Ruchi singh Parihar | Biostatistics and Epidemiology | Best Researcher Award

Assist Prof. Dr. Ruchi singh Parihar | Biostatistics and Epidemiology | Best Researcher Award

Christ University | India

Assist Prof. Dr. Ruchi Singh Parihar is a distinguished climate scientist and Assistant Professor in the Department of Statistics and Data Science at CHRIST (Deemed to be University), Bangalore, whose research embodies a unique integration of climate science, epidemiology, and data-driven modeling. With a Ph.D. in Climate Change and Health jointly awarded by IIT Delhi and Graphic Era University, her scholarly journey reflects a deep commitment to understanding the nexus between climate variability, disease transmission, and human health. Dr. Parihar’s expertise spans climate and atmospheric modeling, remote sensing, GIS applications, numerical simulations, and environmental health risk assessment, focusing particularly on vector-borne diseases such as malaria. Her according to Scopus includes more than 36 peer-reviewed publications, accumulating over 30 citations and an h-index of 3, with studies featured in prestigious journals such as Nature Scientific Reports, GeoHealth, and the International Journal of Biometeorology. She has held research and visiting positions at globally renowned institutions, including the Institute for Basic Science (IBS), South Korea, and the International Centre for Theoretical Physics (ICTP), Italy, where she continues as an Associate. Recognized with several international Travel and Research Grants from organizations like NSF (USA), UNESCO/IAEA, and Rutgers University, Dr. Parihar actively contributes to international scientific dialogues on climate and health through presentations at major conferences including AGU, EGU, and Gordon Research Conferences. Her memberships in leading professional societies such as AGU, EGU, AOGS, ISNTD, and AWIS highlight her active role in advancing collaborative global science. Dr. Parihar’s pioneering contributions lie in her ability to combine statistical modeling, climate projections, and epidemiological simulations to forecast disease transmission patterns under future climate scenarios, thereby influencing both academic research and public health policy on a global scale.

Profiles: Scopus Google Scholar 

Featured Publications

Bal, P. K., Kumar, D. S., Parihar, R. S., & Saini, A. (2025). Changing climate and its impacts on the dynamics of future malaria transmission over certain endemic regions in India. Scientific Reports, 15(1), 35412.

Parihar, C. M. Q. D. R. S. (2025). Women, health, and the climate emergency. American Journal of Biomedical Science and Research.

Parihar, R. S. (2025). Climate variability and its impact on vector-borne diseases: Using numerical/statistical modeling. In IntechOpen.

Franzke, C. L. E., & Parihar, R. S. (2025). Time of emergence and future projections of extremes of malaria infections in Africa. GeoHealth, 9(6), e2025GH001356.

Franzke, C. L. E., & Parihar, R. S. (2025). Time of emergence and future projections of extremes of malaria transmission dynamics in Africa region. European Geosciences Union (EGU25-2188), Vienna, Austria.

Guo Tian | Machine Learning and Statistics | Best Researcher Award

Assoc Prof. Dr. Guo Tian | Machine Learning and Statistics | Best Researcher Award

