JOSE CLAUDE NYAMOU MOKOMPEA | Econometrics and Statistical Economics | Research Excellence Award

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Mr. JOSE CLAUDE NYAMOU MOKOMPEA | Econometrics and Statistical Economics | Research Excellence Award

Université de Douala (FSEGA) | Cameroon

This scholar is an emerging economist with strong academic training in economic sciences, management, and financial engineering, with advanced specialization in applied economics, macroeconomic analysis, and monetary and banking systems. Academic formation spans economic theory, applied economic modeling, financial engineering, and development economics, supported by multidisciplinary postgraduate training in both national and international institutions. Research orientation is centered on global economic uncertainty, macroeconomic instability, financial systems, and their structural impacts on developing economies, with a particular emphasis on vulnerability, resilience mechanisms, and policy transmission channels. Doctoral research focuses on the effects of global uncertainty on developing countries, contributing to debates in international economics, development finance, and applied macroeconomics. Professional experience includes institutional training in public utilities, urban administration, and development-oriented fieldwork, alongside participation in public health monitoring and international development initiatives. Field research experience includes financial capacity assessments, market integration of green innovations, and socioeconomic evaluation projects in regional and cross-border contexts. Scholarly interests integrate economic modeling, sustainable development, green innovation economics, public policy analysis, and financial inclusion. This profile reflects a strong combination of theoretical grounding, applied research competence, interdisciplinary exposure, and commitment to evidence-based policy and development research in emerging and developing economies.

Profile: Orcid 

Featured Publications 

Mignamissi, D., Ndong Ntah, M. H., Nyamou Mokompea, J. C., & Possi Tebeng, E. X. (2025). Corruption and misery: What lessons for developing countries? Journal of the Knowledge Economy.

Junpeng Guo | Recommendation system | Research Excellence Award

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Prof. Junpeng Guo | Recommendation system | Research Excellence Award

Tianjin University | China

The research profile centers on advanced decision-support and analytical methodologies applied to complex digital and managerial environments. Core research areas include recommender systems in e-commerce and social media platforms, Recommendation system with a focus on improving personalization, user engagement, and decision quality through data-driven models. Significant contributions are made in symbolic data analysis and modeling under uncertainty, addressing incomplete, imprecise, and heterogeneous information commonly encountered in real-world decision problems. The work further advances multi-objective evaluation and decision-making frameworks, integrating operations research, decision science, and optimization techniques to support strategic and operational decisions in business and engineering systems. Methodological research emphasizes mathematical modeling, applied statistics, and computational intelligence, bridging theoretical rigor with practical applicability. Scholarly activities extend to peer review and evaluation for leading international journals and major research funding agencies, ensuring alignment with high academic standards and research integrity. International research exposure through visiting scholar appointments has strengthened interdisciplinary collaboration and contributed to the global exchange of knowledge in information systems, management science, and analytics. Overall, the research demonstrates a sustained commitment to developing robust analytical tools that enhance decision-making effectiveness in uncertain, data-intensive, and multi-criteria environments across digital commerce and management domains.

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View ScopusProfile

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.

Somayeh Bahramnejad | Survival Analysis and Reliability | Editorial Board Member

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Dr. Somayeh Bahramnejad | Survival Analysis and Reliability | Editorial Board Member

