Fatih UCUN | Regression and Correlation Analysis | Best Researcher Award

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Prof. Dr. Fatih UCUN | Regression and Correlation Analysis | Best Researcher Award

Suleyman Demirel University | Turkey

Prof. Dr. Fatih Ucun is a distinguished physicist specializing in atomic and molecular physics, with expertise in electron paramagnetic resonance (EPR), nuclear magnetic resonance (NMR), and infrared (IR) spectroscopy. He completed his B.Sc. and M.Sc. in Physics at Atatürk University and earned his Ph.D. from Ondokuz Mayıs University. He is a full professor in the Department of Physics at Suleyman Demirel University in Isparta, Turkey. Prof. Ucun has made significant contributions to computational chemistry, molecular modeling, and quantum mechanics, bridging theoretical insights with practical applications in material science and nanotechnology through pioneering studies on molecular electronic structures and quantum chemical simulations. He has authored 91 publications, cited 883 times, and holds an h-index of 16, reflecting his substantial impact in the field. In addition to his research, he has published four books and serves on editorial boards of scientific journals, demonstrating his leadership and influence in the academic community. His work has advanced the understanding of atomic-level interactions and energy transfer mechanisms, while mentoring future scientists and enriching scientific progress in physical chemistry and computational modeling.

Profiles: Scopus | Google Scholar 

Featured Publications

Ucun, F., Isik, Y. E., & Tiryaki, O. (2025). An approach to description of isotropic hyperfine interaction constants in the fluorinated nitrobenzene and nitrophenol radical anions: DFT calculations vs. experiment. Russian Journal of Physical Chemistry A, 99, 2498–2505.

Yolburun, H., & Ucun, F. (2023). EPR analysis of dinitrobenzoic acid anion radicals. International Journal of Computational and Experimental Science and Technology.

Ucun, F. (2023). EPR analysis of dinitrobenzoic acid anion radicals. International Journal of Computational and Experimental Science and Technology.

Ucun, F., & Alakuş, N. (2022). Enthalpies and activation energies of several gas reactions by intrinsic reaction coordinate (IRC) calculations. El-Cezeri, 9(2), 576–583.

Ucun, F., & Küçük, S. (2022). Triafulvalen, pentafulvalen ve heptafulvalenin katyon ve anyon radikallerinin EPR aşırı ince-yapı yapıları: Bir teorik çalışma. Süleyman Demirel University Faculty of Arts and Science Journal of Science.

BHASKAR A | Survival Analysis and Reliability | Best Researcher Award

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Mr. BHASKAR A | Survival Analysis and Reliability | Best Researcher Award

SRM Institute of Science and Technology (SRMIST) | India

Mr. Bhaskar A is a highly accomplished academic and industry professional with over two decades of experience in mechanical engineering, manufacturing, and Agile methodologies. Currently serving as an Assistant Professor (Selection Grade) and Scrum Master at SRM Institute of Science and Technology (SRMIST), Ramapuram, he has played a pivotal role in integrating Agile practices into engineering education, mentoring teams, and enhancing organizational productivity. His educational journey includes an MBA from Annamalai University, an M.E. in Manufacturing Engineering from Madras Institute of Technology, and a B.E. in Mechanical Engineering from the University of Madras, and he is presently pursuing a part-time Ph.D. in Lean Manufacturing from Anna University. Over his career, he has held positions as an Assistant Professor at several engineering colleges and worked in industry roles including Production Engineer, contributing to process improvements and team management. Dr. Bhaskar has made significant research contributions in lean manufacturing, mechanical properties of materials, and the application of Agile methodologies, with numerous publications in journals and conferences. Beyond research and teaching, he is dedicated to continuous professional development, having completed multiple Faculty Development Programs, workshops, and online courses in project management, digital manufacturing, materials science, and other emerging technologies, reflecting his commitment to advancing knowledge and fostering innovation in engineering education.

Profiles:  Google Scholar | Linked In

Featured Publications

Alexpandian, A. S., Rajesha, M., Loganathan, P., Hariram, V., & [Y.R.]. (2023). Optimization of machining parameters to improve surface quality in the abrasive water jet cutting of AA6351 aluminium alloy. International Journal of Vehicle Structures & Systems, 15(4), 547–551.

