Dr. Anton Loskutov | Energy and Sustainability | Research Excellence Award

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Dr. Anton Loskutov | Energy and Sustainability | Research Excellence Award

Dr. Anton Loskutov | Energy and Sustainability | Research Excellence Award | Dr | Nizhegorodskiy Gosudarstvennyy Tekhnicheskiy University | Research Excellence Award

Dr. Anton Loskutov is an accomplished researcher, Associate Professor, and senior scientist whose work spans electric power systems, relay protection, digital substations, smart distribution networks, and machine-learning-driven automation technologies. Dr. Anton Loskutov completed his engineering education at Nizhny Novgorod State Technical University and earned his Ph.D. from Samara State Technical University, where his research centered on developing and studying novel topologies for medium-voltage smart urban distribution networks. His professional experience includes serving as an Associate Professor in the Department of Electric Power, Electricity Supply, and Power Electronics, as well as working as a senior researcher in the laboratory for autonomous hybrid electric power systems. Throughout his role, Dr. Anton Loskutov has actively contributed to relay protection algorithms, overhead line fault-location methods, intelligent network automation, distributed generation integration, and the application of sequential statistical methods to power system decision-making. His research interests encompass electrical network simulation, data-driven energy analytics, high-voltage system protection, artificial intelligence tools for fault recognition, and the development of advanced emergency mode detection frameworks. Dr. Anton Loskutov’s research skills include computational modeling, machine learning for energy diagnostics, development of protection schemes, system optimization, sequential probability testing, and applied algorithm design for electrical networks. His work is widely published in reputed international journals such as Energies, Algorithms, Information, and Technologies, and he has coauthored multiple papers presented in IEEE conferences and Scopus-indexed proceedings. In recognition of his contribution to the field, Dr. Anton Loskutov is an active member of CIGRE, participating in the B5 subcommittee working group on relay automation modeling technologies and representing young researchers in major international sessions. His honors include selection to the youth section of CIGRE and involvement in significant collaborative power engineering projects. Dr. Anton Loskutov continues to contribute to the academic and engineering community through mentoring, interdisciplinary teamwork, and innovative applied research that enhances the safety, efficiency, and resilience of modern electrical networks. With a strong background in intelligent grid development, a robust publication record, and ongoing participation in international technical communities, Dr. Anton Loskutov stands out as a dedicated scholar whose work significantly advances the modernization of power system protection, automation, and distributed energy technologies.

Profile: Scopus | 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. Kulikov, A., Ilyushin, P., Loskutov, A., & Filippov, S. (2023). Fault location method for overhead power line based on a multi-hypothetical sequential analysis using the Armitage algorithm. Inventions.

  3. 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. Energies.

  4. Kulikov, A., Ilyushin, P., & Loskutov, A. (2023). Enhanced readability of electrical network complex emergency modes provided by data compression methods. Information.

  5. 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. Algorithms.

  6. Kulikov, A., Ilyushin, P., Loskutov, A., Suslov, K., & Filippov, S. (2022). WSPRT methods for improving power system automation devices in the conditions of distributed generation sources operation. Energies.

  7. Kulikov, A., & Loskutov, A. (2022). Relay protection and automation algorithms of electrical networks based on simulation and machine learning methods. Energies.

 

Aleksandr Kulikov | Energy and Sustainability | Research Excellence Award

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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.

 

 

Zhongjun Yan | Energy and Sustainability | Best Researcher Award

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Dr. Zhongjun Yan | Energy and Sustainability | Best Researcher Award

Dr. Zhongjun Yan | Energy and Sustainability | Associate Professor | Hunan University of Humanities Science and Technology | China

Dr. Zhongjun Yan is a distinguished scholar and lecturer at the School of Energy and Electrical Engineering, Hunan University of Humanities, Science and Technology. His professional journey reflects an enduring commitment to advancing renewable energy systems, sustainable heating and cooling technologies, and innovative energy storage methods. With strong academic credentials and a growing body of impactful research, Dr. Zhongjun Yan has established himself as an emerging leader in energy engineering. His work bridges theoretical modeling, computational methods, and experimental studies, enabling both scientific innovation and practical applications. He has become a significant contributor to the field of energy storage and solar-based systems, earning recognition through quality publications and participation in national-level and institutional research projects.

