Jian-Gen Liu | Mathematical Statistics | Innovative Research Award

Published on by Statistics

Innovative Research Award

Jian-Gen Liu
Affiliation Suzhou University of Technology
Country China
Scopus ID 57192912165
Documents 75
Citations 1355
h-index 24
Subject Area Mathematical Physics
Event World Statistics Awards

Jian-Gen Liu,
Suzhou University of Technology

Jian-Gen Liu is affiliated with Suzhou University of Technology, China, and has established an academic profile in Mathematical Physics through peer-reviewed publications and scholarly collaborations. His research portfolio demonstrates sustained scientific productivity and measurable citation impact, supporting recognition through the World Statistics Awards. [1]

Abstract

This article presents an overview of Jian-Gen Liu’s academic achievements, publication record, citation performance, and research influence within Mathematical Physics. The profile summarizes scholarly productivity and highlights evidence supporting consideration for the Innovative Research Award presented through the World Statistics Awards. [1] [2]

Keywords

Mathematical Physics, Scientific Research, Scholarly Publications, Citation Analysis, Scopus Author, Research Excellence, Academic Impact, Innovative Research Award, World Statistics Awards. [1]

Introduction

Jian-Gen Liu has contributed to mathematical physics through theoretical investigations and peer-reviewed publications. His scholarly activities demonstrate consistent academic engagement, interdisciplinary collaboration, and measurable research visibility. Citation indicators and publication output reflect sustained contributions supporting international academic recognition and professional distinction. [1] [2]

Research Profile

Affiliated with Suzhou University of Technology, Jian-Gen Liu maintains a recognized Scopus author profile featuring seventy-five indexed publications, over one thousand citations, and an h-index of twenty-four. These metrics indicate continuous scientific productivity and broad scholarly engagement across mathematical physics research. [1] [3]

Research Contributions

His research contributions include advancing mathematical modeling, analytical methods, and theoretical approaches applicable to complex physical systems. Published investigations have supported scientific understanding, encouraged interdisciplinary collaboration, and provided valuable references for researchers working within mathematical and computational sciences. [2]

Publications

The publication portfolio contains peer-reviewed journal articles indexed in major scientific databases. These works demonstrate methodological rigor, research consistency, and international dissemination. Several publications include Digital Object Identifiers, ensuring accessibility, citation reliability, and long-term scholarly referencing within the academic community. [2]

Research Impact

The documented citation count and h-index indicate that Jian-Gen Liu’s publications have influenced subsequent scientific studies. His research output contributes to knowledge development, strengthens academic discourse, and demonstrates continuing relevance within mathematical physics and associated interdisciplinary research fields. [1] [3]

Award Suitability

Based on documented scholarly achievements, publication quality, citation performance, and measurable research influence, Jian-Gen Liu satisfies important academic considerations for the Innovative Research Award. His sustained scientific productivity reflects the principles of excellence, integrity, innovation, and international research contribution. [1]

Conclusion

Jian-Gen Liu’s academic record illustrates continuous research development, recognized publication performance, and meaningful scientific influence. Available bibliometric indicators support acknowledgement of his scholarly accomplishments while emphasizing continued contributions to mathematical physics through internationally visible and peer-reviewed research activities. [1] [2]

References

  1. Elsevier. (n.d.). Scopus author details: Jian-Gen Liu, Author ID 57192912165.

    https://www.scopus.com/pages/authors/57192912165

  2. Liu, J., & Tian, K. (2026). Formulation, symmetry analysis and solutions for the time fractional thin film-type equation. Journal of Geometry and Physics

    https://www.sciencedirect.com/science/article/abs/pii/S0393044026001737?via%3Dihub

  3. World Statistics Awards. (n.d.). Award Information and Nomination Guidelines.

    https://statisticsaward.com

Esra Cakir | Fuzzy Statistics and Uncertainty Modelling | Innovative Research Award

Published on by Statistics

Innovative Research Award

Esra Cakir,
Affiliation Galatasaray University
Country Turkey
Scopus ID 57210106850
Documents 50
Citations 286
h-index 9
Subject Area Fuzzy set theory
Event World Statistics Awards
ORCID 0000-0003-4134-7679

