Tianyuan Xiao | Chemistry | Best Researcher Award

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Prof. Tianyuan Xiao | Chemistry | Best Researcher Award

Qiqihar University | China

Prof. Tianyuan Xiao is a distinguished researcher with a strong record of contributions to materials chemistry and sustainable energy research, having published 32 scientific documents that have garnered 247 citations , reflecting an h-index of 9. His research primarily explores deep eutectic solvents (DES), lignin nanoparticles, covalent adaptive networks, flame retardant materials, and lignin-based adhesive hydrogels, with an additional focus on density functional theory (DFT) for molecular modeling and analysis. Prof. Xiao’s studies are driven by the pursuit of sustainable and high-performance materials derived from lignocellulosic biomass. His recent influential works include “Recent Progress in Deep Eutectic Solvent (DES) Fractionation of Lignocellulosic Components: A Review” published in Renewable and Sustainable Energy Reviews and “Cracking Aryl Ether Bonds of Lignin by Gamma-Valerolactone (GVL) in Coordination with Acid Lithium Bromide Molten Salt System” in the International Journal of Biological Macromolecules. Through his research, Prof. Xiao has significantly advanced understanding of biomass valorization, solvent design, and green chemistry, offering novel insights into environmentally friendly processes for energy and materials innovation.

Profile : Scopus

Featured Publications

Xiao, T., Song, J., Jia, W., Sun, Y., Guo, Y., Fatehi, P., & Shi, H. (2025). Cracking aryl ether bonds of lignin by γ-valerolactone (GVL) in coordination with acid lithium bromide molten salt system. International Journal of Biological Macromolecules, 309(Part 1), 142643.

Xiao, T., Hou, M., Guo, X., Cao, X., Li, C., Zhang, Q., Jia, W., Sun, Y., Guo, Y., & Shi, H. (2024). Recent progress in deep eutectic solvent (DES) fractionation of lignocellulosic components: A review. Renewable and Sustainable Energy Reviews, 192, 114243.

Salman Shahzad | Social Sciences | Best Researcher Award

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Mr. Salman Shahzad | Social Sciences | Best Researcher Award

Xi'an Jiaotong University | China

Mr. Salman Shahzad is a distinguished legal researcher whose academic and scholarly work focuses on public-private partnerships, intellectual property law, and comparative legal systems. Currently pursuing a Ph.D. at Xi’an Jiaotong University, his research explores legal frameworks for public-private partnerships in emerging economies, particularly comparing Pakistan and China. He has earned recognition for his academic excellence, including awards from the New Silk Road Law School Alliance and multiple “Outstanding International Student” honors. His extensive participation in international conferences and training programs—ranging from AI law and corporate law to climate change and arbitration—reflects his interdisciplinary engagement with global legal challenges. With a strong foundation in intellectual property law from Zhongnan University of Economics and Law and an LLB from Abdul Wali Khan University, he has contributed significantly to discussions on copyright, patent harmonization, and digital regulation. His publications span topics such as AI liability, cyberbullying, and extradition law, featured in reputable platforms including ResearchGate and national newspapers. Mr. Shahzad’s active memberships in professional legal associations and contributions to legal education, writing, and policy discourse demonstrate his commitment to advancing legal scholarship and bridging comparative perspectives between national and international legal systems.

Profiles : Orcid | Google Scholar

Featured Publications

Shahzad, S., & Wang, B. (2025, June 2). Geographical indications and sustainable development: Bridging policy gaps in Pakistan’s GI framework for socio-economic growth. Sustainability, 17(11), 5114.

Gwo Dong Lin | Mathematics | Excellence in Research Award

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Prof. Gwo Dong Lin | Mathematics | Excellence in Research Award

Academia Sinica, Institute of Statistical Science | Taiwan

Prof. Gwo Dong Lin is a distinguished statistician and mathematician whose extensive contributions have profoundly influenced the fields of probability theory, moment problems, and life distribution analysis. With an h-index of 18, 71 published documents, and 933 citations from 783 sources, his scholarly output demonstrates both depth and enduring impact. He earned his Ph.D. in Management Science from Tamkang University, following earlier degrees in mathematics from National Taiwan Normal University. Over his career, Prof. Lin served at Academia Sinica’s Institute of Statistical Science, including roles as Deputy Director and Acting Director, and later as Adjunct Research Fellow. He has also directed the Social and Data Science Research Center under the Hwa-Kang Xing-Ye Foundation. His editorial work spans several international journals, and he has been an invited speaker at global conferences organized by the International Statistical Institute and other leading organizations. Recognized as an ISI Elected Member since 1991 and recipient of Taiwan’s Outstanding Research Award (1994–1995), Prof. Lin’s pioneering studies on characterizations of distributions, inequalities for transforms, and moment determinacy continue to shape modern statistical theory and inspire future explorations in applied probability and statistical modeling.

Profile : Scopus

Featured Publications 

Lin, G. D., & Stoyanov, J. (2025). New sufficient conditions for moment-determinacy via probability density tails. Mathematics, 13, 2671.

