Davron Juraev | Data Modeling and Database Design | Research Excellence Award

Published on by Database Scientist

Prof. Dr. Davron Juraev | Data Modeling and Database Design | Research Excellence Award

Research Fellow | Turon University | Uzbekistan

Prof. Dr. Davron Juraev is an internationally published mathematician whose research centers on ill-posed problems, elliptic systems, Cauchy problems, Helmholtz equation factorizations, mathematical physics, numerical analysis, and applied mathematical modeling. According to Google Scholar, he has 1,532 citations, 284 indexed documents, an h-index of 23, and an i10-index of 41, reflecting sustained global impact. His scholarship spans high-visibility journals and proceedings in mathematical physics, fractional calculus, spectral theory, computational mathematics, data analysis, and engineering applications, with extensive contributions to Helmholtz theory, regularization methods, and matrix factorization techniques. He has authored multiple research monographs and book chapters with international publishers, edited special issues in mathematical physics, and published across interdisciplinary domains including engineering systems, quantum decision models, and applied data sciences. His funded research leadership includes fundamental national and international collaborative projects, while his editorial board memberships, guest editorships, and reviewer service demonstrate recognized authority within the global applied mathematics and computational sciences community.

Citation Metrics (Google Scholar)

1800

1500

1200

900

600

300

0

Citations
1532

Documents
284

h-index
23

i10index
41

Citations

Documents

h-index

i10-index

View Scopus Profile  View ORCID Profile  View Google Scholar  View ResearchGate  View Web of Science

Featured Publications

Peng Su | Machine Learning on Databases | Research Excellence Award

Published on by Database Scientist

Prof. Peng Su | Machine Learning on Databases | Research Excellence Award

Hebei University of Technology | China

Prof. Peng Su’s research centers on the advanced design, electromagnetic modeling, and performance optimization of permanent-magnet (PM) electrical machines, with a primary emphasis on flux-switching machine topologies for electric and hybrid-electric vehicle applications. With a citation record of 563 citations in total (431 since 2020), an h-index of 12 (11 since 2020), and an i10-index of 16 (12 since 2020), his contributions are well recognized within the electrical machine research community. His work significantly advances understanding of rotor-PM and stator-PM flux-switching architectures through rigorous analyses of operating principles, air-gap field modulation, hybrid-excitation mechanisms, and multi-phase configurations, enabling improved torque density, efficiency, and thermal robustness. Prof. Peng Su has delivered influential findings on PM eddy-current losses, stator-slot and rotor-pole selection, cogging-torque reduction strategies, and magnetization effects, offering practical design paths for minimizing parasitic losses and enhancing reliability under high-speed and vector-controlled drive conditions. His portfolio extends across diverse machine types—including axial-modular machines, multitooth structures, tubular PM generators, and toroidally wound direct-drive motors—demonstrating comprehensive expertise in advanced electromagnetic machine architectures. He also contributes to loss modeling in soft magnetic composites, fault behavior characterization, and performance evaluation methodologies tailored to transportation electrification requirements. Through systematic comparative studies, innovative structural proposals, and refined analytical models, Prof. Peng Su continues to shape the development of next-generation PM machines and high-efficiency energy-conversion technologies, reinforcing his position as a leading contributor to modern electrical machine engineering.

Profiles: Google Scholar | Orcid

Featured Publications

  • Hua, W., Su, P., Tong, M., & Meng, J. (2016). Investigation of a five-phase E-core hybrid-excitation flux-switching machine for EV and HEV applications. IEEE Transactions on Industry Applications, 53(1), 124–133.

  • Su, P., Hua, W., Wu, Z., Han, P., & Cheng, M. (2017). Analysis of the operation principle for rotor-permanent-magnet flux-switching machines. IEEE Transactions on Industrial Electronics, 65(2), 1062–1073.

  • Su, P., Hua, W., Wu, Z., Chen, Z., Zhang, G., & Cheng, M. (2018). Comprehensive comparison of rotor permanent magnet and stator permanent magnet flux-switching machines. IEEE Transactions on Industrial Electronics, 66(8), 5862–5871.

  • Su, P., Hua, W., Hu, M., Chen, Z., Cheng, M., & Wang, W. (2019). Analysis of PM eddy current loss in rotor-PM and stator-PM flux-switching machines by air-gap field modulation theory. IEEE Transactions on Industrial Electronics, 67(3), 1824–1835.

  • Su, P., Hua, W., Hu, M., Wu, Z., Si, J., Chen, Z., & Cheng, M. (2019). Analysis of stator slots and rotor pole pairs combinations of rotor-permanent magnet flux-switching machines. IEEE Transactions on Industrial Electronics, 67(2), 906–918.*