Esra Cakir,
Galatasaray University

Esra Cakir, affiliated with Galatasaray University, has contributed to research in fuzzy set theory through scholarly publications addressing mathematical modeling, uncertainty analysis, and decision-making methodologies. Her publication record, citation performance, and continuing academic engagement demonstrate sustained contributions to statistics and applied mathematical sciences within an international research environment.[1]

Abstract

Esra Cakir’s academic activities focus on fuzzy set theory and related statistical methodologies that support uncertainty modeling, optimization, and intelligent decision-making. Her research portfolio reflects continued publication in peer-reviewed journals and measurable scholarly influence through citations, contributing to mathematical sciences and interdisciplinary statistical applications.[1] [2]

Keywords

Fuzzy Set Theory, Statistics, Decision Making, Mathematical Modeling, Optimization, Uncertainty Analysis, Applied Mathematics, Data Analysis, Intelligent Systems, Scientific Research.[2]

Introduction

Esra Cakir has established an academic presence through research in fuzzy set theory, emphasizing mathematical approaches for uncertainty and decision analysis. Her work supports statistical modeling and interdisciplinary applications while contributing to peer-reviewed scientific literature that advances quantitative research methodologies across multiple domains.[1] [2]

Research Profile

Affiliated with Galatasaray University, Esra Cakir has authored fifty indexed publications and accumulated 286 citations with an h-index of nine. Her research addresses fuzzy systems, mathematical reasoning, and statistical techniques, demonstrating consistent scholarly productivity and international academic visibility through recognized indexing databases.[1] [3]

Research Contributions

Her contributions include developing and applying fuzzy set methodologies for uncertainty evaluation, decision support, and mathematical analysis. These studies encourage improved analytical frameworks across statistics and related disciplines while promoting interdisciplinary collaboration and methodological refinement within contemporary quantitative research environments.[2] [3]

Publications

Esra Cakir’s publication record comprises fifty Scopus-indexed documents covering fuzzy mathematics, statistical modeling, and decision sciences. These publications demonstrate continuing research activity, collaboration with academic peers, and dissemination of findings through internationally recognized scholarly journals and conference proceedings.[1] [4]

Research Impact

With 286 citations and an h-index of nine, her research demonstrates measurable academic influence. Citation performance indicates that her published studies continue supporting subsequent investigations, reflecting sustained relevance within fuzzy set theory, statistical methodologies, and interdisciplinary mathematical research communities.[1] [3]

Award Suitability

The Innovative Research Award appropriately recognizes sustained scholarly productivity, meaningful publication output, and contributions to fuzzy set theory. Her documented research achievements, citation record, and continuing engagement with advanced statistical methodologies align with the objectives of international academic recognition programs.[1] [2]

Conclusion

Esra Cakir’s academic profile reflects continuous contributions to fuzzy set theory through publications, citations, and collaborative research. Her scholarly achievements demonstrate professional consistency and support her recognition within the World Statistics Awards as a researcher contributing to contemporary statistical and mathematical sciences.[1] [3]

References

  1. Elsevier. (n.d.). Scopus author details: Esra Cakir, Author ID 57210106850. Scopus.

    https://www.scopus.com/pages/authors/57210106850

  2. ORCID. (n.d.). Esra Cakir ORCID Record: 0000-0003-4134-7679.

    https://orcid.org/0000-0003-4134-7679

  3. Çakır, E. (2026). Energy-efficient and sustainable milk-run optimization for e-scooter battery routing under fuzzy time windows. IEEE Transactions on Industry Applications.

    https://doi.org/10.1109/TIA.2026.3680469

  4. World Statistics Awards. (n.d.). Innovative Research Award.

    https://statisticsaward.com

Khurshid Hussain | Artificial Intelligence in Statistics | Research Excellence Award

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Mr. Khurshid Hussain | Artificial Intelligence in Statistics | Research Excellence Award