Devaraju, A. B. A. (2025). Integrated ERP lean model for quality enhancement and operational excellence in SME based automotive mould manufacturing. Scientific Reports, 15(35979), 1–16.

Jeffrey, V. P. S. S. J. A., Govindaraj, S., Mahesh, R., Bhaskar, A., Arunkumar, K., & [R.]. (2025). Influence of Fe2O3 nanoparticle-infused waste cooking oil biodiesel on the emission, performance, and combustion aspects towards a cleaner environment. Journal of Environmental Nanotechnology, 14(3), 466–476.

Yoganjaneyulu, G., Perumal, V. S., Sivasankaran, S., Annamalai, B., & Niranjan, T. (2025). Strategic method to enhancing the formability of Nitinol foils via micro-incremental sheet forming processes and evaluation of structure–property. Metals and Materials International, 1–15.

Hepsi, B. M. J., Bhaskar, A., Rekha, R. S., & Vasanthi, P. (2024). Wear behavior of hemp-flax-glass fibre hybrid composite material. Advances in Additive Manufacturing Technologies, 75–79.

Kuruba Chandrakala | Machine Learning and Statistics | Best Researcher Award

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Dr. Kuruba Chandrakala | Machine Learning and Statistics | Best Researcher Award

Siddhartha Academy of Higher Education | India

Dr. Kuruba Chandrakala is an emerging researcher in the domains of computer vision, deep learning, and medical image processing, currently serving as Assistant Professor (Selection Grade) in the CSE department at Siddhartha Academy of Higher Education, Vijayawada. She earned her Ph.D. from NIT Tiruchirappalli, preceded by M.Tech in Computer Science and Engineering with distinction from JNTU Kakinada and B.Tech in the same discipline from JNTU Anantapur. She has qualified both NET and APSET examinations. Her professional trajectory includes roles as Head of Department (CSE-AIML) at Vignan’s Nirula Institute of Technology & Science for Women and previous teaching appointments at VNITSW and SITAM, along with industry experience as a System Engineer with Tata Consultancy Services. Her publication record comprises five Scopus indexed papers, four of which are in SCIE journals, two IEEE conference papers, and one book chapter; she also holds one patent. Her Scopus metrics include an h-index of 4, 10 documents, and 150 citations. Her research has addressed areas such as diabetic retinopathy segmentation, robust blood vessel detection, and image enhancement through deep learning architectures. She teaches courses including Deep Learning, Machine Learning, Big Data Analytics, Cloud Computing, and programming in C, C++, Java, and Python. She has earned numerous certifications from NPTEL, Coursera, Microsoft, IBM, and Wipro and received awards such as the NPTEL Discipline Star and Wipro Project Excellence Award. Her leadership and mentoring roles include serving as a mentor for Wipro TalentNext, nodal officer for Microsoft Upskilling and APSCHE virtual internship programs, and coordinator for various hackathons. She is a life member of professional bodies such as CSI, ISTE, IAENG, and IET, and has delivered several invited and guest lectures, contributing significantly to academic excellence and research advancement.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Chandrakala, K., & Gopalan, N. P. (2025). 3DECNN: A novel method for segmentation of diabetic retinopathy in retinal fundus images using 3D-edge CNN. Neural Computing and Applications.

Kuruba, C., Sharmila, S. K., Mounika, V., Aswini, D., & Poojitha, G. (2023). Three layered security model to prevent credit card fraud using LBPH and CNN-ResNet architecture. International Conference on Hybrid Intelligent Systems, 422–428.

Dharmaiah, K., Mebarek-Oudina, F., Sreenivasa Kumar, M., & Chandra Kala. (2023). Nuclear reactor application on Jeffrey fluid flow with Falkner-Skan factor, Brownian and thermophoresis, non-linear thermal radiation impacts past a wedge. Journal of the Indian Chemical Society, 100(2), 117.

Kuruba, C., & Gopalan, N. P. (2023). Robust blood vessel detection with image enhancement using relative intensity order transformation and deep learning. Biomedical Signal Processing and Control, 86, 105195.

