Jinfa Zhang | Statistical Applications in Engineering | Research Excellence Award

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Dr. Jinfa Zhang | Statistical Applications in Engineering | Research Excellence Award

China University of Petroleum (Beijing) | China 

The research profile reflects a strong and continuous focus on petroleum engineering, Statistical Applications in Engineering with specialized expertise in rock mechanics, geomechanics, lost circulation control, reservoir stimulation, and enhanced oil and gas recovery. Advanced doctoral research concentrates on the mechanical behavior of reservoir rocks, wellbore stability, and lost circulation mechanisms, integrating theoretical modeling with practical engineering applications. Master’s-level research emphasized oil and gas reservoir stimulation technologies, enhanced recovery methods, numerical reservoir simulation, and optimization techniques, supported by a strong academic performance and rigorous coursework in advanced reservoir engineering, fluid phase equilibria, and simulation software applications. Undergraduate training provided a solid foundation in drilling engineering, completion engineering, rock mechanics, porous media flow, oilfield chemistry, and production engineering. The research experience is complemented by extensive proficiency in industry-standard professional software for fracturing design, reservoir simulation, curve fitting, programming, and geospatial analysis, enabling comprehensive data-driven studies. Practical exposure through geological fieldwork and petroleum production training strengthened the ability to connect theoretical research with field-scale operations. Academic excellence is demonstrated through competitive scholarships, innovation and design competitions, and national-level recognitions, highlighting strong research capability, interdisciplinary technical skills, and potential for impactful contributions to petroleum engineering research and technology development.

Citation Metrics (Scopus)

40
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Citations
23

Documents
9

h-index
2

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h-index


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Featured Publications

Chokri Aloui | Operations Research and Statistical Optimization | Research Excellence Award

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Dr. Chokri Aloui | Operations Research and Statistical Optimization | Research Excellence Award

University of Sousse | Tunisia

Dr. Chokri Aloui is an Assistant Professor at the Faculty of Economics and Management, University of Sousse, and a researcher at the Laboratory of Research in Innovation Management and Sustainable Development, Sousse Higher Institute of Management, specializing in microeconomics, industrial organization, platform and network economics, environmental economics, and the economic appraisal of development projects. He holds a Ph.D. in Economics from Sousse University, preceded by a Master’s degree from Tunisia Polytechnic School and a Bachelor’s degree from Jendouba University, and his academic trajectory reflects a consistent focus on network externalities, two-sided markets, competition, and digital economy dynamics. His teaching portfolio spans industrial economics, microeconomics at various levels, game theory, markets and strategies, development project appraisal, and business simulation, demonstrating broad expertise across applied and theoretical microeconomics. His research contributions include influential works on platform capacity sharing, congestion pricing, net neutrality, corporate social responsibility in two-sided platforms, and environmental certification within international trade, published in journals such as Economic Modelling, Networks and Spatial Economics, Managerial and Decision Economics, the International Review of Economics, and The Manchester School. Across his scholarly output, he has produced multiple peer-reviewed articles and maintains an active presence on platforms such as Google Scholar and ResearchGate. His Scopus profile reports approximately 43 citations, an h-index of 3, and a set of documents reflecting his ongoing research productivity. Overall, Chokri Aloui stands out as a researcher whose work integrates rigorous modeling with practical economic policy implications, contributing meaningfully to the understanding of digital markets, innovation, environmental responsibility, and development-oriented economic assessments.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Kaili Wang | Machine Learning and Statistics | Best Researcher Award

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Dr. Kaili Wang | Machine Learning and Statistics | Best Researcher Award

