Aleksandr Kulikov | Energy and Sustainability | Research Excellence Award

Published on by Research Hypothesis

Prof. Dr. Aleksandr Kulikov | Energy and Sustainability | Research Excellence Award

Prof. Dr. Aleksandr Kulikov | Energy and Sustainability | Research Excellence Award | Lecturer | Nizhny Novgorod State Technical University | Russia

Prof. Dr. Aleksandr Kulikov is a distinguished scholar in electric power engineering, widely recognized for his advanced expertise in relay protection, emergency automation, distributed generation, digital signal processing, and the cybersecurity of modern electric networks. Prof. Dr. Aleksandr Kulikov holds multiple higher education degrees across engineering and economics, including a doctoral-level qualification in electric power systems, complemented by earlier academic work in radar, radio navigation, and economic system reliability. His professional experience spans leadership positions in major energy enterprises, where he served as Deputy Chief Engineer, Director of trunk electric grid operations, scientific supervisor for government-funded technology programs, and a long-serving professor at the Nizhny Novgorod State Technical University. Throughout his career, Prof. Dr. Aleksandr Kulikov has demonstrated outstanding commitment to academic excellence, supervising master’s students, postgraduate researchers, and doctoral candidates, many of whom have successfully defended their dissertations under his mentorship. His research interests cover a wide spectrum of modern power-system challenges, including high-voltage line fault detection, emergency-mode processing, machine-learning-based grid diagnostics, selective control of power-quality indicators, and the reliability of renewable-integrated microgrids. His research skills span analytical modeling, digital signal processing, industrial frequency analysis, reliability assessment, fault location techniques, and the development of novel algorithms and decision-support systems for complex power networks. Prof. Dr. Aleksandr Kulikov has contributed more than three hundred scientific works, including publications in Scopus-indexed and Web of Science–indexed journals, IEEE conference proceedings, and high-impact engineering journals. His inventions and patents further demonstrate his innovative contributions to advancing electric power technologies. Among his numerous awards and honors are prestigious regional, national, and international distinctions, including medals, honorary diplomas, and recognition for excellence in scientific innovation and contributions to the development of electrical grid infrastructure. His leadership roles include membership in dissertation councils, editorial board service for multiple scientific journals, and expert involvement in federal technology-development programs. Prof. Dr. Aleksandr Kulikov continues to advance the field through active research, academic mentorship, and scientific collaboration, maintaining a significant influence on the evolution of intelligent power systems and modern energy engineering. His longstanding dedication to the scientific community, strong record of innovation, and impact on the reliability of national power systems solidify his status as a leading figure deserving of international recognition.

Profile: ORCID 

Featured Publications 

  1. Kulikov, A., Loskutov, A., Ilyushin, P., Kurkin, A., & Sluzova, A. (2025). High-voltage overhead power line fault location through sequential determination of faulted section technologies.

  2. Ilyushin, P., Papkov, B., Kulikov, A., & Suslov, K. (2025). Algorithm and methods for analyzing power consumption behavior of industrial enterprises considering process characteristics.

  3. Kulikov, A. L., Sevostyanov, A. A., & Ilyushin, P. V. (2023). Analysis of electrical-power quality in modern power-supply systems with selective control of several indicators.

  4. Kulikov, A., Ilyushin, P., Loskutov, A., & Filippov, S. (2023). Application of search algorithms in determining fault location on overhead power lines according to the emergency mode parameters.

  5. Kulikov, A., Loskutov, A., Bezdushniy, D., & Petrov, I. (2023). Decision tree models and machine learning algorithms in the fault recognition on power lines with branches.

  6. Kulikov, A., Ilyushin, P., & Suslov, K. (2023). Enhanced readability of electrical network complex emergency modes provided by data compression methods.

  7. Kulikov, A., Ilyushin, P., Suslov, K., & Filippov, S. (2023). Estimating the error of fault location on overhead power lines by emergency state parameters using an analytical technique.