Kuruba, C., Pushpalatha, N., Ramu, G., Suneetha, I., Kumar, M. R., & Harish, P. (2023). Data mining and deep learning-based hybrid health care application. Applied Nanoscience, 13(3), 2431–2437.

Yufeng Jiang | Statistical Applications in Engineering | Best Researcher Award

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Assoc Prof. Dr. Yufeng Jiang | Statistical Applications in Engineering | Best Researcher Award

Ocean University of China | China

Assoc Prof. Dr. Yufeng Jiang is an Associate Professor at the Ocean University of China, specializing in the health monitoring and safety assessment of offshore and marine engineering structures. With a strong academic foundation from the Ocean University of China, he has dedicated his career to advancing intelligent damage diagnosis methods that can directly utilize incomplete information while maintaining high noise robustness. He innovatively developed an iterative two-stage damage identification methodology capable of simultaneously locating structural damage and assessing its severity. Dr. Jiang has designed a hardware network of fiber optic sensors for condition monitoring of deepwater pressure-resistant subsea structures and created an intelligent structural health monitoring and early warning system, which has been successfully applied in a 500-meter deep-sea mixed-transport system demonstration project. His research has led to 20 Documents , 10 patents, and collaboration on three major research projects, resulting in a citation count of 111 and an h-index of 6, reflecting the significant impact of his work. Additionally, he has contributed to two consultancy projects and maintained collaborations across multiple institutions, consistently translating innovative research into practical engineering applications. Dr. Jiang continues to advance the field of marine structural safety with a focus on applied intelligence and robust monitoring solutions.

Profiles: Scopus  | Orcid

Featured Publications

Liu, Y., Wang, S., Jiang, Y., & Du, J. (2025). A spatial deformation reconstruction method of deep-sea mining riser from sparse inclination measurements. Ocean Engineering.

Wang, C., Luo, D., Guo, Y., Zheng, Z., Jiang, Y., & Du, J. (2025). A novel stochastic model updating method for offshore platforms based on Kriging model with active learning. Ocean Engineering.

Jiang, Y., Ma, C., Wang, S., & Li, Y. (2024). A novel evolutionary algorithm for structural model updating with a hybrid initialization and multi-stage update strategy. Ocean Engineering.

Jiang, Y., Liu, Y., Wang, S., & Rakicevic, Z. (2024). Structural damage classification in offshore structures under environmental variations and measured noises using linear discrimination analysis. Structural Control and Health Monitoring.

Liu, Y., Jiang, Y., Zhao, H., Wang, S., & Han, J. (2023). Experimental investigation on vortex-induced vibration characteristics of a segmented free-hanging flexible riser. Ocean Engineering.

Tushar Bhoite | Bayesian Networks and Decision Theory | Best Researcher Award

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Dr. Tushar Bhoite | Bayesian Networks and Decision Theory | Best Researcher Award

Dr. Tushar Bhoite | MES’s Wadia College of Engineering | India

Dr. Tushar Devidas Bhoite, Ph.D. in Mechanical Technology, M.E. in Machine Design, with over sixteen years of professional experience (including twelve in the automobile industry and four in academics), is a leading researcher and practitioner in integrating advanced IT technologies in auto-component manufacturing. His research interests encompass Industry 4.0, Industrial Internet of Things (IIoT), Digital Twin systems, Generative AI, predictive maintenance, neural and Bayesian networks, real-time monitoring, optimization and efficiency improvements in production environments. To date, he has authored 6 international journal papers and 3 international conference papers, co-authored 2 textbooks, and filed 2 patents, contributing to both theoretical and applied advancements. His master’s project, awarded from RGSTC Mumbai, stands as a landmark in his research portfolio, he has an h-index of 1 and over 1 citations as per his Scopus profile, reflecting strong scholarly impact. In his industrial roles, Dr. Bhoite has successfully led IOT implementations in assembly and press shops, improved Overall Equipment Effectiveness, standardized work systems, deployed TPM and Kaizen methodologies, and developed innovative solutions such as a wet-waste treatment machine. He currently serves as Assistant Professor in Automation & Robotics Engineering at MES’s Wadia College of Engineering, Pune, and continues consulting in production efficiency, resource optimization, and technology integration in manufacturing enterprises.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Bhoite, T. D., Pawar, P. M., & Gaikwad, B. D. FEA based study of effect of radial variation of outer link in a typical roller chain link assembly. International Journal of Mechanical and Industrial Engineering, 1, 65–70.