university of malaya | Malaysia

Dr. Kaili Wang is an accomplished economist and Doctoral Candidate in Financial Economics at the University of Malaya, with a strong academic foundation in quantitative analysis, holding a master’s degree in Quantitative Economics from Zhongnan University of Economics and Law and a bachelor’s degree in Statistics from Luoyang Normal University. She has extensive teaching experience, having served as a full-time faculty member at the Business School of Nantong University of Technology, where she contributed significantly to both academic research and student mentorship. Her research expertise encompasses financial security, green finance, and the operational efficiency of financial institutions, reflected in her monographs, including Analysis of RMB Internationalization Path from the Perspective of Financial Security (sole author) and Research on the Long-term Mechanism of Green Finance Development (second author). She has also led impactful research projects, such as the Jiangsu Provincial University Philosophy and Social Sciences Research Project on the operational efficiency of city commercial banks. Kaili Wang has demonstrated a strong commitment to student development, guiding participants in national and provincial financial competitions to notable achievements, including second and third prizes in the National ETF Elite Challenge and the “East Money Cup” National College Students’ Financial Challenge, and earning recognition as an Excellent Supervisor. Her work reflects a combination of rigorous empirical analysis and practical engagement with financial markets, emphasizing sustainable finance and strategic economic development. With a focus on integrating academic excellence with real-world financial insights, Kaili Wang continues to advance knowledge in financial economics while nurturing the next generation of economists and financial professionals through research, mentorship, and academic leadership. Her career demonstrates a sustained dedication to both scholarly contributions and fostering student success in competitive financial arenas.

Profile: Orcid

Featured Publication

Wang, K. (2024). An analysis of the RMB internationalization path from the perspective of financial security.

Vikas Mehta | Statistical Computing and Programming | Research Excellence Award

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Dr. Vikas Mehta | Statistical Computing and Programming | Research Excellence Award

Korean National Institute for International Education | South Korea

Dr. Vikas Mehta is a structural engineer and researcher specializing in seismic performance optimization, sustainable construction materials, and the application of advanced computational and machine learning methodologies to civil infrastructure systems. He completed his Ph.D. in Civil Engineering at Keimyung University, South Korea, where his award-winning doctoral research introduced innovative modifier-based and data-driven techniques for improving shear strength prediction and design accuracy in reinforced concrete beam-column joints. His expertise spans nonlinear finite element modeling, fragility analysis, physics-informed and graph-based machine learning, geospatial analytics, and performance-based seismic assessment, supported by strong proficiency in ETABS, OpenSees, SeismoSoft, Abaqus, MATLAB, Q-GIS, SPSS, Python, PyTorch, WEKA, and OriginPro. Dr. Mehta serves as a Postdoctoral Researcher at the Chonnam National University R&BD Foundation, contributing to advanced safety technologies for nuclear power plant structures under extreme hazard scenarios, including buckling resistance enhancement, retrofit optimization, and complex wind–terrain interaction studies. His professional background includes academic appointments in structural and construction engineering, where he taught subjects in earthquake engineering, finite element analysis, and structural systems while supervising graduate research and contributing to curriculum and laboratory development. Dr. Mehta has authored a substantial body of SCI-indexed research on seismic damage prediction, torsional behavior modeling, hybrid AI-mechanics frameworks, recycled and sustainable materials, computational methods, and structural performance evaluation, complemented by multiple patents in construction materials, damping devices, and waste-based composites. He has presented at leading international and national conferences and contributed to funded collaborative research, including projects involving global academic and industry partners. His professional affiliations include membership in ASCE, the Institute of Physics (AMInstP), IAEME (Fellow), and licensure as a Class-A engineer under the Himachal Pradesh Town and Country Planning Act. Dr. Mehta’s contributions to structural engineering and computational mechanics continue to gain international visibility, reflected in an h-index of 7, over 172 citations, and more than 19 published documents, underscoring his growing influence in machine learning–driven structural design, seismic resilience, and sustainable construction innovation.

Profiles: Scopus | Orcid

Featured Publications

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Corrigendum to “Adaptive simulation and data-driven hybrid modeling for predicting shear strength and failure modes of interior reinforced concrete beam-column joints”.

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Predictive framework for shear strength and failure modes of exterior reinforced concrete beam–column joints using machine learning. Structural Concrete. h.

Sagar, G. S., Mukthi, S., & Mehta, V. (2025). Analyzing compressive, flexural, and tensile strength of concrete incorporating used foundry sand: Experimental and machine learning insights. Archives of Computational Methods in Engineering.