 

 

Yang Chen | Energy and Sustainability | Best Researcher Award

Published on by Research Hypothesis

Mr. Yang Chen | Energy and Sustainability | Best Researcher Award

Mr. Yang Chen | Energy and Sustainability | Best Researcher Award | PhD Candidate | The Hong Kong Polytechnic University | Hong Kong 

Mr. Yang Chen is a dedicated researcher in environmental and energy economics whose work integrates advanced computational methods with policy-relevant environmental analysis, contributing significantly to the understanding of carbon emissions, pollution control, and sustainability transitions. Mr. Yang Chen’s academic foundation is rooted in his doctoral studies at The Hong Kong Polytechnic University, where he specializes in environmental modelling, causal complexity analysis, and machine-learning–assisted prediction systems. His education equips him with strong analytical abilities in econometrics, environmental impact assessment, and data-driven research methodologies, forming the backbone of his scholarly identity. Professionally, Mr. Yang Chen has engaged in several completed and ongoing research projects involving interdisciplinary teams and multi-institutional networks, allowing him to contribute to innovative work addressing global environmental and energy challenges. His research interests include carbon emission modelling, renewable energy policy evaluation, environmental pollution dynamics, and the application of fuzzy-set qualitative comparative analysis (fsQCA) combined with SHAP-based machine-learning frameworks, reflecting his commitment to methodological innovation and complex-systems thinking. Mr. Yang Chen’s research skills span statistical modelling, causal inference, policy impact analysis, machine learning for environmental prediction, scientific writing, and peer-review activities for high-impact journals, strengthening his role as a rising scholar in sustainability research. His publication record includes approximately ten papers in reputable JCR Q1 journals such as Building and Environment, Environmental Impact Assessment Review, Earth’s Future, Journal of Cleaner Production, and Journal of Environmental Management, demonstrating consistent scholarly productivity. In addition to journal articles, Mr. Yang Chen has contributed as an editorial board member to two academic books published by leading Chinese presses, reflecting recognition of his expertise. His citation metrics, including more than two hundred citations, an h-index of six, and multiple i10-index publications, further underscore the growing influence of his work. Although he is early in his career and has not yet accumulated major awards, Mr. Yang Chen’s recognition as a reviewer for top journals and his authorship in high-impact platforms demonstrate his academic credibility and emerging leadership within the research community. In conclusion, Mr. Yang Chen exemplifies the qualities of a forward-looking environmental economist whose combination of methodological innovation, strong publication output, and commitment to interdisciplinary sustainability research positions him for significant future contributions to global climate policy, environmental modelling, and academic leadership.

Profile:  ORCID | Google Scholar

Featured Publications

  1. Chen, Y., Luo, L., Feng, W., Wu, J., & Cai, W. (2025). Progressive prediction of embodied carbon emissions across stages of schematic design with machine learning. Journal of Cleaner Production. (Citations: 3)

  2. Chen, Y., Guo, X., Yi, W., Hong, J., & Wen, Q. (2025). Synergistic pollution and carbon reductions from the China National Sustainable Communities Pilot Policy. Energy. (Citations: 5)

  3. Zheng, S., Chen, Y., Hong, J., & Pu, Y. (2025). Global climate policy effectiveness analysis: Evidence from 49 countries, 1951–2018. Journal of Comparative Policy Analysis. (Citations: 2)

  4. Chen, Y., Hong, J., Wen, Q., Yi, W., & Zheng, S. (2024). The Janus-faced role of renewable energy development in global carbon reduction under renewable energy policies. Earth’s Future. (Citations: 12)

  5. Chen, Y., Lai, T., Hong, J., & Teng, Y. (2023). Path analysis of regional carbon lock-in and unlocking from a qualitative comparative perspective. In Proceedings of the International Symposium on Advancement of Construction Management and Real Estate. (Citations: 1)

  6. Chen, Y., Zhao, Z., Yi, W., Hong, J., & Zhang, B. (2023). Has China achieved synergistic reduction of carbon emissions and air pollution? Evidence from 283 Chinese cities. Environmental Impact Assessment Review. (Citations: 18)

  7. Chen, Y., Hong, J., Tang, M., Zheng, Y., Qiu, M., & Ni, D. (2022). Causal complexity of environmental pollution in China: A province-level fuzzy-set qualitative comparative analysis. Environmental Science and Pollution Research. (Citations: 40)