Sirjan University of Technology | Iran

Dr. Somayeh Bahramnejad is an accomplished Assistant Professor in the Department of Computer Engineering at Sirjan University of Technology, recognized for her scholarly impact and multidisciplinary contributions across reliability engineering, machine learning, image processing, computer architecture, and computer networks. She completed her B.S. degree in Computer Hardware Engineering at Ferdowsi University of Mashhad, earned her M.Sc. in Computer Architecture from Amirkabir University of Technology, and later obtained her Ph.D. in Computer Architecture from the University of Isfahan. With a steadily expanding academic portfolio, she has published influential research in reputable international journals, including Microelectronics Reliability, SN Computer Science, Computing, Computers & Electrical Engineering, and Scientia Iranica, contributing to a total of six peer-reviewed journal publications. According to her Google Scholar profile, she has accumulated 29 citations, an h-index of 3, and an i10-index of 1, demonstrating the visibility and growing influence of her research contributions. Dr. Bahramnejad has significantly advanced the field through innovative work on reliability improvement of SRAM-based FPGAs, reliability analysis of CR-VANETs, and the application of machine-learning methods for evaluating digital circuit reliability. She provides academic consultancy to seven M.Sc. students, supporting high-quality research, technical development, and scholarly productivity. Her professional presence on Google Scholar and ORCID ensures transparent documentation of her academic achievements and research outputs. Committed to interdisciplinary collaboration and impactful scientific inquiry, she focuses on designing robust, scalable, and reliable computing systems informed by both theoretical insight and practical need. With her dedication to excellence, mentorship, innovation, and long-term contributions to engineering research, Dr. Bahramnejad stands as a strong candidate for distinctions such as the Reliability Analysis Award, Best Researcher Award, Best Paper Award, Women Researcher Award, and Innovative Research Award, reflecting her potential for continued leadership within the global research community.

Profiles: Scopus | Orcid

Featured Publications

Bahramnejad, S. (2025). A fuzzy-arithmetic-based reliability assessment model for digital circuits (FARAM-DC). Microelectronics Reliability.

Bahramnejad, S., Movahhedinia, N., & Naseri, A. (2024). An LSTM-based method for automatic reliability prediction of cognitive radio vehicular ad hoc networks. SN Computer Science.

Bahramnejad, S., Movahhedinia, N., & Naseri, A. (2023). A deep learning method for automatic reliability prediction of CR-VANETs. Research Square.

Bahramnejad, S., & Movahhedinia, N. (2022). A fuzzy arithmetic-based analytical reliability assessment framework (FAARAF): Case study, cognitive radio vehicular networks with drivers. Computing.

Bahramnejad, S., & Movahhedinia, N. (2022). A reliability estimation framework for cognitive radio V2V communications and an ANN-based model for automating estimations. Computing.

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

Tao Zhong | Machine Learning and Statistics | Best Researcher Award

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Dr. Tao Zhong | Machine Learning and Statistics | Best Researcher Award

Sun Yat-sen University | China

Dr. Zhong Tao is a dedicated interdisciplinary researcher specializing in environmental engineering, material science, and computational modelling. A native of Chongqing, China, he is a member of the Communist Party of China and currently based in Guangzhou. He earned his Bachelor’s degree in Environmental and Ecological Engineering with a minor in Computer Science and Technology from Sichuan Agricultural University, followed by a Master’s in Environmental Science and Engineering from Guangxi University under Prof. Yu Zebin, and is pursuing his Doctor of Engineering (Ph.D.) in Resources and Environment at Sun Yat-sen University under Prof. He Chun. His research focuses on the design and development of high-activity environmental functional materials for atmospheric and water pollutant removal, catalytic ozonation, and clean-energy catalysis, including hydrogen production via water splitting. He also employs Density Functional Theory (DFT) to analyze catalytic materials and pollutant molecular structures, building structure–property relationships to guide experiments. Dr. Zhong has contributed to 31 SCI-indexed papers, including 11 as first or co-first author, and applied for 5 patents, with 4 granted. His ongoing research includes national and provincial projects as principal investigator or key contributor. He has received multiple national and university-level scholarships and awards for academic excellence, innovation, and leadership. His Scopus metrics reflect a growing international influence, with an h-index of 10, 22 documents, and over 343 citations, underscoring his strong academic productivity. Known for his rigorous research approach, interdisciplinary collaboration, and mentoring of peers and students, Dr. Zhong also pursues interests in history, literature, and sports, maintaining an optimistic, resilient, and disciplined outlook that complements his scientific career.