Bhoite, T. D., & Buktar, R. B. (2025). Productivity enhancement in Indian auto component manufacturing supply chain with IoT using neural networks. Production, 35, e20240047.

Bhoite, T. D., Buktar, R. B., Mahalle, P. N., Khond, M. P., Pise, G. S., & More, Y. Y. (2025). Productivity enhancement in the Indian auto component manufacturing supply chain through IoT, digital twins with generative AI, and stacked encoder-enhanced neural networks. Operations Research Forum, 6(4), 143.

Bhoite, D. T., & Buktar, R. (2025). An investigation into revolutionizing auto component manufacturing: An IoT-based approach for improved productivity and waste elimination. Journal of Information Systems Engineering and Management, 10(9s), 409–429.

Bhoite, D. T., Buktar, R., & Kannukkadan, G. (2024). Leveraging IoT in auto component manufacturing to monitor surface roughness and tool temperature. Journal of Electrical Systems, 20(2s), 563–574.*

Ching Chih Tsai | Fuzzy Statistics and Uncertainty Modelling | Best Researcher Award

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Prof. Ching Chih Tsai | Fuzzy Statistics and Uncertainty Modelling | Best Researcher Award

Prof. Ching Chih Tsai |  National Chung Hsing University | Taiwan

Prof. Ching Chih Tsai is a distinguished academic in electrical engineering and control systems, currently serving as a Life Distinguished Professor at the Department of Electrical Engineering, National Chung Hsing University (NCHU), Taiwan. He earned his Ph.D. from Northwestern University in 1991. Dr. Tsai has held significant leadership roles, including serving as the President of the Chinese Automatic Control Society (CACS), the Robotics Society of Taiwan (RST), and the International Fuzzy Systems Association (IFSA). He has also been a Board of Governors member of IEEE Systems, Man, and Cybernetics Society (SMCS) and is currently the Dean of the College of Electrical Engineering and Computer Science at NCHU. An IEEE Fellow, his research focuses on intelligent control systems, mobile robotics, and automation intelligence. Dr. Tsai has published over 700 technical articles, with more than 20 in the International Journal of Fuzzy Systems since 2005. His recent work includes a 2025 paper on intelligent adaptive formation control for multi-quadrotors, introducing a hybrid controller combining Output Recurrent Fuzzy Broad Learning Systems (ORFBLS), reinforcement learning, and adaptive backstepping sliding mode control. According to Scopus, he has an h-index of 29, with 3,902 citations from 272 documents.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Rospawan, A., Tsai, C.-C., & Hung, C.-C. (2025). Two-layer intelligent learning control using output recurrent fuzzy neural long short-term memory broad learning system with RMSprop. IEEE Access.

Tsai, C.-C., Hung, C.-C., Mao, C.-F., Wu, H.-S., & Chen, C.-H. (2025). Fuzzy neural LSTM-RBLS for fractional-order PID sliding-mode motion control of autonomous mobile robots with four ISID wheels. International Journal of Fuzzy Systems.

Tsai, C.-C., Mao, C.-F., & Hussain, K. (2025). Intelligent adaptive formation control using ORFBLS and reinforcement learning for uncertain tilting multi-quadrotors. International Journal of Fuzzy Systems. =

Rospawan, A., Tsai, C.-C., & Hung, C.-C. (2025). Intelligent MIMO ORFBLS-based setpoint tracking control with its application to temperature control of an industrial extrusion barrel. International Journal of Fuzzy Systems.

Tsai, C.-C., Huang, H.-C., Chen, H.-Y., Hung, C.-C., & Chen, S.-T. (2024). Intelligent collision-free formation control of ball-riding robots using output recurrent broad learning in industrial cyber-physical systems. IEEE Transactions on Industrial Cyber-Physical Systems.

