through the ranks, becoming a Research Director in 2016. Over the years, she has held leadership roles, such as the Director of the “Ionized Media and Laser” Research Division (2012-2015) and Head of the Thermal Spray Team (2013-2020). She currently leads the Thermal Spray Technology Platform at CDTA, overseeing several research projects. Her involvement in numerous projects includes developing coatings resistant to wear and erosion, thermal barrier coatings, and cold spray deposition techniques. Dr. Mebdoua-Lahmar also served as an elected member of the CDTA Scientific Council from 2019 to 2023 and as its President in 2022-2023.

Research Interests

Dr. Mebdoua-Lahmar’s primary research interests lie in surface engineering, specifically the use of thermal spray processes to create protective coatings. Her work covers various applications, from wear-resistant coatings for industrial use to thermal barrier coatings and modeling of deposition processes such as cold spray. Additionally, she has explored the use of advanced materials for corrosion protection and the integration of energetic devices on nonconductive substrates. Her research also extends to numerical studies and modeling of heat transfer during coating formation, as well as the mechanical and electrochemical properties of thermally sprayed materials.

Award

Dr. Yamina Mebdoua-Lahmar, it seems that she is indeed a highly qualified and suitable candidate for the Best Researcher Award. Below is a structured analysis:

Publication Top Note

Rabah Azzoug, Yamina Mebdoua, Fatah Hellal, “Microstructural, Mechanical and Electrochemical Characterization of a Flame Sprayed NiFeCrBSi/WC Cermet Coating,” 21-25, 2022.

R. Azzoug, Y. Mebdoua, F. Hellal, F. Marra, “Analysis of Microstructure, Mechanical Indentation and Corrosive Behavior of a Thermally Sprayed NiFeCrBSi-WC Composite Coating,” Journal of Alloys and Compounds, December 2021, DOI:10.1016/j.jallcom.2021.163505.

O. Sifi, M. Djeghlal, Y. Mebdoua, S. Djeraf, F Hadj-Larbi, “The effect of the solution and aging treatments on the microstructures and microhardness of nickel-based superalloy,” Applied Physics A, 2020, DOI:10.1007/s00339-020-03517-2.

Y. Mebdoua, Y. Fizi, N. Bouhelal, “Cold sprayed copper coating: numerical study of particle impact and coating characterization,” Eur. Phys. J. Appl. Phys., 2016, 74, 24608. DOI:10.1051/epjap/2015150316.

Y. Mebdoua, A. Vardelle, P. Fauchais, “Heat Diffusion in Solidifying Alumina Splat Deposited on Solid Substrate under Plasma sprayed Conditions: Application to Coating Formation,” Defect and Diffusion Forum, 2010.

Y. Mebdoua, A. Vardelle, P. Fauchais, “Numerical Study of Alumina Nucleation Deposited on Steel Substrate under Plasma Spray Conditions,” International Journal of Thermal Sciences, 2010.

S. Djerourou, H. Lahmar, N. Bouhellal, Y. Mebdoua, “Study of Twin Wire Arc Sprayed Zinc/Aluminum Coating on Low carbon Steel Substrate: Application to Corrosion Protection,” Advanced Materials Research, 2013, Vol 685.

Conclusion

Dr. Yamina Mebdoua-Lahmar’s career is marked by significant contributions to the field of materials science, particularly in the area of surface treatments and thermal spraying. Through her leadership at the CDTA, she has advanced numerous groundbreaking projects and contributed to the development of innovative materials with industrial applications. Her academic and professional achievements have established her as a leading expert in the field. Through continuous research, teaching, and active participation in scientific conferences, Dr. Mebdoua-Lahmar remains a pivotal figure in the ongoing evolution of surface treatment technologies and material sciences.