Kiost | South Korea

Mr. Khurshid Hussain is a dynamic researcher whose work spans advanced automotive engineering, semiconductor design, integrated sensing and communications, and AI-driven signal processing, establishing him as a multidisciplinary contributor across next-generation wireless, cybersecurity, and intelligent vehicular systems. He holds a Master’s degree in Advanced Automotive Engineering from Sun Moon University, South Korea, where he specialized in high-performance millimeter-wave circuit design with emphasis on 60 GHz digital variable-gain amplifiers, beamforming architectures, low-power attenuators, and chip-level ISAC systems for secure and intelligent communication. His research extends into geomatics and remote sensing, focusing on multimodal mapping using optical, SAR, and LiDAR streams, change detection, 3D reconstruction, and uncertainty-aware geospatial pipelines, alongside self-supervised and weak-supervised learning approaches for large-scale spatial data modeling. He is the inventor of a patented transistor-array-based variable attenuator and has authored an expanding collection of peer-reviewed publications in leading journals such as Electronics, IEEE Access, Applied Sciences, and IEEE Transactions, addressing topics ranging from radar–communication co-design and ultrasonic 3D beamforming sensors to predictive maintenance of aerospace components, OTFS-based V2X ISAC architectures, and AI-enhanced signal intelligence. His scholarly profile includes 9 documents, 77 citations, and an h-index of 4, reflecting his growing influence in mmWave IC design, wireless sensing, and AI-integrated communication. Khurshid has delivered technical presentations at major international conferences covering maritime IT convergence, high-frequency amplifier design, battery analytics, advanced beamforming, and power-efficient RF front-end systems. His expertise spans Cadence, HFSS, Python, MATLAB, OrCAD, cybersecurity tools, and vector network analyzers, reinforced by experience in transceiver integration, AI-chip convergence, intrusion detection systems, battery research, and embedded engineering. Earlier, he completed his B.Sc. in Electrical Engineering with a focus on IoT-based renewable-energy automation, where he developed sensor-driven, cloud-connected, and energy-efficient systems. Fluent in English and active in multicultural environments, Khurshid is known for his creativity, leadership, communication skills, and passion for innovation, continually advancing secure, intelligent, and energy-efficient technologies for the automotive, wireless, and sensing industries.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Hussain, K., & Yoo, J. (2025). Low-latency marine-based OTFS echo parameter estimation enabled by AI. Sensors, 25(23), Article 7104. DOI: 10.3390/s25237104

Hussain, K., Ali, E. M., Hussain, W., Raza, A., & Elkamchouchi, D. H. (2025). Robust OTFS-ISAC for vehicular-to-base station end-to-end sensing and communication. Electronics, 14(21), Article 4340. DOI: 10.3390/electronics14214340

Hussain, K., Jeon, W., Lee, Y., Song, I., & Oh, I. (2025). CMOS-compatible ultrasonic 3D beamforming sensor system for automotive applications. Applied Sciences, 15(16), Article 9201. DOI: 10.3390/app15169201

Hussain, K., & Oh, I. (2024). Joint radar, communication, and integration of beamforming technology. Electronics, 13(8), Article 1531. DOI: 10.3390/electronics13081531

Hussain, K., & Oh, I. (2024). Review of joint radar, communication, and integration of beam-forming technology. Preprint. DOI: 10.20944/preprints202404.0208.v1

Yohanna Kusuma | Multivariate Statistical Analysis | Best Researcher Award

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Dr. Yohanna Kusuma | Multivariate Statistical Analysis | Best Researcher Award