Mehta, V., Thakur, M. S., & Chey, M. H. (2025). Enhancing seismic design accuracy of RC beam-column joints: Modifier-based approach for shear strength predictions. Structures.

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Adaptive simulation and data-driven hybrid modeling for predicting shear strength and failure modes of interior reinforced concrete beam-column joints. Structures.

Jitae Kim | Econometrics and Statistical Economics | Excellence in Research Award

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Dr. Jitae Kim | Econometrics and Statistical Economics | Excellence in Research Award

Environmental Planning Institute | South Korea

Dr. Jitae Kim is a distinguished environmental and resource economist serving as a Senior Researcher at the Environmental Planning Institute of Seoul National University and as an Academic Research Professor with the Korea Research Foundation. He holds a Ph.D., M.A., and B.A. in Economics, completing all degrees at leading Korean universities, and has built a multidisciplinary research portfolio spanning environmental planning, climate economics, applied econometrics, labor-market dynamics, and carbon policy analysis. His scholarly work covers meta-regression valuation of biodiversity, cost–benefit assessments of ecological projects, econometric forecasting of energy demand, and empirical investigations of how climate extremes such as heatwaves and typhoons influence labor markets, wages, and informal work conditions. He has contributed extensively to research on carbon mitigation under the Korean Emissions Trading Scheme, the co-benefits of green remodeling, and the transition toward sustainable energy systems. His international collaborations include major research projects on climate-disaster-driven labor-market disruptions in the Philippines, conducted with academic partners at Ateneo de Manila University. His publications appear in respected international and Korean journals, complemented by multiple working papers, conference presentations, and policy-oriented studies. Based on publicly available academic profiles, he has 2 indexed documents and approximately 109 citations, with an estimated h-index of about 1, reflecting the early but growing influence of his work. Before advancing into academia and research leadership, he served in analytical roles with institutions such as the Korea Capital Market Institute and the Korea Labor Institute, contributing to evidence-based policy development in environmental, labor, and economic sectors. Through his expanding body of research, Dr. Kim continues to shape discussions on just transition, climate-risk adaptation, sustainable energy planning, and equitable climate-finance allocation, establishing himself as a rising scholar dedicated to bridging empirical analysis with practical environmental policy solutions.

Profiles: Scopus | Google Scholar 

Featured Publication

Kim, J., Hong, J. H., & Kim, J. (2025). Energy consumption forecasting of neighborhood living facilities: A panel regression approach.

Palidan Muhetaer | Statistical Computing and Programming | Best Researcher Award

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Assoc Prof. Dr. Palidan Muhetaer | Statistical Computing and Programming | Best Researcher Award

Xinjiang University of Finance & Economics | China

Profiles: Scopus 

Featured Publications

Fan, Y., Qian, Y., Gong, W., Chu, Z., Qin, Y., & Muhetaer, P. (2024). Multi-level interactive fusion network based on adversarial learning for fusion classification of hyperspectral and LiDAR data

Moumita Mukherjee | Machine Learning and Statistics | Best Researcher Award

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Dr. Moumita Mukherjee | Machine Learning and Statistics | Best Researcher Award

Charite-University Medicine Berlin | Germany

Dr. Moumita Mukherjee is an accomplished health economist and digital health researcher with expertise in health systems research, machine learning applications in healthcare, and interdisciplinary teaching. She holds a PhD in Economics from the University of Calcutta, an MBA in Entrepreneurship, Innovation and Project Development from International Telematic University, and an MSc in Data Science from the University of Europe for Applied Sciences, Germany. Her professional experience spans both academic and applied research environments, including positions at Charite-University Medicine Berlin, the Indian Institute of Public Health in Shillong, and the Berlin School of Business and Innovation. She has contributed extensively to global health research focusing on digital transformation, equity in healthcare access, and the use of data-driven methods for improving health outcomes. Her body of work includes numerous peer-reviewed publications in leading journals such as Scientific Reports, Journal of Health, Population and Nutrition, Journal of Health Management, and International Journal for Equity in Health, as well as book chapters and authored volumes addressing child health, nutrition, and health equity. In her current role at Charite-University Medicine Berlin, she lectures on digital health and artificial intelligence, supervises master’s theses, and mentors students. With advanced technical proficiency in Python, STATA, and NVivo, she applies econometric, machine learning, and deep learning models to address complex public health and policy questions. Her interdisciplinary approach integrates health economics, digital innovation, and policy analysis to support equitable and sustainable health systems worldwide. Through her research, teaching, and mentorship, Dr. Moumita Mukherjee continues to bridge data science and health economics to shape the future of evidence-based global health policy and digital healthcare transformation.

