Roghieh Hajiboland | Research Excellence | Research Excellence Award

Dr. Roghieh Hajiboland | Research Excellence | Research Excellence Award

Dr. Roghieh Hajiboland | University of Tabriz | Iran

Prof. Roghieh Hajiboland is a distinguished Full Professor of Plant Physiology in the Department of Plant, Cell and Molecular Biology, renowned for her extensive contributions to mineral nutrition, abiotic stress tolerance, and plant–microbe interactions. She earned her Ph.D. in Plant Physiology from the University of Hohenheim, Germany, and has since developed a globally recognized research portfolio focused on nutrient uptake, transport physiology, heavy metal tolerance, salinity and drought stress adaptation, aluminum toxicity, and silicon- and selenium-mediated stress mitigation in diverse crop and halophytic species. With an active research career spanning more than a decade, Prof. Hajiboland has produced a substantial body of high-impact scientific work, including 60+ international journal articles, influential compilation books with Springer, Elsevier, Wiley, and Shayesteh Publishers, and numerous national publications and conference presentations. Her studies have advanced fundamental understanding of mineral element functions, nutrient remobilization, antioxidant responses, water relations, and physiological/biochemical mechanisms underlying stress resilience in plants. She is widely recognized for pioneering research on tea plant physiology, halophyte species, intercropping systems, and the roles of aluminum, selenium, and silicon in plant stress biology. Prof. Hajiboland teaches a broad range of undergraduate, postgraduate, and doctoral-level courses, including Plant Physiology, Plant Growth and Development, Mineral Nutrition, Uptake and Transport in Plants, Transport Physiology, Evolutionary Biology, and Plant–Microbe Interactions. Her academic leadership includes supervising graduate research, mentoring young scientists, and contributing actively to departmental and institutional development. Her scholarly visibility is supported through Google Scholar, Scopus, and ResearchGate profiles, reflecting strong citation influence and international collaboration, particularly with leading researchers in Europe. Through her sustained research, teaching, and publication record, Prof. Hajiboland continues to shape contemporary understanding of plant stress physiology and sustainable crop improvement under challenging environmental conditions.

Profile: Scopus | Orcid | Google Scholar

Featured Publications

Moradtalab, N., Hajiboland, R., Aliasgharzad, N., Hartmann, T. E., & Neumann, G. (2019). Silicon and the association with an arbuscular-mycorrhizal fungus (Rhizophagus clarus) mitigate the adverse effects of drought stress on strawberry. Agronomy, 9(1), 41. https://doi.org/10.3390/agronomy9010041

Rahmat, S., Hajiboland, R., & Sadeghzade, N. (2017). Selenium delays leaf senescence in oilseed rape plants. Photosynthetica, 55(1), 1–10. https://doi.org/10.1007/s11099-016-0643-6

Hajiboland, R., Bahrami-Rad, S., & Poschenrieder, C. (2017). Silicon modifies both a local response and a systemic response to mechanical stress in tobacco leaves. Biologia Plantarum, 61(1), 123–131. https://doi.org/10.1007/s10535-016-0633-3

Ebrahimi, N., Hartikainen, H., Simojoki, A., Hajiboland, R., & Seppänen, M. (2015). Dynamics of dry matter and selenium accumulation in oilseed rape (Brassica napus L.) in response to organic and inorganic selenium treatments. Agricultural and Food Science, 24(3), 219–230.*

Hajiboland, R., Sadeghzadeh, N., Ebrahimi, N., Sadeghzadeh, B., & Mohammadi, S. A. (2015). Influence of selenium in drought-stressed wheat plants under greenhouse and field conditions. Acta Agriculturae Slovenica, 105(2), 213–225. https://doi.org/10.14720/aas.2015.105.2.01

Hajiboland, R., Bastani, S., Bahrami-Rad, S., & Poschenrieder, C. (2015). Interactions between aluminum and boron in tea (Camellia sinensis) plants. Acta Physiologiae Plantarum, 37(12), 1–12. https://doi.org/10.1007/s11738-015-1803-1