The Royal Melbourne Hospital-The University of Melbourne | Australia

Dr. Yohanna Kusuma is an Australian-trained, internationally recognised neurologist and academic whose clinical and research work bridges acute stroke, neuroimaging, neurosonology, and movement disorders, with a strong translational focus across the Asia-Pacific region. She obtained her neurology specialist qualification from the University of Indonesia with honours, completed advanced fellowships in neurosonology and stroke at leading institutions in Singapore, and earned a PhD from Deakin University supported by an international scholarship, focusing on advanced CT-perfusion imaging in acute ischaemic stroke and the influence of ethnicity on imaging and clinical outcomes. She holds Fellowship of the Royal Australasian College of Physicians, qualifying her as a Consultant Neurologist in Australia. Dr Kusuma serves as Chief Investigator of the AI-powered SERENA platform for real-time stroke triage and decision support, leads the multinational APEX registry on acute ischaemic stroke with cancer spanning nine Asia–Pacific countries, and co-supervises PhD and honours students at Deakin University. She holds senior appointments in both Australia and Indonesia, including Senior Consultant Neurology at Metropolitan Medical Centre Hospital in Jakarta and Senior Research Fellow at The University of Melbourne. Her professional leadership includes representing Indonesia on the Asia Pacific Stroke Organisation and the Asian Stroke Advisory Panel, serving on the Education Council of the Australian Stroke Academy, and having previously served as a Co-opted Board Member of the World Stroke Organisation. Actively engaged in education and training, she has organised and delivered numerous neurosonology and stroke imaging workshops across the Asia-Pacific. Her research output is extensive, with an h-index of 4 and 144 citations, 13 peer-reviewed publications, book chapters, and international presentations. Dr Kusuma exemplifies a clinician-scientist who integrates cutting-edge imaging, neurosonology, and translational stroke research while advancing global collaborations in academic neurology, clinical innovation, and medical education.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

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.

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.

Kuruba Chandrakala | Machine Learning and Statistics | Best Researcher Award

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

Siddhartha Academy of Higher Education | India

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

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

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

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

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

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

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

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

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

Normasys | France

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

Profiles: Scopus | Orcid

Featured Publications

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

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

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

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

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

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”

Hexin Zhang | Descriptive and Inferential Statistics | Best Paper Award

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Dr. Hexin Zhang | Descriptive and Inferential Statistics | Best Paper Award

Dr. Hexin Zhang | Harbin Engineering University | China

Dr. Hexin Zhang serves as an Associate Professor and Ph.D. Supervisor at the School of Materials Science and Chemical Engineering, Harbin Engineering University. His academic journey has been guided by a dedication to advancing the field of high-temperature composite materials, superalloys, and additive manufacturing. With consistent contributions to research and education, Dr. Zhang has established himself as a recognized scholar whose work bridges fundamental understanding with industrial application. His expertise reflects not only in his technical research but also in the mentorship of students and the leadership of collaborative projects. Through his professional efforts, he has nurtured an academic path marked by innovation, curiosity, and the pursuit of impactful scientific progress. His work remains committed to developing solutions that align with the evolving challenges of materials science while setting benchmarks that inspire colleagues and students alike across research and industrial communities.

Profile

Scopus

Education

Dr. Zhang pursued rigorous academic training in materials science, which laid the foundation for his impactful career. His undergraduate education provided a comprehensive grounding in chemistry and material fundamentals, equipping him with the tools to navigate complex research challenges. His postgraduate journey deepened this knowledge through advanced study in high-temperature materials and structural applications, allowing him to build expertise in addressing technical frontiers of engineering innovation. The doctoral training he received emphasized both theoretical understanding and experimental practice, guiding him to investigate emerging material systems with precision and creativity. His educational background combines strong academic discipline with applied problem-solving, reinforcing his ability to contribute meaningfully to both scientific discovery and industrial implementation. This solid academic pathway has directly shaped his role as a researcher, educator, and supervisor, positioning him to guide future generations while continuing to explore new research possibilities in his chosen fields.

Experience

Dr. Zhang has successfully led and contributed to projects supported by various funding bodies, including national foundations, special research programs, and regional initiatives. His portfolio includes collaborations with both academic and industrial partners, reflecting his commitment to transforming laboratory findings into practical technologies. Through these roles, he has gained invaluable experience in project management, cross-disciplinary teamwork, and academic leadership. His efforts span from fundamental research into high-performance materials to applied studies that directly serve industrial needs. By working with industry collaborators, he has fostered the integration of cutting-edge knowledge into real-world applications, enhancing technological progress in key sectors. His role as a Ph.D. Supervisor highlights his ability to mentor students and nurture talent, ensuring the sustainability of research excellence. Collectively, his experience exemplifies a dynamic balance between scholarly inquiry, practical application, and academic mentorship within the evolving domain of materials science.

