Dr. Adina Aniculaesei | Technology | Best Researcher Award

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Dr. Adina Aniculaesei | Technology | Best Researcher Award

Dr. Adina Aniculaesei , Postdoctoral Researcher, Department of Computer Science and Engineering, University of Gothenburg and Chalmers University of Technology, Sweden.

Adina Aniculăesei is a passionate researcher and expert in automated safety‑critical systems, currently based in Gothenburg, Sweden. Born in Iași, Romania, she has dedicated her career to making autonomous vehicles and mobile robots safer, focusing on verification, formal methods, and runtime validation. Through years of multidisciplinary research and teaching, she has shaped the future of software engineering for intelligent transportation and collaborative robotics. Her deep knowledge of formal verification and system modeling has positioned her as a leading voice in the realm of dependable and trustworthy autonomous platforms, making significant impacts in both academia and industry.

Publication Profile

Google Scholar

🎓 Education Background

Adina earned her Doctorate (Dr. rer. nat.) in Computer Science from the Clausthal University of Technology, Germany, in 2024, graduating magna cum laude. She holds an M.Sc. in Computer Science from the Technical University of Braunschweig (2011) and a B.Sc. in Computer Science from Alexandru Ioan Cuza University, Romania (2007). An Erasmus–Socrates scholar, she enriched her studies with a year at the Technical University of Braunschweig. Her rigorous training combined formal methods, software engineering, and automated test case generation, making her adept at tackling complex, safety‑critical domains.

💼 Professional Experience

Adina Aniculăesei has worked as a Postdoctoral Researcher at the University of Gothenburg and Chalmers University of Technology (since October 2024), focusing on translating formal behavioral specifications into ROS2 nodes for collaborative robot applications. Previously, she served as a Doctoral Researcher and Research Assistant at TU Clausthal, leading industry collaborations, teaching, and mentoring students. Her experience includes roles across software and systems engineering, with a strong focus on safety, formal verification, and automated test generation for automotive and robotics domains, making her a sought‑after expert and educator in the field.

🏅 Awards and Honors

Throughout her academic journey, Adina Aniculăesei has been recognized for excellence and dedication. She received the Siemens Master Program Scholarship (2007–2009) and the Erasmus–Socrates Scholarship (2005–2006). Her doctoral studies earned her the magna cum laude distinction upon defending her Ph.D. thesis at Clausthal University of Technology in 2024. Additionally, she holds technical certifications including ISAQB Certified Professional for Software Architecture and ISTQB Certified Tester Foundation Level, highlighting her commitment to mastering both theoretical and practical elements of her field.

🔍 Research Focus

Adina Aniculăesei’s research centers on formal verification, automated test generation, and runtime monitoring for automated safety‑critical and collaborative multi‑agent systems. She explores methods for specifying, verifying, and validating complex operational design domains (ODDs) for autonomous vehicles and mobile robots. Her expertise includes formal methods (SPIN, NuSMV, PRISM), test case generation, model checking, and AI‑based environment perception, making her work pivotal in shaping next‑generation transportation and robotics technologies.

✅ Conclusion

With a profound background in formal methods, automated test generation, and verification of safety‑critical systems, Adina Aniculăesei has established herself as an influential expert in both academia and industry. Her dedication to mentoring students, publishing impactful research, and collaborating with international institutions has positioned her as a thought leader in software engineering for dependable, trustworthy, and safe autonomous technologies.

📚 Publication Top Notes

  • Towards a holistic software systems engineering approach for dependable autonomous systems – Proceedings of the 1st International Workshop on Software Engineering for AI (2018). Cited by 70
  • Towards the verification of safety‑critical autonomous systems in dynamic environments – arXiv preprint (2016). Cited by 42
  • Automated generation of requirements‑based test cases for an adaptive cruise control system – IEEE Workshop on Validation, Analysis and Evolution of Software Tests (2018). Cited by 24
  • UML‑based analysis of power consumption for real‑time embedded systems – IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications (2011). Cited by 24
  • Graceful degradation of decision and control responsibility for autonomous systems based on dependability cages – 5th International Symposium on Future Active Safety Technology Toward Zero Accidents (2019). Cited by 14

 

Liangdong Zhao | Energy | Best Researcher Award

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Dr. Liangdong Zhao | Energy | Best Researcher Award

PhD, Huazhong University of Science and Technology China

Liangdong Zhao is a first-year PhD student at the School of Energy and Power Engineering, Huazhong University of Science and Technology (HUST), Wuhan, China. His research is focused on innovative catalyst development for hydrogen production via methanol reforming, especially under low-temperature conditions. Passionate about advancing sustainable energy technologies, Liangdong is exploring non-platinum-based anode catalysts tailored for direct methanol fuel cells. His early work has already led to one SCI-indexed journal publication, a patent submission, and an industry-linked research project. With growing expertise in catalysis and clean energy systems, he is contributing to breakthroughs in alcohol-hydrogen engine compatibility, positioning his work at the forefront of hydrogen energy innovation. Liangdong combines academic rigor with practical relevance, aiming to revolutionize hydrogen-based fuel alternatives for real-world applications. He is currently preparing more outputs that demonstrate high international standards and practical significance in the global energy transition landscape.