Tsinghua University | China

Assoc Prof. Dr. Guo Tian is an accomplished young chemical engineer whose research lies at the frontier of sustainable catalysis and CO₂/CO conversion. He earned his Bachelor’s degree in Chemical Engineering under Prof. Xuezhi Duan at the East China University of Science and Technology and pursued his doctoral studies in Chemical Engineering at Tsinghua University under the guidance of Prof. Fei Wei. Following his doctoral training, he joined Southwest Jiaotong University as an Associate Professor and Principal Investigator. At only twenty-five years of age, Guo has led pioneering work on high-pressure thermo-catalytic systems, including the design of a reactor capable of stable operation at up to 60 bar integrated with surface-enhanced infrared absorption spectroscopy (SEIRAS) for in-situ monitoring of reaction intermediates. His studies have revealed critical mechanistic pathways in CO/CO₂ conversion using bifunctional catalysts, identifying oxygenate intermediates as key to improving the traditional methanol-to-hydrocarbons (MTH) mechanism. Drawing inspiration from biological systems, he has advanced the concept of bio-inspired multifunctional catalysts and introduced the innovative idea of “catalytic shunt” strategies to enhance selectivity and efficiency. Combining experimental research with density-functional theory (DFT) and micromodel simulations, his work bridges molecular-level understanding with reactor-scale engineering. Dr. Tian has authored numerous influential publications in high-impact journals such as Nature Sustainability, Nature Communications, ACS Catalysis, and the Journal of the American Chemical Society. Notable among these are “Efficient syngas conversion via catalytic shunt” (Nature Sustainability), and “Upgrading CO₂ to sustainable aromatics via perovskite-mediated tandem catalysis” (Nature Communications). According to his Scopus profile, he has authored 14 documents, accumulated around 297 citations, and holds an h-index of 9, reflecting a strong and growing impact in the field. His expertise includes thermochemical measurement and data analysis, catalytic materials design, reactor and reaction-system development, in-situ spectroscopy (SEM, XRD, XPS, XAS), and DFT-based theoretical modeling. Integrating theory, advanced characterization, and engineering innovation, Guo Tian’s vision focuses on transforming CO₂ and CO into high-value sustainable fuels such as aviation fuel components, contributing to global carbon-neutral energy goals. Through his scientific rigor, leadership, and creativity, he has rapidly emerged as a rising star in heterogeneous catalysis and sustainable chemical engineering.

Profiles: Scopus Google Scholar Orcid

Featured Publications

M. Zhao, Q. Wu, X. Chen, H. Xiong, G. Tian, L. Yan, F. Xiao, & F. Wei. (2025). Entropy-governed zeolite intergrowth. Journal of the American Chemical Society.

Z. Wang, X. Liu, G. Tian, Z. Wang, L. Li, F. Lu, Y. Yu, Z. Li, F. Wei, & C. Zhang. (2025). Research advances in coal-based syngas to aromatics technology. Clean Energy, 9(5), 136–152.

J. He, G. Tian, D. Liao, Z. Li, Y. Cui, F. Wei, C. Zeng, & C. Zhang. (2025). Mechanistic insights into methanol conversion and methanol-mediated tandem catalysis toward hydrocarbons. Journal of Energy Chemistry.

H. Xiong, Y. C. Wang, X. Liang, M. Zhao, G. Tian, G. Wang, L. Gu, & X. Chen. (2025). In situ quantitative imaging of nonuniformly distributed molecules in zeolites. Journal of the American Chemical Society, 147(32), 28965–28972.

Z. Li, J. Chen, G. Xu, Z. Tang, X. Liang, G. Tian, F. Lu, Y. Yu, Y. Wen, & J. Yang. (2025). Constructing three-dimensional covalent organic framework with aea topology and flattened spherical cages. Chemistry of Materials, 37(5), 1942–1948.

Fatih UCUN | Regression and Correlation Analysis | Best Researcher Award

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.

Oleg Selyugin | Big Data and Statistical Analytics | Big Data Analytics Award

Dr. Oleg Selyugin | Big Data and Statistical Analytics | Big Data Analytics Award

Joint Institute for Nuclear Research | Russia

Dr. Oleg Selyugin is a Russian empirical and theoretical physicist with a distinguished career in high-energy hadron scattering and the structure of hadrons. After completing his studies at the Physics Department of Moscow State University, he joined the Joint Institute for Nuclear Research (JINR), first as a probationer and researcher at the Laboratory of Nuclear Problems, and later at the Bogoliubov Theoretical Laboratory (BTL), where he now serves as a leading scientist. At BTL, he earned his Ph.D. with the thesis “High energy elastic hadron-hadron scattering in a wide momentum transfer region,” and later obtained his Doctor of Physics and Mathematics degree with the thesis “The structure of high-energy amplitude of the elastic hadron-hadron scattering in the diffraction region.” Dr Selyugin has been recognized with multiple International Prizes of JINR for his outstanding contributions to polaron physics, hadron physics, and high-energy physics. His primary research interests include the structure of hadrons (PDFs, GPDs, form-factors), phenomenology of high-energy physics (differential cross sections, spin phenomena), models of extra dimensions (d-brane gravity), and nonlinear effects. He has been actively involved in interpreting experimental results from the CERN LHC, particularly the TOTEM and ATLAS Collaborations. His theoretical work integrates electromagnetic and gravitational form-factors derived from novel t-dependent GPDs, as well as soft and cross-even pomeron contributions, within dispersion-relation-based frameworks. With over 180 scientific papers, Dr Selyugin has made a profound and lasting impact on the understanding of elastic hadron scattering at high energies. Although specific bibliometric indicators such as 17 h-index, 78 documents, and 815 citations vary across databases, his scientific influence is widely recognized within the international physics community. He continues his pioneering research at JINR in Dubna, Russia.