Edward Gartay Gar | Multivariate Statistical Analysis | Best Researcher Award

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Mr. Edward Gartay Gar | Multivariate Statistical Analysis | Best Researcher Award

Mr. Edward Gartay Gar | University of Cape Coast | Ghana

Mr. Edward Gartay Gar, B.Sc., M.Phil. Economics Candidate, is a results-driven economist with a strong foundation in leadership, financial literacy, data analysis, and strategic management. Hailing from Monrovia, Liberia, Gar completed his BSc in Economics from William V.S. Tubman University and is currently pursuing an MPhil in Philosophy in Economics Studies at the University of Cape Coast, Ghana. Over the years, he has built extensive expertise in research, administration, and professional engagement with both private and public sector institutions. His international exposure includes specialized training programs in Nigeria, Ghana, and Liberia, reflecting his commitment to global economic perspectives and youth empowerment. Gar has demonstrated strong interpersonal and leadership skills, effectively supervising teams, managing projects, and mentoring students. His core competencies lie in program planning, data-driven decision-making, and sustainable economic development, emphasizing evidence-based interventions that contribute to institutional efficiency and societal progress.

Profile: Google Scholar

Featured Publication

Gar, E. G., Askandir, I., & Turzin, J. K. (2024). The magnitude and risk factors for concurrent anthropometric and nutritional deficiency among children aged 6 to 59 months in Liberia: A multi-level analysis.

Haifa Jammeli | Operations Research and Statistical Optimization | Best Researcher Award

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Dr. Haifa Jammeli | Operations Research and Statistical Optimization | Best Researcher Award

Normasys | France

Dr. Haifa Jammeli is a research fellow at the Institut Supérieur de Gestion de Tunis, specializing in business computing and operations research. She holds a PhD from the Higher Institute of Management in Tunisia and a Master’s degree in Logistics and Transportation Sciences from the Higher Institute of Logistics and Transportation, Sousse University. Her academic and professional journey spans over a decade, with significant contributions to supply chain optimization, AI in logistics, and sustainable urban planning. She is a part-time instructor at Paris Nanterre University and NEOMA Business School, teaching courses in supply chain management, operations research, data analysis, and IT project management. Her research focuses on optimizing transportation routes for COVID-19 patients and cash logistics using tools like CPLEX, QGIS, and Python, and she has developed AI models to forecast urban solid waste generation and propose green logistics solutions for household waste collection. With over 70 citations across nine publications, her work has been presented at international conferences and published in journals such as IEEE Transactions on Engineering Management and Annals of Operations Research. Her h-index is 10, reflecting both productivity and impact in her field. She has received awards including the Perficio Award for Best Woman Entrepreneur of the Year and was a finalist for the IFROS Prize for Operational Research in Development. Fluent in English, French, and Arabic, she combines strong technical skills (CPLEX, MATLAB, Python, R, SQL, QGIS) with experience in teaching, project leadership, and applying AI-based decision models to real‐world sustainability challenges.

Profiles: Scopus | Orcid

Featured Publications

Alaya, H., Jammeli, H., Ben Abdelaziz, F., Masmoudi, M., & Verny, J. (2024). Sustainable logistics for transfer of COVID-19 patients: Lesson learned from France. International Transactions in Operational Research.

Jammeli, H., & Verny, J. (2024). A multi-objective model for two-level distribution system in the city of Paris. Annals of Operations Research. (Accepted for publication)

Jammeli, H., Khefacha, A., Sellei, B., & Verny, J. (2023, October 18–21). The impact of AI tools in education environment. In 2023 IEEE ASEE Frontiers in Education Conference, College Station, Texas.

Jammeli, H., Alaya, H., & Verny, J. (2023, October 23–25). An analysis of the role of the Internet of Things and sensor technologies in optimizing waste management in the city of Sousse, Tunisia . World Recycling Convention, Madrid, Spain.

Jammeli, H., & Verny, J. (2022). A literature review for green smart home delivery problem in urban environments. In 2022 International Conference on Decision Aid Sciences and Applications (DASA) (pp. 756–760). IEEE.