Publication Profile

ORCID

🎓 Education

Liangdong Zhao is currently pursuing his PhD in Energy and Power Engineering at Huazhong University of Science and Technology (HUST), one of China’s top research institutions in the energy domain. Enrolled in 2024, he has chosen to specialize in catalyst development for hydrogen production and clean fuel applications. Prior to his doctoral studies, Liangdong completed his undergraduate and/or master’s studies (specifics not provided) in fields likely aligned with chemical or energy engineering, equipping him with foundational knowledge in thermodynamics, materials science, and fuel cell technologies. At HUST, he benefits from state-of-the-art laboratories and expert faculty supervision, which support his advanced research into non-platinum catalysts and low-temperature methanol reforming systems. His academic journey reflects a strong commitment to addressing global energy challenges through rigorous scientific inquiry and innovation. Zhao’s training continues to emphasize applied research, combining theoretical frameworks with practical problem-solving in energy systems and materials engineering.

💼 Experience

As a PhD student, Liangdong Zhao has engaged in both academic research and industry-related work since 2024 at the School of Energy and Power Engineering, Huazhong University of Science and Technology. Though early in his career, he has already participated in one research project and contributed to a consultancy/industry project, demonstrating an ability to translate scientific knowledge into real-world applications. His hands-on experience in designing catalysts for hydrogen production and testing under operational conditions reflects both laboratory precision and field relevance. Zhao is also involved in the synthesis and evaluation of non-platinum anode catalysts for direct methanol fuel cells, a key step toward sustainable and cost-effective hydrogen energy solutions. His contributions extend to experimental design, data interpretation, and material characterization. He has also co-authored a peer-reviewed article in an SCI journal and is the applicant for a related patent, further underlining his early yet impactful career trajectory in energy research.

🏅 Awards and Honors

Although Liangdong Zhao is in the early stages of his academic journey and has not yet received formal honors or awards, his achievements reflect strong potential for future recognition. His research has already resulted in a peer-reviewed SCI publication in Catalysts (DOI: 10.3390/catal15050478), marking an important milestone for a first-year PhD student. Additionally, his work has led to a patent submission, indicating originality and applicability in his innovations. His involvement in an industry-linked research project is also notable, suggesting early trust in his technical competencies. Zhao’s nomination for the Best Researcher Award is a testament to his contributions and growing impact in the field of sustainable energy research. As he continues to publish and expand his research collaborations, further accolades are expected. His dedication to solving real-world energy problems through catalytic innovation and clean fuel development places him in a promising position for future academic honors.

🔬 Research Focus

Liangdong Zhao’s research focuses on catalyst development for hydrogen production via low-temperature methanol cracking, a promising approach for sustainable fuel alternatives. His work emphasizes creating non-platinum-based anode catalysts for direct methanol fuel cells (DMFCs), which are more cost-effective and efficient under actual engine operating conditions. He aims to improve catalytic performance while ensuring stability and scalability. Zhao is particularly interested in enhancing the viability of alcohol-hydrogen engines by tailoring catalysts that perform optimally in realistic thermal and chemical environments. His current research has produced advanced catalyst materials that demonstrate high conversion efficiency and durability. These innovations have significant implications for green hydrogen generation, low-emission transport systems, and decentralized energy solutions. His contributions aim to bridge the gap between laboratory-scale breakthroughs and real-world industrial adoption, supporting global efforts toward decarbonization and clean energy transitions.

🌟Conclusion 

In conclusion, Mr. Liangdong Zhao exhibits the characteristics of a future research leader in energy engineering. His innovative contributions in hydrogen catalyst research and commitment to practical applications make him a strong nominee for the Best Researcher Award. With continued mentorship and exposure, he is well-positioned to contribute significantly to the field and become an influential voice in sustainable energy solutions.