Profiles: Scopus | Orcid

Featured Publications

Selyugin, O. V. (2024). Unified description of elastic hadron scattering at low and high energies. Physics of Atomic Nuclei, 87(S2), S349–S362.

Yufeng Jiang | Statistical Applications in Engineering | Best Researcher Award

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.

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

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.

Seyed Abolfazl Hosseini | Statistical Modeling and Simulation | Best Researcher Award

Dr. Seyed Abolfazl Hosseini | Statistical Modeling and Simulation | Best Researcher Award

Dr. Seyed Abolfazl Hosseini | Islamic Azad University | Iran

Dr. Seyed Abolfazl Hosseini is an accomplished electrical engineer and academic whose work seamlessly integrates communications systems, signal processing, machine learning, and remote sensing. He earned his Ph.D. in Communications Systems Engineering from Tarbiat Modares University, following an M.Sc. from K. N. Toosi University and a B.Sc. in Control Engineering from Sharif University of Technology. Over his academic career, he has held leadership roles including Dean of the Electrical & Electronics Research Centre, head of the Communications Engineering Department, and overseen more than 35 M.Sc. theses and 5 Ph.D. dissertations. According to his publication record encompasses more than 5 documents, and his works have been cited over 18 times, with an h-index of 3. He has published in top journals on topics such as MIMO-UFMC system optimization, hyperspectral image classification, blind watermarking, and nonparametric density estimation. Beyond research, he has directed industry projects in IoT, AI, surveillance, and power systems, and contributed to drafting technical standards for electricity markets. Dr. Hosseini is proficient in MATLAB, Python, and advanced mathematics including stochastic processes, linear algebra, fractal theory, and graph theory. He continues to blend theory with practice, driving innovation and teaching the next generation of engineers.

Profiles: Scopus Orcid | ResearchGate

Featured Publications

Hassan Abdollahpour, H., Hosseini, S. A., Raeisi, N., & Azam, F. 3D geometry modeling method for MIMO communication systems using correlation coefficients. Journal of Computer Networks and Communications.

Aghamiri, H. R., Hosseini, S. A., Green, J. R., & Oommen, B. J. Nonparametric probability density function estimation using the Padé approximation. Algorithms.

Asgharnia, M., Hosseini, S. A., Shahzadi, A., Ghazi-Maghrebi, S., & Shaghaghi Kandovan, R. Optimization framework for user clustering, beamforming design and power allocation in MIMO-UFMC systems. IEEE Access.

Khalili, F., Razzazi, F., & Hosseini, S. A. Registration of remote sensing images by the combination of complex nonlinear diffusion and phase congruency attributes. Journal of the Indian Society of Remote Sensing.

Hosseini, S. A., et al. A simple method to prepare and characterize optical fork-shaped diffraction gratings for generation of orbital angular momentum beams. Journal of Optics.

Edward Gartay Gar | Multivariate Statistical Analysis | Best Researcher Award

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.