Profiles: Google Scholar | Orcid

Featured Publications

Kiran Sree Pokkuluri | Machine Learning and Statistics | Excellence in Research Award

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Prof. Dr. Kiran Sree Pokkuluri | Machine Learning and Statistics | Excellence in Research Award

Shri Vishnu Engineering College For Women | India

Prof. Dr. Kiran Sree Pokkuluri is a distinguished academician, researcher, and innovator in the field of Artificial Intelligence and Machine Learning with an illustrious career of academic and research excellence. Currently serving as Professor and Head of the Department of Computer Science and Engineering at Shri Vishnu Engineering College for Women, he has significantly contributed to advancing computational intelligence and data-driven innovation in academia and industry. He holds a Ph.D. in Artificial Intelligence from JNTU-Hyderabad and has an impressive scholarly record with over 100 research publications in reputed SCI and Scopus-indexed journals, a citation count exceeding 653, an h-index above 13, and an Documents exceeding 152, reflecting the global impact of his research. His research areas include Deep Learning, Healthcare Analytics, Bioinformatics, IoT Power Optimization, Big Data Analytics, and Cloud Computing. Dr. Sree has authored six textbooks with ISBNs on Artificial Intelligence, Machine Learning, and Deep Learning, and has filed and published six patents in the domains of AI and intelligent systems. His innovations such as the Hybrid Deep Neural ZF Network (HDNZF-Net) have set new benchmarks in real-time speech enhancement for speech-impaired individuals and IoT optimization. He has completed five major funded projects and collaborated with premier institutions including Stanford University through the UIF program, fostering cross-disciplinary innovation. A recognized thought leader, Dr. Sree serves as Editor-in-Chief, editorial board member, and reviewer for multiple international journals. His remarkable achievements have earned him prestigious recognitions like the Bharat Excellence Award and Rashtriya Ratan Award, and he has been featured in Marquis Who’s Who in the World. As Global Vice President of the World Statistical Data Analysis Research Association (WSA) and a member of professional bodies such as IEEE, ISTE, CSI, and IAENG, Dr. Kiran Sree continues to inspire excellence in AI-driven research, education, and technological innovation.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Venkatachalam, B., Pokkuluri, K. S., Suguna Kumar, S., Dhandapani, A., & Bhonsle, M. (2025). Adaptive fuzzy heuristic algorithm for dynamic data mining in IoT integrated big data environments. Journal of Fuzzy Extension and Applications, 6(3), 615–636.

Pokkuluri, K. S., Sarkar, P., Birchha, V., Mathariya, S. K., Veeramachaneni, V., & others. (2025). Intelligent reasonable optimization for virtual machine provisioning in hybrid cloud using fuzzy AHP and cost-effective autoscaling. SN Computer Science, 6(7), 1–15.

Sivanuja, M., Raju, P. J. R. S., Prasad, M., RR, P. B. V., Kumar, K. S., & Pokkuluri, K. S,. (2025). A novel ensemble-based deep learning framework combining CNN and transfer learning models for enhanced wildfire detection. In Proceedings of the 2025 International Conference on Computational Robotics, Testing and Applications.

Alzubi, J. A., Pokkuluri, K. S., Arunachalam, R., Shukla, S. K., Venugopal, S., & others. (2025). A generative adversarial network-based accurate masked face recognition model using dual scale adaptive efficient attention network. Scientific Reports, 15(1), 17594.

Pokkuluri, K. S., Chandanan, A. K., Mishra, A. K., Jyothi, D., Lavanya, M. S. S. L., & others. (2025). Deep learning-enhanced intrusion detection and privacy preservation for IIoT networks. In Proceedings of the 2025 4th International Conference on Distributed Computing and Electrical Systems.