Research Interests

Dr. Zhang’s research interests revolve around the development and optimization of high-temperature composite materials, superalloys, and additive manufacturing techniques. He explores structural design strategies that improve material performance under demanding conditions, with particular emphasis on durability, thermal stability, and mechanical resilience. His work aims to refine the performance of engineering materials to meet the growing challenges of modern industries such as aerospace, energy, and advanced manufacturing. He also investigates innovative methods in additive manufacturing to enhance precision, reduce costs, and create complex structures that were previously unattainable with conventional techniques. By combining experimental approaches with theoretical insights, his research offers comprehensive solutions that bridge academic exploration and industrial need. This multidisciplinary focus underscores his commitment to fostering new knowledge while addressing practical challenges, making his contributions relevant both in academia and in fields that depend on advanced material technologies.

Award & Recognitions

Dr. Zhang has received recognition for his contributions to scientific research and academic leadership. His achievements have been acknowledged through competitive research grants, invitations to contribute to academic committees, and opportunities to collaborate on high-impact projects. These distinctions reflect his capacity to lead with innovation and to make lasting contributions within his area of expertise. His consistent pursuit of excellence, coupled with his ability to align research with industrial needs, highlights his distinguished role within the scientific community. His awards and honors not only represent personal success but also underscore the collective progress of his teams and collaborators. Each recognition reinforces the importance of his research in advancing material science applications, while also motivating future endeavors aimed at solving critical technological challenges. His professional acknowledgments illustrate his standing as a respected scholar and an influential contributor to the global research landscape.

Publication Top Notes

Impact of Secondary γ’ Precipitate on the High-Temperature Creep Properties of DD6 Alloy

Journal: Metals and Materials International
Authors: Xiaopeng Li, Shan Yu, Yao Huang, Yuqi Wang, Hexin Zhang, Chengzhi Zhao

Microstructural Evolution and Its Effect on Tensile Properties of 10Cr-2W-3Co Martensitic Steel During Thermal Exposure

Journal: Materials Today Communications
Authors: Yuqi Wang, Yihan Zhao, Yao Huang, Shan Yu, Jiaxin Shang, Chengkun Yang, Hexin Zhang, Chengzhi Zhao

Microstructure Evolution and Mechanical Properties of Ti-6Al-4V Alloy Fabricated by Directed Energy Deposition Assisted with Dual Ultrasonic Vibration

Journal: Materials Science and Engineering A
Authors: Fang Chao Peng, Chunhuan Guo, Fengchun Jiang, Hexin Zhang, Sergey Konovalov

Effect of powder particle size on the microscopic morphology and mechanical properties of 316 L stainless steel hollow spheres

Journal: Granular Matter
Authors: Jianliang Li, Xu Cui, Qianfei Sun, Chunhuan Guo, Fengchun Jiang, Hexin Zhang

Study on Hot-Compressive Deformation Behavior and Microstructure Evolution of 12Cr10Co3MoWVNbNB Martensitic Steel

Journal: Steel Research International
Authors: Yuqi Wang, Yao Huang, Shan Yu, Chengkun Yang, Hexin Zhang, and Chengzhi Zhao

Conclusion

Dr. Zhang’s academic journey illustrates a consistent pursuit of excellence in scientific exploration, technological innovation, and educational mentorship. His contributions to high-temperature materials, superalloys, and additive manufacturing highlight his ability to merge theoretical knowledge with practical application, thereby fostering advancements that resonate across industries and research domains. As an active leader in research projects and an accomplished author of widely cited publications, he exemplifies the qualities of a researcher committed to addressing contemporary challenges. His mentorship of students and collaborations with industrial partners further amplify the impact of his work, ensuring its continued relevance and contribution to both knowledge and application. In light of his achievements, he stands as a highly deserving candidate for recognition, embodying the spirit of academic excellence, innovation, and professional dedication. His continued efforts will undoubtedly shape the future trajectory of materials science and inspire new generations of researchers.