Kai Wang | Statistical Data Visualization | Best Researcher Award

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Assoc Prof. Dr. Kai Wang | Statistical Data Visualization | Best Researcher Award

Shandong First Medical University | China

Assoc Prof. Dr. Kai Wang is an Associate Professor at the State Key Laboratory of Advanced Drug Delivery and Release Systems, School of Pharmaceutical Sciences & Institute of Materia Medica, Shandong First Medical University, China, whose work bridges chemistry, biology, and medicine. His research focuses on the design of boronic acid–based spectroscopic probes for glucose sensing and their application in fluorescence detection and bioimaging, as well as glycobiology studies that explore the therapeutic and diagnostic potential of saccharides in drug development and disease treatment. Dr. Wang has developed several innovative fluorescent probes that achieve high sensitivity and selectivity in imaging cellular glucose in live cells and zebrafish, contributing to the understanding of cellular glucose homeostasis, ROS signaling, and the interplay between diabetes and depression. He collaborates with renowned researchers worldwide, including Tony D. James, Zhongnan Wu, Shaojie Zhang, and Meng Meng, and maintains active membership in the Chinese Chemical Society and the Chinese Society of Biophysics. he has 1 document, 1 citation, and an h-index of 1, reflecting the growing international recognition of his contributions. His goal is to provide novel molecular tools and strategies for disease diagnosis, innovative drug design, and translational medicine.

Profiles : Scopus | Orcid

Featured Publications

“Reversible Recognition-Based Boronic Acid Probes for Glucose Detection in Live Cells and Zebrafish”

“Biomimetic Analysis of Neurotransmitters for Disease Diagnosis through Light‐Driven Nanozyme Sensor Array and Machine Learning”

“Synthesis of Diboronic Acid-Based Fluorescent Probes for the Sensitive Detection of Glucose in Aqueous Media and Biological Matrices”

“A DNA nanoscaffold-based electrochemical assay for sensitive determination of O-GlcNAc transferase (OGT) activity and its application in cell-permeable OGT inhibitors screening”

“A glucose-rich heteropolysaccharide from Marsdenia tenacissima (Roxb.) Wight et Arn. and its zinc-modified complex enhance immunoregulation by regulating TLR4-Myd88-NF-κB pathway”

Ahmed A. Ahmed | Regression and Correlation Analysis | Best Researcher Award

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Assoc Prof. Dr. Ahmed A. Ahmed | Regression and Correlation Analysis | Best Researcher Award

Mustansiriyah University | Iraq

Dr. Ahmed A. Ahmed, Ph.D, is a distinguished faculty member in the Civil Engineering Department at Mustansiriyah University, Baghdad, Iraq, with a robust research profile emphasizing new and advanced infrastructure materials, durability of engineering materials, infrastructure sustainability, green building materials, material characterization, corrosion and carbonation assessment, microstructure analysis, and evaluation of concrete deterioration processes and mechanisms. With an h-index of 5, 70 citations, and a ResearchGate score of 83.5, Dr. Ahmed has contributed extensively to the field through numerous high-impact publications, including studies on corrosion resistance of calcium sulfoaluminate cementitious systems, reliability of chloride testing in cementitious systems, and experimental investigations on reinforcing steel behavior under corrosive conditions. Since 2012, he has served as a faculty member at Mustansiriyah University and held leadership roles such as Head of the Training and Development Unit in the Continuing Education Branch and active membership in professional societies including the American Concrete Institute, American Society of Civil Engineers, Iraqi Academic Syndicate, Iraqi Engineers Union, and Iraqi Teachers Union. Dr. Ahmed earned his Ph.D. in Infrastructure Materials with a minor in Statistics from Oregon State University and holds multiple advanced teaching certificates and engineering degrees. He has also presented at international conventions and workshops across the United States and Malaysia, highlighting his commitment to research excellence, pedagogy, and professional development in civil engineering.

Profiles:  Orcid | Scopus

Featured Publications

“Assessing the Impact of Graphene Nanoplatelets Aggregates on the Performance Characteristics of Cement-Based Materials”

“Performance Evaluation of Concrete Masonry Unit Mixtures Incorporating Citric Acid-Treated Corn Stover Ash and Alkalinized Corn Stover Fibers”

“Evaluating the Characteristics of Fibrous Pure Gypsum Containing Chopped Carbon Fiber (CCF)”

“Evaluating the performance of thermomechanically beneficiated fly ash blended mortar”

“Reliability of chloride testing results in cementitious systems containing admixed chlorides”