Alla Polyanska | Energy | Research Excellence Award

Published on by Popular Scientist

Prof. Dr. Alla Polyanska | Energy | Research Excellence Award

Professor | AGH University of Krakow | Poland

Prof. Dr. Alla Polyanska focuses on energy systems and smart technologies, with recent research emphasizing sustainable energy transitions and advanced electricity load forecasting. Her work applies a multicriteria approach to assess the effectiveness of energy transition strategies across EU countries, providing insights into policy outcomes and optimization of renewable integration. Additionally, she develops hybrid predictive models combining ARIMA, LSTM, and Random Forest algorithms for intelligent electricity load forecasting, enhancing accuracy in demand prediction and grid management. Her research bridges energy policy evaluation and data-driven modeling, contributing to more efficient, resilient, and sustainable energy systems in Europe.

Citation Metrics (Scopus)

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Citations
279

Documents
25

h-index
12


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Featured Publications

Kaiyao Wu | Energy Economics | Research Excellence Distinction Award

Published on by Popular Scientist

Prof. Kaiyao Wu | Energy Economics | Research Excellence Distinction Award

Professor | Shanghai University of International Business and Economics | China

Prof. Kaiyao Wu is a distinguished scholar in statistics, sustainable development economics, and global value chain research, recognized for his extensive contributions to the quantitative analysis of international trade, energy systems, and digital economic transformation. His work integrates statistical modeling, network analysis, and data science to explore how global production systems, demographic transitions, and environmental governance shape economic development and enterprise behavior. Prof. Wu has authored more than forty peer-reviewed articles in high-impact journals, offering influential insights into embedded carbon flows, carbon neutrality strategies, energy efficiency measurement, ESG performance, global value chain positioning, and outward foreign investment dynamics. His interdisciplinary research bridges industrial economics, environmental accounting, and digitalization studies, with notable applications to enterprise decision-making, regional sustainability assessments, and international trade competitiveness. He has published multiple monographs and textbooks covering topics such as 3E (economy-energy-environment) coupling networks, enterprise data processing, and sustainable development accounting, which are widely used in academic and professional communities. In addition to his research achievements, Prof. Wu plays an active role in academic leadership as a member of several national expert committees, contributing to policy evaluation, statistical innovation, and digital-trade research. He also serves as a reviewer and evaluator for major national research programs, supporting the advancement of empirical methodologies and evidence-based policymaking. His teaching interests span enterprise data analytics, SAS-based statistical analysis, global value chain statistics, and applied market research, where he integrates rigorous quantitative approaches with real-world problem-solving to cultivate the next generation of data-driven professionals.

Profiles: Scopus | Orcid

Featured Publications

Duan, J., Li, Y., Shi, W., & Wu, K. (2025). Beyond the linear: Green technology innovation, moderators, and GVC upgrading. SSRN.

Du, L., Wei, M., & Wu, K. (2023). Information technology and firm’s green innovation: Evidence from China. Environmental Science and Pollution Research, 30.

Liu, H., Wu, K., & Zhou, Q. (2022). Whether and how ESG impacts corporate financial performance in the Yangtze River Delta of China. Sustainability, 14(24), 16584.

Wu, K., Chen, F., Anwar, S., & Liao, L. (2024). The impact of population aging on a country’s global value chain position: Unraveling the dynamics and mechanisms. Emerging Markets Finance and Trade, 60(3).

Wu, K., Sun, C., Zhang, J., & Duan, J. (2023). Carbon neutrality along the global value chain: An international embedded carbon network analysis. Environmental Science and Pollution Research, 30.