Guangqin Li | Innovation Impact | Best Researcher Award

Prof. Guangqin Li | Innovation Impact | Best Researcher Award

Prof. Guangqin Li | Anhui University of Finance & Economics | China

Dr. Guangqin Li began his academic journey with a doctorate in Urban Economics and Management from Shanghai University of Finance and Economics and now serves as a professor and master’s supervisor at Anhui University of Finance & Economics. With deep research interests in the digital economy, industrial economy, environmental economy, and regional economy, he has established himself as a versatile scholar bridging theoretical insights and empirical applications. His bibliometric profile reflects 37 published documents, 1,847 citations from 1,765 citing documents, and an h-index of 18, underscoring his growing impact within the academic community. His publications span studies on the green transformation of industry, the interface of urban innovation and infrastructure investment, and the spatial dynamics of economic development. He has contributed extensively through consultancy projects and collaborations with industry and regional authorities and serves on editorial boards of key journals in his fields. His research output has helped inform policy discussions on how new infrastructure investment can catalyze innovation in cities, particularly by influencing talent agglomeration and economic clustering. Poised at the cutting edge of his disciplines, he continues to mentor rising scholars and engage in interdisciplinary work, positioning his future contributions to shape the intersection of digitalization, regional growth, and sustainability.

Profiles: Scopus | Orcid 

Featured Publications 

Zhang, B., & Li, G. (2025). New infrastructure special debt, agglomeration and urban innovation: Evidence from China. Economic Modelling.

Liu, W., & Li, G. (2025). Sci-tech finance and urban entrepreneurial activity: Evidence from China. Economic Change and Restructuring.

Li, G., & Niu, W. (2025). How does fintech promote urban innovation? Empirical evidence from China. Economic Change and Restructuring.

Fang, X., Liu, M., & Li, G. (2024). Can the green credit policy promote green innovation in enterprises? Empirical evidence from China. Technological and Economic Development of Economy.

Li, G., Jin, Y., & Gao, X. (2023). Digital transformation and pollution emission of enterprises: Evidence from China’s micro-enterprises. Energy Reports.

Bao Liu | Emerging Technologies | Best Researcher Award

Dr. Bao Liu | Emerging Technologies | Best Researcher Award

Dr. Bao Liu | Xi’an University of Science and Technology | China

Dr. Liu Bao is an Associate Professor and Academic Leader in the field of Pattern Recognition and Intelligent Systems at the School of Electrical and Control Engineering, Xi’an University of Science and Technology, where he also serves as a Graduate Supervisor and Project-based Ph.D. Supervisor. He earned his doctorate in engineering from Xi’an Jiaotong University, completed postdoctoral research at Xi’an University of Science and Technology, and broadened his academic experience as a visiting fellow at Macquarie University in Australia. Recognized as a Senior Data Analyst by the Ministry of Industry and Information Technology of China, Dr. Liu is an active member of several national academic societies and professional committees. His research focuses on multi-source information fusion and intelligent technologies for coal fire disaster prevention and control, integrating advanced computational and automation techniques to address complex industrial challenges. Throughout his career, he has led diverse national, provincial, and industry-based research projects and contributed extensively to scientific publications and technological innovation through patents and software developments. As a committed educator and mentor, Dr. Liu has inspired students to excel in academic and professional pursuits and has been honored with multiple awards recognizing his dedication to teaching, research, and academic service.

Profile: Orcid

Featured Publications

Liu, B., Liu, Q., & Wu, Z. (2026, February). A novel robust Student’s t scale mixture distribution based Kalman filter. Signal Processing. https://doi.org/10.1016/j.sigpro.2025.110296

Liu, B., Wu, Z., & Liu, Q. (2025). Gaussian mixture model-based variational Bayesian approach for extended target tracking. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2025.3565347

Liu, B., & Jiang, W. (2024). DFKD: Dynamic focused knowledge distillation approach for insulator defect detection. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2024.3485446

Liu, B., & Jiang, W. (2024, December). LA-YOLO: Bidirectional adaptive feature fusion approach for small object detection of insulator self-explosion defects. IEEE Transactions on Power Delivery. https://doi.org/10.1109/TPWRD.2024.3467915

Liu, B., Zhou, N., & Wang, Z. (2024, December 27). DFI-YOLOv8 based defect detection method for fan blades. In Proceedings of the 2024 Conference on [Insert Conference Name]. https://doi.org/10.1145/3722405.3722437