Profiles: Scopus 

Featured Publications

Guo, X., Yao, Z., Long, X., Zeng, L., Wang, C., Fang, Z., Zhong, T., Tian, S., Shu, D., & He, C. (2025). Recent advances in tailored nanostructured ozonation catalysts for enhanced VOCs removal: Synergistic optimization of scale configuration and electronic microenvironment.

Zhong, T., Yao, Z., Zeng, L., Zhao, H., Long, X., Li, T., Tian, S., & He, C. (2025). Manipulating spin-configuration via electron reverse overflow to dynamically tune the adsorption behavior of sulfur-containing intermediates for enhanced sulfur resistance.

Om Sambhaji Shelke | Operations Research and Statistical Optimization | Excellence in Research Award

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Dr. Om Sambhaji Shelke | Operations Research and Statistical Optimization | Excellence in Research Award

Sinomune Pharmaceutical Co. Ltd | China

Dr. Om Sambhaji Shelke is a highly accomplished pharmaceutical scientist with extensive expertise in the formulation and development of topical, semisolid, solid, and liquid drug products. Holding a Ph.D. in Pharmacy and an M. Pharmacy from Savitribai Phule Pune University, he has over a decade of experience across global markets including the US, EU, China, Hong Kong, and India. Currently serving as Chief Scientist at Sinomune Pharmaceutical Co. Ltd. in Wuxi, Jiangsu, China, Dr. Shelke leads the development of generic topical products for the NMPA market. He is skilled in Quality by Design (QbD)-based development of creams, ointments, gels, shampoos, and solutions, with specialization in novel formats such as emulgel, organogel, nanogel, solid lipid nanoparticles, suspensions, and toothpaste. He also holds three granted patents and has published multiple scientific and technical articles. Throughout his career, he has received multiple awards recognizing his innovation, knowledge sharing, and leadership, including the StarFire Award. Dr. Shelke has held pivotal roles at leading pharmaceutical and consumer healthcare companies such as Prinbury Biopharm Co. Ltd., Encube Ethicals Pvt Ltd., Bright Future Pharmaceuticals Ltd., Unilever Industries Pvt Ltd., Abbott Healthcare Pvt Ltd., Dr. Reddy’s Laboratories, and Glenmark Pharmaceuticals Ltd., contributing to both regulatory-compliant NDA, ANDA, and 505(b)(2) products as well as OTC, cosmetic, and personal care formulations. His professional journey reflects a consistent commitment to scientific excellence, innovative product development, and leadership in cross-functional teams, positioning him as a prominent figure in global pharmaceutical research and development.

Profiles: Google Scholar | Orcid

Featured Publications

F. Jie, O. Shelke, Z. Yijie, C. Yulan, & L. Yongbo. (2025). Q1 and Q2 selection, Q3, IVRT, IVPT, pharmacokinetic and pharmacodynamic evaluation of topical generic product. Drug Development and Industrial Pharmacy, 51(6), 555–565.

J. Feng, O. S. Shelke, Y. Chen, Z. Zhang, X. Tang, & Y. Zhu. (2025). IVRT and IVPT of desonide lotion and cream: Correlation with human bioequivalence study. Journal of Pharmaceutical Innovation, 20(5), 196.

S. Krishna Phani Chandra, S. Om Sambhaji, & N. Shorgar. (2025). Quantification of leniolisib in rat plasma using LC-MS/MS: Method development, validation, and pharmacokinetic study. African Journal of Biological Sciences, 7(7), 121–142.

S. Om. (2025). Editorial article: The transformative impact of AI in pharmaceutical drug product development. Insights of Pharmatech, 1(2), 1.

S. Gadge, O. S. Shelke, R. Pingale, P. Palande, S. Tandale, P. Sonawane, … (2025). Development and evaluation of a polyherbal neem-based emulgel enriched with herbal oils for enhanced topical delivery and antibacterial efficacy. Journal of Chemical Health Risks, 15(3), 2189–2209.

Guo Tian | Machine Learning and Statistics | Best Researcher Award

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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.