Professional Profile 

Education

Dr. Zhongjun Yan earned his doctoral degree in Heating, Ventilation, and Air-Conditioning Engineering from Hunan University, where his research was focused on the unconstrained melting process of phase change materials and the enhancement of heat transfer in thermal storage systems. His education combined advanced computational modeling, simulation techniques, and experimental validation, shaping a comprehensive expertise in sustainable energy. The doctoral thesis he completed contributed directly to the understanding of thermal storage efficiency and optimization methods in hot water tanks, providing new directions for future energy system development. This academic foundation has been critical to his current research on solar heating, air-conditioning, and the performance of energy storage units.

Experience

In his role as a lecturer, Dr. Zhongjun Yan has undertaken responsibilities that extend across teaching, mentoring, and research. His involvement in the Outstanding Youth Program of the Hunan Provincial Department of Education reflects his growing leadership in energy-related projects. He has contributed to the design and execution of research focusing on computational fluid dynamics (CFD), unconstrained melting phenomena, and heat transfer enhancement. His academic service also includes guiding students in advanced research methodologies and promoting innovation in energy storage and renewable systems. Moreover, Dr. Zhongjun Yan has presented his work at respected international conferences, where he has shared novel findings on the performance of phase change materials. Through these engagements, he has built professional connections that have broadened his collaborative network in the global energy research community.

Research Interest

Dr. Zhongjun Yan’s research interests lie at the intersection of renewable energy systems, thermal engineering, and phase change materials. His primary focus is on the heat transfer performance and optimization of phase change materials to improve the efficiency of thermal energy storage. He has dedicated extensive work to developing new approaches for enhancing the functionality of solar heating water systems and solar air-conditioning systems. Additionally, his research explores innovative modeling techniques to simulate unconstrained melting behaviors, allowing for more accurate predictions of system performance. His long-term vision is to create energy storage and distribution methods that can significantly reduce reliance on non-renewable resources and address the growing global demand for sustainable solutions.

Award

Dr. Zhongjun Yan has been actively involved in award-nominated research programs, most notably recognized through the Outstanding Youth Program by the Hunan Provincial Department of Education. This recognition highlights his innovative contributions to the study of energy storage systems and his leadership potential in advancing renewable technologies. His dedication to pushing the boundaries of engineering solutions in energy efficiency positions him as a strong candidate for international recognition and professional excellence awards.

Selected Publications

  • Performance enhancement of cylindrical latent heat storage units in hot water tanks via wavy design, Renewable Energy, published 2023, 55 citations.

  • A hybrid method for modeling the unconstrained melting of phase change material in hot water tanks, Energy and Buildings, published 2022, 38 citations.

  • Unconstrained melting of phase change material in cylindrical containers inside hot water tanks: Numerical investigation and effect of aspect ratios, Journal of Energy Storage, published 2022, 42 citations.

  • Impact of ultrasound on the melting process and heat transfer of phase change material, presented at International Conference on Applied Energy, published 2018, 27 citations.

Conclusion

Dr. Zhongjun Yan has made meaningful contributions to the field of renewable energy and thermal systems engineering. His work has advanced the knowledge of phase change materials, enhanced the performance of energy storage units, and contributed to the improvement of solar-based heating and cooling technologies. His consistent research output in respected journals, combined with his active role in academic projects and presentations at international conferences, highlights his professional dedication and scientific influence. Dr. Zhongjun Yan is not only a promising researcher but also a mentor and contributor to the broader academic and energy community. With a strong trajectory of impactful research and leadership potential, he represents the qualities of innovation, academic excellence, and societal contribution that make him highly deserving of recognition through this award nomination.

