Jian Xia | Artificial Intelligence in Statistics | Research Excellence Award

Dr. Jian Xia | Artificial Intelligence in Statistics | Research Excellence Award

Hubei University of Automotive Industry | China

Dr. Jian Xia is a dedicated materials scientist specializing in next-generation electronic and photonic devices, with a strong academic foundation and a growing record of impactful research. He obtained his Ph.D. degree from the School of Materials Science and Engineering at Huazhong University of Science and Technology, where he developed expertise in resistive switching devices, phase-change materials, and advanced optical memory technologies. After completing his doctoral studies, he joined the Hubei University of Automotive Technology as a lecturer, contributing actively to both teaching and research in the field of electronic materials and integrated circuit design. Dr. Xia’s research interests encompass memristors, phase-change memory, and photonic neuromorphic devices, all of which hold promising applications in high-performance computing, data storage, and artificial intelligence hardware. He has undertaken notable research projects, including the Open Fund of the Hubei Key Laboratory of Energy Storage and Power Battery and the Doctoral Scientific Research Foundation of Hubei University of Automotive Technology. With a citation index of 361 and a research portfolio of 20 SCI-indexed publications, Dr. Xia has contributed articles to leading international journals such as Nature Communications, Laser & Photonics Reviews, ACS Photonics, Applied Physics Letters, IEEE Electron Device Letters, and Science China Materials. His innovative contributions are further demonstrated by nine patents that are either published or under review, highlighting his commitment to advancing practical and technologically significant developments in electronic device engineering. Although he has yet to hold editorial appointments or professional memberships, his scholarly influence continues to grow through strong research visibility and future collaboration potential. Dr. Xia maintains an active academic presence on platforms such as ResearchGate and continues to advance pioneering research aimed at developing energy-efficient, high-density, and neuromorphic computing devices to meet the evolving demands of modern information technology.

Citation Metrics (Scopus)

400
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0

Citations
361

Documents
7

h-index
5

Citations

Documents

h-index


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Featured Publication

 

Vikas Mehta | Statistical Computing and Programming | Research Excellence Award

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.

Zeliha Coskun Tas | Statistical Applications in Engineering | Best Researcher Award

Mrs. Zeliha Coskun Tas | Statistical Applications in Engineering | Best Researcher Award

Kocaeli University | Turkey

Mrs. Zeliha Coskun Tas is a distinguished researcher in the field of Biomedical Engineering, currently serving as a Research Assistant at Kocaeli University, Faculty of Technology, Biomedical Engineering Department. She is actively pursuing her Ph.D. at the Institute of Science, Kocaeli University, where she also completed her Master’s degree, following her Bachelor’s degree in Biomedical Engineering from Erciyes University. Her research expertise encompasses biomaterials, biometals, bioceramics, and functionally graded biomaterials, with a strong emphasis on developing innovative bioactive implant interfaces and evaluating biomechanical performance in medical applications. Zeliha Coskun Tas has authored and co-authored several impactful publications in high-ranking SCI-E journals, including the Journal of Biomedical Materials Research: Part A, World Neurosurgery, and the Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine. Her study, “A Novel Radially Graded Hydroxyapatite-Based Composite for Bioactive Implant Interfaces,” reflects her commitment to advancing bioengineering materials for enhanced implant functionality. In addition, she has presented multiple peer-reviewed papers at international conferences in Italy and Turkey, focusing on 3D printing applications, biomechanical testing, and advanced implant design. Her research contributions have also extended to nationally funded projects supported by Kocaeli University’s Scientific Research Project Unit (BAP), where she played a leading role in projects such as Production and Characterization of Functionally Graded Ceramic and Polymer Doped Titanium Implants and Development of an Apparatus Design for Radial Gradient Powder Material Casting. Her earlier project, Development of Torsion and Four-Point Bending Test Systems for Finger and Toe Bones, demonstrates her interdisciplinary approach linking materials science and biomechanics. Beyond research, she actively contributes to the scientific community through peer reviews for reputed journals such as the Journal of Materials Engineering and Performance, Sakarya University Journal of Science, and Physical and Engineering Sciences in Medicine. A recipient of the TÜBİTAK 2211-C and 2214-A scholarships, she continues to pursue excellence in biomedical research with a focus on creating advanced, sustainable, and biocompatible materials for medical innovation. Through her dedication, academic rigor, and innovative research, Res. Asst. Zeliha Coskun Tas exemplifies the new generation of biomedical engineers shaping the future of healthcare technology.

Profiles: Google Scholar

Featured Publications

Coşkun, Z., Çelik, T., & Kişioğlu, Y. (2023). Metatarsal bone model production using 3D printing and comparison of material properties with results obtained from CT-based modeling and real bone. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 5.

Coşkun, Z., Çelik, T., & Kişioğlu, Y. (2021). Design and manufacture of the torque test setup for small and shapeless materials. Turkish Journal of Engineering, 6(1), 81–86.

Coşkun, Z., Çelik, T., & Kişioğlu, Y. (2021). Comparison of the stress distribution between high-heeled and flat shoes on the first metatarsal bone. Politeknik Dergisi, 24(3), 1303–1308.

Çelik, T., & Coşkun Taş, Z. (2024). Biomechanical evaluation of a newly developed functional-grade composite material for pedicle screws. World Neurosurgery, 187, e525–e533.

Coşkun Taş, Z., & Çelik, T. (2022). Design of new pedicle screw and biomechanical evaluation using finite element analysis. 3rd International Conference on Applied Engineering and Natural Sciences, 1.