Dou, X., Kuriki, S., Lin, G. D., & Richards, D. (2025). EM estimation of the B-spline copula with penalized pseudo-likelihood functions. Statistical Papers, 66, 30.

Lin, G. D., & Stoyanov, J. (2024). New characterizations of the Gamma distribution via independence of two statistics by using Anosov’s theorem. Theory of Probability and Its Applications, 69, 745–759 (Russian edition); SIAM version, 69, 592–604.

Hu, C.-Y., & Lin, G. D. (2022). Characterizations of the normal distribution via the independence of the sample mean and the feasible definite statistics with ordered arguments. Annals of the Institute of Statistical Mathematics, 74, 473–488.

Lin, G. D., & Hu, C.-Y. (2022). On the semi-Mittag-Leffler distributions. Probability and Mathematical Statistics, 42, 81–96.

Hu, C.-Y., Lin, G. D., & Stoyanov, J. (2021). Characterization of probability distributions via functional equations of power-mixture type. Mathematics, 9, 271. Also in: L. Shaikhet (Ed.), Prime Archives in Applied Mathematics (2nd ed.). Hyderabad, India: Vide Leaf.

Lin, G. D., & Dou, X. (2021). An identity for two integral transforms applied to the uniqueness of a distribution via its Laplace–Stieltjes transform. Statistics, 55, 365–385.

Dou, X., Kuriki, S., Lin, G. D., & Richards, D. (2021). Dependence structures of B-spline copulas. Sankhyā: The Indian Journal of Statistics, Series A, 83, 238–311.

Lin, G. D., & Hu, C.-Y. (2021). Formulas of absolute moments. Sankhyā: The Indian Journal of Statistics, Series A, 83, 476–495.

Hu, C.-Y., & Lin, G. D. (2020). Necessary and sufficient conditions for unique solution to functional equations of Poincaré type. Journal of Mathematical Analysis and Applications, 491, 124399.

Stoyanov, J. M., Lin, G. D., & Kopanov, P. (2020). New checkable conditions for moment determinacy of probability distributions. Theory of Probability and Its Applications, 65, 634–648 (Russian edition); SIAM version, 65, 497–509.

Lin, G. D., Dou, X., & Kuriki, S. (2019). The bivariate lack-of-memory distributions. Sankhyā: The Indian Journal of Statistics, Series A, 81, 273–297.

Lin, G. D. (2019). On powers of the Catalan number sequence. Discrete Mathematics, 342, 2139–2147.

Hu, C.-Y., & Lin, G. D. (2018). Characterizations of the logistic and related distributions. Journal of Mathematical Analysis and Applications, 463, 79–92.

Lin, G. D. (2017). Recent developments on the moment problem. Journal of Statistical Distributions and Applications, 4, 5.

Lai, C.-D., Lin, G. D., Govindaraju, K., & Pirikahu, S. (2017). A simulation study on the correlation structure of Marshall–Olkin bivariate Weibull distribution. Journal of Statistical Computation and Simulation, 87, 156–170.

Jiayang Gao | Business, Management and Accounting | Best Researcher Award

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Assoc. Prof. Dr. Jiayang Gao | Business, Management and Accounting | Best Researcher Award

South China Normal University | China

Assoc. Prof. Dr. Jiayang Gao is an accomplished scholar in Management at the School of Economics and Management, South China Normal University, specializing in sustainability and innovation management. With an academic journey that began with a B.Sc. in Mathematics from Southeast University, followed by an M.Sc. in Computer Science at South China Normal University, and culminating in a Ph.D. in Management from Sun Yat-Sen University, Dr. Gao has built a strong interdisciplinary foundation. His academic career spans nearly two decades, serving as Lecturer from 2007 to 2025 before being appointed Associate Professor in 2025. He has further enriched his international experience as an Academic Visitor at the University of Birmingham and Loughborough University in the UK. Dr. Gao has authored 4 indexed documents with 39 citations across 39 scholarly records, achieving an h-index of 2, reflecting his growing influence in the field. His research explores mechanisms shaping emergent industries, institutional policy, and social psychology in workplace dynamics, with notable publications in Transportation Research Part D, Current Issues in Tourism, and Technological Forecasting and Social Change. He has also led and co-led several provincial and national research projects, particularly on clean energy vehicles, decent work, and digital industry transformation.

