Adrián Alarcon | Network | Best Industrial Research Award

Published on by Environmental Scientists

Mr. Adrián Alarcon | Network | Best Industrial Research Award

Mr. Adrián Alarcon | Network | Researcher at CIRCE – Centro Tecnológico | Spain

Mr. Adrián Alarcon is a researcher specializing in smart grids and intelligent control of electrical power systems with a particular emphasis on modern network-oriented challenges associated with voltage regulation, renewable integration, and artificial intelligence applications in power engineering. Mr. Adrián Alarcon holds advanced technical education in electrical and energy systems, including graduate-level training in smart energy, data science, and related computational disciplines, positioning him at the intersection of engineering and data-driven optimization. His formal training includes master’s degrees in Smart Energy with a focus on renewable energy and digitalization and a Magister in Data Science, along with additional coursework in power system analysis, statistics, and industrial maintenance, reflecting a broad technical foundation in both theoretical and applied facets of energy systems and network control. Professionally, Mr Adrián Alarcon is currently employed as an Investigator (Smart Grid Researcher) at CIRCE – Centro Tecnológico in Zaragoza, Spain, where he leads and contributes to research projects aimed at improving voltage control and operational resilience of electrical grids, particularly through integrating artificial intelligence and neuroevolutionary approaches into classical power system control frameworks; his work involves rigorous simulation, algorithm development, and comparative analysis of machine learning and heuristic optimization techniques for autonomous grid regulation and smart network performance. Before his current role, Mr. Adrián Alarcon accumulated extensive industry experience, including technical and leadership positions in system protection, operations analysis, electrical interconnections, and teaching, demonstrating his ability to bridge academic research with real-world power engineering challenges. His research interests revolve around network-centric voltage regulation, autonomous control agents, deep reinforcement learning, and evolutionary computing applied to power systems, with a core focus on enhancing grid stability, efficiency, and adaptivity under variable renewable generation and complex operating conditions. Mr. Adrián Alarcon’s research skills encompass advanced programming (Python, C/C++), simulation environments for power systems, neural network design, comparative algorithm evaluation, and metaheuristic optimization, enabling systematic exploration of intelligent control strategies and performance benchmarking against conventional control schemes. While formal awards and honors for Mr. Adrián Alarcon’s academic work are not broadly publicly documented, his publication in a peer-reviewed journal and leadership in applied research projects reflect professional recognition within the smart grid research community. In conclusion, Mr Adrián Alarcon stands out as a dedicated engineer-scientist focused on addressing key network challenges in modern electrical systems, with a demonstrable trajectory of integrating data-driven intelligence into the evolution of smart grid technologies.

Academic Profile: ORCID

Featured Publications:

Alarcón Becerra, A., Albernaz Lacerda, V., Rocca, R., Talayero Navales, A. P., & Llombart Estopiñán, A. (2025). Comparative Study of Neuroevolution and Deep Reinforcement Learning for Voltage Regulation in Power Systems. Inventions, 10(6), 110. Published 2025. Citations: citation data not yet available / indexing pending.

 

 

Danish Khan | Engineering | Best Researcher Award

Published on by Environmental Scientists

Dr. Danish Khan | Engineering | Best Researcher Award

Research Assistant | Zhejiang University | China

Danish Khan is a dedicated researcher and engineer specializing in power systems, optimization, and machine learning applications for renewable energy. With a Ph.D. from Zhejiang University and a master’s from Shanghai Jiao Tong University, his work enhances the performance of grid-connected inverters and battery energy storage systems. Currently serving as a Postdoctoral Fellow at Hong Kong Industrial Artificial Intelligence & Robotics Centre (FLAIR), he advances smart energy systems through control design and AI integration.

Professional Profile

Scopus

Education

Danish Khan is an accomplished researcher in Electrical Engineering, specializing in power electronics and grid integration. He earned his Ph.D. from Zhejiang University (2020–2024), where his research focused on enhancing the stability of LCL-filtered grid-connected inverters a critical aspect of renewable energy systems. Prior to this, he completed his Master’s degree at Shanghai Jiao Tong University (2017–2020), conducting in-depth studies on resonance peak mitigation to improve power quality and system reliability. His academic foundation was laid at COMSATS University, Islamabad, where he earned his Bachelor’s degree in Electrical Engineering (2012–2016). Throughout his academic career, Danish has demonstrated a deep commitment to solving complex problems in energy systems through advanced modeling, control strategies, and system optimization. His work contributes significantly to the advancement of efficient and stable smart grid technologies. With strong analytical skills and a robust technical background, he stands out as a promising expert in sustainable and intelligent energy solutions.

Experience

Danish Khan brings robust hands-on research experience in AI-driven energy systems and embedded control. Currently, he is a Postdoctoral Research Fellow at FLAIR, Hong Kong, where he is actively engaged in the development of robotic-energy integration systems, merging advanced artificial intelligence techniques with power electronics. His work aims to create smarter, adaptive energy systems that align with the future of automation and sustainable technologies. Prior to this, he served as a Research Assistant at Shanghai Jiao Tong University, where he was involved in both academic and technical roles, managing lecture events and spearheading the development of novel inverter control strategies. His contributions during this time significantly advanced control techniques for power electronic converters, enhancing their performance in dynamic grid environments. Danish’s multidisciplinary expertise allows him to bridge AI, robotics, and energy systems positioning him as a valuable contributor in both academic and applied research environments focused on smart grid evolution and intelligent energy solutions.

Research Interests

Danish Khan’s research focuses on adaptive control, optimization, and machine learning within the realm of power electronics. He develops advanced control strategies for grid-connected inverters, solar photovoltaic (PV) systems, and battery energy storage solutions, aiming to enhance system efficiency and stability. His work also extends to glare analysis for infrastructure planning, addressing safety and performance concerns in renewable energy deployment. By integrating AI techniques like reinforcement learning, he strives to build intelligent, self-adaptive systems capable of responding to dynamic environmental and operational conditions. His research supports the development of resilient and efficient green technologies for sustainable energy futures.

Awards

Danish has been recognized with several prestigious awards, including the Chinese Government Scholarship for his Ph.D., the National Endowment Scholarship for Talent during his master’s, and the HEC Pakistan Scholarship for his undergraduate studies. He received a Bronze Medal from COMSATS and an Excellent Oral Presentation Award at an international conference in Shanghai (2019).

Top Noted Publications

Title: Enhanced Stability of Grid-Connected Inverter Using Adaptive Filtering Damping
Year: 2025
Cited by: 12

Title: A Reinforcement Learning-Based Control System for Higher Resonance Frequency Conditions
Year: 2024
Cited by: 17

Title: Half-Quadratic Criterion-Based Adaptive Control for Robust LCL-Filtered Inverter
Year: 2024
Cited by: 10

Title: Optimal LCL-Filter Design Using Metaheuristic Algorithms
Year: 2023
Cited by: 29

Title: Loss Reduction in Isolated Series Resonant Converter
Year: 2022
Cited by: 35

Title: Capacitor Current Resonance Suppression Using ASPR Plant Concept
Year: 2022
Cited by: 28

Conclusion

Danish Khan is a promising and technically advanced researcher whose work addresses some of the most pressing challenges in modern electrical power systems and renewable energy integration. With a solid research portfolio, strong publication record, hands-on experience, and international education, he stands out as a suitable candidate for the Best Researcher Award especially in emerging areas such as AI-powered energy systems and adaptive inverter control.