Xhavit Islami | Econometrics and Statistical Economics | Best Researcher Award

Assist Prof. Dr. Xhavit Islami | Econometrics and Statistical Economics | Best Researcher Award

AAB College | Albania

Assist Prof. Dr. Xhavit Islami is a leading academic in Management and Strategic Management at the Faculty of Economics, AAB College, Republic of Kosovo. He earned his PhD in Organizational Sciences and Management from the University of “Ss. Cyril and Methodius” in North Macedonia and has since built a strong record of research and scholarly contributions. Professor Islami has completed 35 research projects and is currently engaged in five ongoing projects, demonstrating his active involvement in advancing knowledge in management, strategic decision-making, human resource management, and supply chain management. He has published 16 articles in high-impact, Scopus-indexed journals and authored two books, reflecting his commitment to rigorous scholarship. His research work has earned him a Scopus h-index of 4 with 122 citations, highlighting the influence of his publications within the international academic community. He has also participated in five consultancy and industry-sponsored projects, bridging the gap between theory and practice. Professor Islami has collaborated on significant initiatives, including the “EDU-LAB Horizon” Project (2025–2027), and serves on the Scientific Committee of AAB College. His studies focus on innovative strategies, organizational performance, and the integration of artificial intelligence in management practices, providing practical insights for businesses and policymakers. Through his research, he has contributed to the understanding of competitive advantage, sustainable growth, and organizational effectiveness. Professor Islami maintains active professional profiles on Scopus, ORCID, ResearchGate, SSRN, and Academia.edu, ensuring his work is accessible and widely recognized. His scholarly achievements, combined with his ongoing research and industry collaborations, position him as a prominent figure in management and strategic studies, making him a highly deserving candidate for the Best Researcher Award.

Profiles: Scopus Google ScholarOrcid

Featured Publications

“When and How Does Innovation Augment the Effect of HRM on SME Performance?”

“Artificial intelligence and value-based strategy: a literature review and future research directions”

“Lean manufacturing and firms’ financial performance: the role of strategic supplier partnership and information sharing”

“Does competitive strategy moderate the linkage between HRM practices and company performance”

“The Role of Internal Human Resource Orchestration on Firm Performance”

Nitendra Palankar | Statistical Applications in Engineering | Best Researcher Award

Dr. Nitendra Palankar | Statistical Applications in Engineering | Best Researcher Award

Don Bosco College of Engineering | India

Dr. Nitendra Palankar is a seasoned academic and researcher specializing in Transportation Engineering and Concrete Technology, with over 12 years of experience in the field. He currently serves as a Professor in the Department of Civil Engineering at KLS Gogte Institute of Technology, Belagavi, Karnataka, India. Dr. Palankar completed his Ph.D. in Civil Engineering (Transportation Engineering) from the National Institute of Technology Karnataka (NITK), Surathkal, in July 2016, following an M.Tech. in the same discipline from NITK in 2012. His doctoral research focused on the “Performance of Alkali Activated Concrete Mixes with Steel Slag as Coarse Aggregate for Rigid Pavements,” under the guidance of Prof. A.U. Ravishankar. He has been actively involved in teaching for over six years and has contributed significantly to the academic community through various roles, including serving as an editorial member for the American Journal of Construction and Building Materials and as a reviewer for several reputed journals and conferences. Dr. Palankar has also been a registered research guide at Visvesvaraya Technological University (VTU), Belagavi, currently supervising two research scholars. His research interests encompass sustainable construction materials, particularly the use of industrial by-products in concrete, and the development of eco-friendly pavement technologies. He has authored numerous publications in high-impact journals, including the Journal of Cleaner Production and the International Journal of Pavement Engineering. Dr. Palankar holds an h-index of 6, with 484 citations. His work has garnered recognition for its contribution to sustainable civil engineering practices, particularly in the context of utilizing industrial waste materials for pavement construction. Through his extensive research and academic endeavors, Dr. Palankar continues to advance the field of transportation engineering, focusing on innovative and sustainable solutions for infrastructure development.

Featured Publications

“Studies on Self-Healing Properties of Glass Fibre Reinforced Bituminous Concrete Mixes”

“Development of regression model for strength prediction of Eco-Friendly alkali activated dry lean concrete for pavements”

“Investigations on performance of alkali activated mortar mixes containing red mud and aluminum dross”

“Performance of Alkali-Activated Mortar Mixes Containing Industrial Waste Materials as Binders”

“A study on the effect of rejuvenators in reclaimed asphalt pavement based stone mastic asphalt mixes”