📚 Publication Top Note

  • Title: Sustainable Hydrogen from Methanol: NiCuCe Catalyst Design with CO₂-Driven Regeneration for Carbon-Neutral Energy Systems

  •  Year: 2025

  •  Authors: Yankun Jiang, Liangdong Zhao, Siqi Li

  •  Link (DOI): https://doi.org/10.3390/catal15050478

 

Dr. Dawei Qiu | Smart Grid | Best Researcher Award

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Dr. Dawei Qiu | Smart Grid | Best Researcher Award

Lecturer, University of Exeter, United Kingdom

Dr. Dawei Qiu is a distinguished scholar in smart energy systems, currently serving as a Lecturer at the University of Exeter, UK 🏫. With a strong background in electrical engineering and power systems, he specializes in AI-driven reinforcement learning, market design for low-carbon energy transition, and resilience enhancement of energy systems ⚡. His extensive research contributions in smart grids and power systems have earned him recognition in academia, with a Google Scholar citation count of 2,109, an h-index of 24, and an h10-index of 35 📊.

Publication Profile

Google Scholar

🎓 Education

Dr. Qiu holds a Ph.D. in Electrical Engineering from Imperial College London (2016–2020) 🎓, where he conducted pioneering research on local flexibility’s impact on electricity retailers under the supervision of Prof. Goran Strbac. Prior to this, he completed his M.Sc. in Power System Engineering from University College London (2014–2015) and obtained his B.Eng. in Electrical and Electronic Engineering from Northumbria University at Newcastle (2010–2014) ⚙️. His academic journey has been shaped by esteemed mentors, including Dr. Ben Hanson and Dr. Zhiwei (David) Gao, IEEE Fellow.

💼 Experience

Dr. Qiu’s professional career spans academia and research institutions, where he has contributed significantly to energy systems innovation 🌍. Before joining the University of Exeter in 2024, he was a Research Fellow at Imperial College London (2023–2024), specializing in market design for low-carbon energy systems. He also served as a Research Associate at the same institution from 2020 to 2023 🔬. His work in smart grids and energy resilience has been instrumental in shaping sustainable and intelligent power infrastructure.

🏆 Awards and Honors

Dr. Qiu’s research excellence has been acknowledged through various accolades 🏅. His contributions to smart energy systems, AI-driven reinforcement learning, and low-carbon market design have positioned him as a leading researcher in the field. His studies have been published in top-tier journals, and his work has received high citations, demonstrating its impact on the global research community 🌟.

🔬 Research Focus

Dr. Qiu’s research is centered on leveraging artificial intelligence and reinforcement learning for power and energy applications 🤖. His work explores market mechanisms for cost-effective and sustainable energy transitions, as well as the resilience enhancement of energy systems in response to climate change 🌍. His expertise in AI-driven optimization and machine learning applications in energy systems makes him a key contributor to the advancement of smart grid technologies.

🔚 Conclusion

Dr. Dawei Qiu is a leading researcher in smart energy systems, with a strong academic background and impactful contributions to power systems engineering 🔬. His expertise in AI-driven market optimization, reinforcement learning, and resilient energy systems has made him a valuable asset to the research community 🌍. With his ongoing work at the University of Exeter, he continues to drive innovation in low-carbon and intelligent energy solutions ⚡.

🔗 Publications

A knowledge-based safe reinforcement learning approach for real-time automatic control in a smart energy hub – Applied Energy (Under review, 2025) 🔗 Link

Enhanced Meta Reinforcement Learning for Resilient Transient Stabilization – IEEE Transactions on Power Systems (Under review, 2025) 🔗 Link

Machine learning-based economic model predictive control for energy hubs with variable energy efficiencies – Energy (First round revision, 2024) 🔗 Link

A Review of Resilience Enhancement Measures for Hydrogen-penetrated Multi-energy Systems – Proceedings of the IEEE (Under review, 2025) 🔗 Link

Coordinated Optimal Dispatch Based on Dynamic Feasible Operation Region Aggregation – IEEE Transactions on Smart Grid (First round revision, 2024) 🔗 Link

A Sequential Multi-Agent Reinforcement Learning Method for Coordinated Reconfiguration of Substation and MV Distribution Networks – IEEE Transactions on Power Systems (Under review, 2024) 🔗 Link

Enhancing Microgrid Resilience through a Two-Layer Control Framework for Electric Vehicle Integration and Communication Load Management – IEEE Internet of Things Journal (Under review, 2024) 🔗 Link

Coordinated Electric Vehicle Control in Microgrids Towards Multi-Service Provisions: A Transformer Learning-based Risk Management Strategy – Energy (Under review, 2024) 🔗 Link

Adaptive Resilient Control Against False Data Injection Attacks for a Multi-Energy Microgrid Using Deep Reinforcement Learning – IEEE Transactions on Network Science and Engineering (Under review, 2024) 🔗 Link