Profile : Scopus

Featured Publications

"Cold waves and electric vehicle adoption: Evidence from Chinese cities"
"Air quality and tourism orders: a quasi-experimental study"
"Forecasting the development of Clean energy vehicles in large Cities: A system dynamics perspective"
"Effects of Public Funding on the Commercial Diffusion of On-site Hydrogen Production Technology: A System Dynamics Perspective"
"Technical or Non-technical Innovation: Transformation Given Consideration to Decent Work by Small OEM Manufacturers"
"Did Industrial Upgrading Restrain Decent Work in the GPN Context: Based on Evidences from Guangdong Province"
"Study Review on FDI’s Impacts on Host Country Decent Work’s Main Index"
"State action on Online game industry and business marketing decision"
"Comparable study on Dynamic advantage among regional digital entertainment industry cluster"
"The comparison Study on online game industrial international Competitiveness between China and Korea"

 

 

Hassan Ramchoun | Mathematics | Best Researcher Award

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Dr. Hassan Ramchoun | Mathematics | Best Researcher Award

Moulay Ismail University | Morocco

Author Profile

Scopus

Early Academic Pursuits

Dr. Hassan Ramchoun’s academic journey reflects a strong foundation in mathematics and computer science. Beginning with his bachelor’s studies in applied mathematics, he progressively advanced through a master’s degree in operations research and statistics, where he explored Bayesian approaches in artificial neural networks for medical imaging. His doctoral research in applied mathematics and computer science further solidified his expertise, focusing on parameter and hyper-parameter estimation in Bayesian neural networks with applications in classification and regression. These early experiences shaped his specialization in applied mathematics, artificial intelligence, and machine learning.

Professional Endeavors

Dr. Ramchoun has built a diverse academic career with teaching, research, and leadership responsibilities. Since joining ENCG Meknès, Moulay Ismail University, as a lecturer, he has also taught at multiple institutions including ENSAM Meknès and the Euro-Mediterranean University of Fès. His teaching portfolio covers a wide spectrum, from probability and statistics to optimization, data analysis, and artificial intelligence. His active engagement in curriculum design, supervision of students, and participation in doctoral juries reflects his deep commitment to higher education and student mentorship.

Contributions and Research Focus

Dr. Ramchoun’s research focuses on applied mathematics, artificial intelligence, and data science, with particular emphasis on Bayesian neural networks, deep learning, optimization, and statistical learning methods. He has contributed to developing new methods for training and optimizing neural networks, incorporating regularization and Bayesian inference. His work extends to multi-objective optimization for neural architectures, convolutional neural networks, and applications in big data analytics. His scholarly contributions are reflected in numerous publications in international journals and conferences, alongside editorial contributions to Springer volumes on artificial intelligence and industrial applications.

Accolades and Recognition

Dr. Ramchoun’s academic excellence has been acknowledged through distinctions such as the CNRST excellence research scholarship and his recognition for doctoral work with high honors. His research output is regularly published in reputed international journals including Neurocomputing, Knowledge-Based Systems, Soft Computing, and Evolving Systems. His active involvement as a reviewer for leading journals and as a member of scientific committees of conferences demonstrates recognition of his expertise by the global scientific community.

Impact and Influence

Through his work, Dr. Ramchoun has significantly influenced both the academic and applied dimensions of artificial intelligence. His innovations in neural network optimization and Bayesian learning methods have advanced understanding in machine learning research, while his teaching and supervision of master’s and doctoral students have contributed to developing future generations of researchers. By bridging theoretical modeling with practical applications, his contributions have relevance not only in academia but also in applied domains such as data science, robotics, and image processing.

Legacy and Future Contributions

The legacy of Dr. Ramchoun lies in his efforts to advance the integration of applied mathematics with artificial intelligence, particularly in deep learning and Bayesian modeling. His involvement in research projects, scientific committees, and international conferences ensures that his contributions extend beyond publications to shaping the field itself. Looking forward, his continued work in optimization techniques, advanced statistical learning, and interdisciplinary applications promises to strengthen the role of artificial intelligence in addressing scientific and industrial challenges.

Publications

  • Article: Convergence of batch gradient descent with learnable smooth masks for pruning feedforward neural networks
    Authors: Quasdane, M., Ramchoun, H., Masrour, T.
    Journal: Neurocomputing
    Year: 2025

  • Article: Enhancing CNN structure and learning through NSGA-II-based multi-objective optimization
    Authors: Elghazi, Khalid, Ramchoun, Hassan, Masrour, Tawfik
    Journal: Evolving Systems
    Year: 2024

  • Article: Implicitly adaptive optimal proposal in variational inference for Bayesian learning
    Authors: Bakhouya, Mostafa, Ramchoun, Hassan, Hadda, Mohammed, et al.
    Journal: International Journal of Data Science and Analytics
    Year: 2024

  • Article: Gaussian Mixture Models for Training Bayesian Convolutional Neural Networks
    Authors: Bakhouya, M., Ramchoun, H., Hadda, M., Masrour, T.
    Journal: Evolutionary Intelligence (Springer)
    Year: 2024

  • Article: Sparse smooth group L0L1/2 regularization method for convolutional neural networks
    Authors: Quasdane, M., Ramchoun, H., Masrour, T.
    Journal: Knowledge-Based Systems
    Year: 2023

Conclusion

Dr. Hassan Ramchoun exemplifies the qualities of a dedicated academic, innovative researcher, and committed educator. His career reflects a balance of teaching excellence, impactful research, and institutional service. With strong foundations in mathematics and expertise in artificial intelligence, his contributions are shaping the evolving landscape of machine learning and data science. His recognition, publications, and leadership in academic communities confirm his standing as an influential figure whose work will continue to resonate in both research and applied domains.