 

Minseok Ryu | Energy and Sustainability | Best Researcher Award

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Minseok Ryu | Energy and Sustainability | Best Researcher Award

Assist Prof Dr Minseok Ryu, Arizona State University, United States

Dr. Minseok Ryu is an Assistant Professor at Arizona State University’s School of Computing and Augmented Intelligence since August 2023 👨‍🏫. He earned his Ph.D. in Industrial and Operations Engineering from the University of Michigan in 2020 🎓. His research focuses on optimization and machine learning applications in power systems and privacy-preserving federated learning 🔍⚡. Dr. Ryu has held positions at Argonne National Laboratory and Los Alamos National Laboratory 🏢. He has received numerous awards, including the 2024 Alliance Fellowship at Mayo Clinic and ASU and multiple research highlights from the DOE-ASCR 🌟.

Publication profile

google scholar

Education

Minseok Ryu holds a Ph.D. in Industrial and Operations Engineering from the University of Michigan, Ann Arbor, which he completed in May 2020 🎓. Before that, he earned an M.S. in Aerospace Engineering from KAIST, Daejeon, Korea, in February 2014 🚀. His academic journey began with a B.S. in Aerospace Engineering from KAIST, which he obtained in February 2012 ✈️.

Employment

Minseok Ryu is currently an Assistant Professor at the School of Computing and Augmented Intelligence at Arizona State University in Tempe, AZ (Aug 2023–present) 📚. Previously, he was a Postdoctoral Appointee at the Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL (Aug 2020–Jul 2023) 🔬. He also worked as a Research Assistant with the Applied Mathematics and Plasma Physics Group, Los Alamos National Laboratory, Los Alamos, NM (May 2019–Aug 2019) 🧪. Additionally, he served as a Post Baccalaureate Research Fellow at the Kellogg School of Management, Northwestern University, Evanston, IL (Nov 2014–Apr 2015) 🎓.

Honors & Awards

Minseok Ryu has achieved numerous accolades throughout his career. In 2024, he was honored as an Alliance Fellow by the Mayo Clinic and ASU Alliance for Health Care and participated in the Faculty Summer Residency program. His research was highlighted by the Department of Energy’s Advanced Scientific Computing Research (DOE-ASCR) in both 2023 and 2022. Ryu received the Rackham Graduate Student Research Grant in 2016 and multiple fellowships from the University of Michigan in 2015. Additionally, he earned the National Science Foundation Student Award from INFORMS Computing Society. Earlier, he received the National Scholarship from the Korean government (2010-2013) and accolades from KAIST, including the Department Honor and Best Technical Poster Award in 2010. 🎓🔬📊

Presentations

Minseok Ryu has made significant contributions to various fields, presenting his research at numerous esteemed conferences. His work includes heuristic algorithms for geomagnetically induced current blocking devices (Paris, June 2024) 🌍⚡, generating columns (Phoenix, Oct 2023) 📝, and differentially private algorithms for constrained federated learning (Seattle and Amsterdam, 2023) 🔒🤖. He has also focused on privacy-preserving federated learning frameworks (Arlington, Aug 2022; Virtual, June 2022) 🛡️📡. Additionally, he has explored optimal power flow control, transmission expansion planning, and robust optimization in healthcare staffing across various platforms including INFORMS, SIAM, and international symposiums 🌐🧑‍⚕️

Research focus

Minseok Ryu’s research primarily focuses on data-driven optimization and privacy-preserving techniques, particularly in federated learning and power systems. His work spans several areas, including robust optimization under uncertainty, privacy-preserving distributed control, and federated learning frameworks. Key applications include improving nurse staffing models, optimizing electric grids against geomagnetic disturbances, and developing secure frameworks for federated learning in biomedical research. Ryu’s contributions are significant in ensuring privacy and robustness in distributed systems and optimization problems. 🧠🔒💡🔋👩‍⚕️

Publication top notes

Data-Driven Distributionally Robust Appointment Scheduling over Wasserstein Balls

APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning

A Privacy-Preserving Distributed Control of Optimal Power Flow

An extended formulation of the convex recoloring problem on a tree

Nurse Staffing under Absenteeism: A Distributionally Robust Optimization Approach

Differentially private federated learning via inexact ADMM with multiple local updates

Mitigating the Impacts of Uncertain Geomagnetic Disturbances on Electric Grids: A Distributionally Robust Optimization Approach

Algorithms for Mitigating the Effect of Uncertain Geomagnetic Disturbances in Electric Grids

Development of an Engineering Education Framework for Aerodynamic Shape Optimization

Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx