Muhammad Tanveer | Energy and Sustainability | Research Excellence Award

Published on by Research Hypothesis

Assoc. Prof. Dr. Muhammad Tanveer | Energy and Sustainability | Research Excellence Award

Assoc. Prof. Dr. Muhammad Tanveer | Energy and Sustainability | Associate Professor at Imam Mohammad Ibn Saud Islamic University | Saudi Arabia

Assoc. Prof. Dr. Muhammad Tanveer is an internationally recognized scholar in management, sustainability, and digital transformation whose work bridges theory, policy, and practice across higher education and industry, and he is widely acknowledged for his global research visibility, high-impact scholarship, and leadership in academic quality assurance; he holds a Doctor of Philosophy in Management from Lincoln University College, a Master of Business Administration from Binary University, and a Master’s degree in Management from Pakistan, complemented by professional certifications and expert credentials in AACSB and NCAAA accreditation as well as Project Management Professional (PMP), reflecting a rare combination of academic depth and institutional governance expertise; his professional experience spans senior academic roles at leading AACSB- and NCAAA-accredited universities in Saudi Arabia and South Asia, where he has served highly productive researcher with authored 87 documents , 1854 Citations ,23 h-index.

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Citations
1854

Documents
87

h-index
23

🟦 Citations        🟥 Documents     🟩 h-index

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Featured Publications

The Impact of Financial Market Development and Foreign Direct Investment on Carbon Intensity from Oil, Gas, Gas Flaring, and Cement Emissions in GCC Countries: A Spatial Analysis
– Energy Strategy Reviews
The Moderating Effect of Geopolitical Risk in the Nexus Between Trade Openness, FDI, and Carbon Emissions in Saudi Arabia
– Environmental and Sustainability Indicators
Leading Green with Heart and Intelligence: Uniting AI, Emotional Intelligence, and Transformational Leadership for a Sustainable Future
– Sustainable Futures
The Green Shift: Harnessing Leadership, HR, and Culture for Sustainable Success
– Waste Management Bulletin
Unleashing the Power of Green HR: How Embracing a Green Culture Drives Environmental Sustainability
– Environmental and Sustainability Indicators

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.