Aladji Abatchoua Madi Madi Ibram | Multivariate Statistical Analysis | Best Researcher Award

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Dr. Aladji Abatchoua Madi Madi Ibram | Multivariate Statistical Analysis | Best Researcher Award

University of Ebolowa | Cameroon

Dr. Aladji Abatchoua Madi Madi Ibram is a distinguished academic and researcher currently serving as the Head of the Department of Biological Sciences Applied to Agriculture at the University of Ebolowa, Cameroon. He holds a Ph.D. in Genetics and Plant Breeding, with a specialized focus on genetic variability, plant improvement, and sustainable agricultural development. As a lecturer, he teaches a wide range of subjects including Mendelian and Morganian genetics, quantitative traits genetics, and seed production. His research primarily emphasizes improving crop yield and nutritional quality in economically important plants, thereby contributing to both food security and human health. Dr. Aladji Abatchoua’s scientific contributions have been recognized across several reputed platforms such as Springer, BMC, Nature Portfolio, Scientific American, Palgrave Macmillan, and Adis. He has published over 14 research papers in internationally indexed journals, showcasing his dedication to advancing plant genetics and breeding. His collaborative research with the University of Ngaoundéré and the University of Yaoundé 1 has further enhanced the understanding of genotype–environment interactions, particularly in crops like sesame and peanut, to identify stable and high-yielding varieties suitable for diverse agro-ecological zones. Beyond his research endeavors, he actively contributes to the academic community as a reviewer for several international journals, including the Journal of Plant Sciences, International Journal of Genetics and Genomics, and Journal of Plant Studies, ensuring the maintenance of high-quality peer-reviewed publications. His commitment to scientific excellence has been acknowledged through multiple certificates of excellence in peer reviewing from reputable international journals such as BP International and the Journal of Experimental Agriculture International. Through his academic leadership, innovative research, and dedication to agricultural advancement, Dr. Aladji Abatchoua Madi Madi Ibram continues to play a pivotal role in fostering agricultural innovation and scientific integrity in Cameroon and beyond.

Profiles:  Orcid

Featured Publications

Aladji Abatchoua Madi Madi Ibram. (2025). Genetic analysis of common bean (Phaseolus vulgaris L.) for root traits, yield components and seed yield. Journal of Applied Genetics.

Jianjian Chen | Operations Research and Statistical Optimization | Operations Research Award

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Dr. Jianjian Chen | Operations Research and Statistical Optimization | Operations Research Award

 Jiangxi University of Finance and Economics | China

Dr. Jianjian Chen is a lecturer in the School of Information Management and Mathematics at Jiangxi University of Finance and Economics, Jiangxi, P. R. China, where he has established himself as a promising scholar in the fields of management science, decision support, and electronic commerce. His research focuses on platform economics, online marketplaces, and decision support methodologies that contribute to both the theoretical and practical advancement of information systems and business strategies. Over the course of his career, Chen has built a solid portfolio of high-quality research, with his work appearing in well-regarded journals including Decision Support Systems, Information Systems Frontiers, Computers & Industrial Engineering, Electronic Commerce Research, and Electronic Commerce Research and Applications. These publications highlight his expertise in applying analytical and empirical methods to understand the complexities of digital platforms and e-commerce ecosystems. According to his Scopus profile Chen has published 7 scholarly documents, which have collectively received 86 citations, resulting in an h-index of 5, reflecting both the productivity and the impact of his research. His contributions not only enrich the academic discourse on decision support and electronic commerce but also offer practical insights for businesses navigating digital transformation and platform-based economies. Chen’s scholarship demonstrates a balance between rigorous methodological development and the application of innovative models to real-world problems, reinforcing his role as a valuable contributor to the intersection of management, information systems, and economics. By combining theoretical frameworks with practical problem-solving approaches, his research provides meaningful support for decision-making in the digital economy and underscores his growing influence within the international academic community.

Profile: Scopus 

Featured Publications

“Traditional e-commerce or live e-commerce? Online sales model selection strategies considering streamers’ bargaining behaviors”