Ramachandran | Machine Learning | Best Researcher Award

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Dr. Ramachandran | Machine Learning | Best Researcher Award

Assistant Professor | Parul institute of Engineering and technology-MCA | India

Dr. Ramachandran P is an esteemed Assistant Professor in the Department of Computer Science at Parul University, Vadodara, Gujarat, with over 11 years of experience in teaching and research. With a robust academic background, he holds a Ph.D. in Computer Science, along with an M.Sc. in Information Technology, an M.Phil. in Computer Science, and a B.Ed. in Computer Science. His passion for technology and innovation has led him to focus on areas such as machine learning, AI, cybersecurity, and software development. He has contributed significantly to the academic community, holding membership in the International Association of Engineers (IAENG) and the Computer Society of India (CSI). His technical expertise spans AWS, Microsoft certifications, Python, MATLAB, and various other cutting-edge technologies.

Profile

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Education

Dr. Ramachandran P’s academic journey reflects his dedication to advancing knowledge in the field of computer science. He completed his Ph.D. in Computer Science and holds multiple degrees, including an M.Sc. in Information Technology, M.Phil. in Computer Science, and B.Ed. in Computer Science. His foundational education began at institutions like Bharathiar University, Periyar University, and Tamilnadu Teacher Education University, shaping his academic trajectory. Throughout his career, Dr. Ramachandran has remained committed to continuous learning, always staying at the forefront of emerging technological trends and tools.

Experience

Dr. Ramachandran has held various academic roles over the years, with his most recent position as Assistant Professor at Parul Institute of Engineering and Technology, Parul University. His professional experience spans teaching, research, and development, including his previous roles at institutions such as KG College of Arts and Science and J.J College of Arts and Science. He has consistently demonstrated leadership in guiding students and colleagues, helping them develop essential technical and research skills. With a strong focus on delivering high-quality education, Dr. Ramachandran has worked with diverse technological platforms, contributing to the growth and development of the institutions where he has taught.

Research Interests

Dr. Ramachandran’s research interests lie primarily in the domains of machine learning, artificial intelligence (AI), cloud computing, and data mining. He has contributed to research on network security, cyber threats, IoT-based solutions, and deep learning techniques for predictive models. His innovative work often involves developing hybrid frameworks to address complex challenges in fields such as health diagnostics, cybersecurity, and real-time data analysis. His published papers and ongoing research focus on enhancing the accuracy and efficiency of machine learning models and exploring new techniques in AI to drive technological advancements.

Award

Dr. Ramachandran has earned recognition for his outstanding contributions to research and education. His work has led to multiple award nominations, including recognition for his work in machine learning and its applications in healthcare. His dedication to research and development in AI and cybersecurity continues to attract attention, and he is nominated for several prestigious awards, including the “Best Researcher Award” at the Cryogenicist Global Awards. His accolades reflect his commitment to advancing knowledge and fostering innovation within the academic and professional communities.

Publication Top Note

“Proactive Detection of Malicious Webpages Using Hybrid Natural Language Processing and Ensemble Learning Techniques”
Journal of Information and Organizational Sciences (2024)

“Proactive Detection of Malicious Webpages Using Hybrid Natural Language Processing and Ensemble Learning Techniques”
Journal of Information and Organizational Sciences (2024-12-18)

“Enhanced Cryptographic Performance and Security Using Optimized Edward-ElGamal Signature Scheme for IoT and Blockchain Applications” International Journal on Smart Sensing and Intelligent Systems (2024-11-10)

“Deep Learning-Based Detection of IoT Botnet Attacks: An Exploration of Residual Networks” International Journal of Safety and Security Engineering (2023)

Conclusion

Dr. Ramachandran P’s contributions to the academic and research fields have been both substantial and impactful. With a diverse range of skills in machine learning, AI, and cybersecurity, he continues to inspire the next generation of technology professionals. His work in enhancing machine learning models and his dedication to improving real-world applications in fields like healthcare and cybersecurity underscore his commitment to innovation. As an educator and researcher, Dr. Ramachandran’s contributions serve as a model for future advancements in technology. His work in AI, particularly in the development of hybrid frameworks and models for improved diagnostic accuracy, showcases his ability to make meaningful changes in both academic and applied research domains. Through his publications, awards, and ongoing efforts in research, Dr. Ramachandran remains a key