Mrs. Kiane Alves e Silva | Technologies | Research Excellence Award

Mrs. Kiane Alves e Silva | Technologies | Research Excellence Award

Polytechnic University of Madrid | Spain

Mrs. Kiane Alves e Silva is a researcher specializing in photovoltaic self-consumption systems, battery storage modelling, and renewable energy communities, with a strong focus on techno-economic assessment and energy system optimization. Her work integrates simulation tools, real-world data, and innovative indicators such as the Mismatch Index to improve decision-making in sustainable energy planning. She has contributed to multiple peer-reviewed journal publications, advancing knowledge in distributed energy solutions and community-based renewable systems. Her research impact is reflected in citation metrics, including Scopus (12 citations, 2 documents, h-index 1) and Google Scholar (14 citations, h-index 2), demonstrating growing academic recognition and influence.

Citation Metrics (Scopus)

20

15

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Citations
12

Documents
2

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 Citations    Documents    h-index


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Featured Publications

Off-grid Photovoltaic Systems Implementation for Electrification of Remote Areas
– Brazilian Archives of Biology and Technology, 2023

Quasi-dynamic operation and maintenance plan for photovoltaic systems in remote areas
– Renewable Energy, 2022

Sizing Photovoltaic Self-Consumption Systems for Sustainable Decision-Making
– Sustainability, 2026

Assoc. Prof. Dr. Musa Gün | Finance | Machine Learning Research Award

Assoc. Prof. Dr. Musa Gün | Finance | Machine Learning Research Award

Associate Professor | Recep Tayyip Erdoğan University | Turkey

Assoc. Prof. Dr. MusaGün of Recep Tayyip Erdoğan University, Turkey, is an active researcher in applying machine learning techniques to finance, demonstrating impactful scholarly contributions and growing academic influence. He has achieved 170 citations overall, with 115 since 2021, reflecting consistent research relevance and visibility. His work includes 10 published documents indexed in Scopus, supported by 12 citations, and he holds an h-index of 2 in Scopus and 8 in Google Scholar. His i10-index stands at 7, indicating multiple well-cited publications.

Citation Metrics (Scopus)

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20

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Citations
12

Documents
10

h-index
2

                       🟦 Citations 🟥 Documents 🟩 h-index


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Featured Publications

Deep learning enhanced energy market prediction: A robust ARIMAX–LSTM fusion for crude oil pricing
– Journal of Computational and Applied Mathematics, 2026

Algorithmic Stability in Turbulent Markets: Shallow vs Deep Learning in Cryptocurrency Forecasting
– Mathematics, 2026

Machine Learning in Finance: Transformation of Financial Markets
– Book Chapter, 2025

Predicting Financial Distress in the Textile Industry
– Journal Article, 2025

A New Approach of Energy Financing: Green Bonds in Emerging Economies
– Book Chapter, 2021

Mr. Ghazi Abbas | Financial Engineering | Research Excellence Award

Mr. Ghazi Abbas | Financial Engineering | Research Excellence Award

Dalian Uiversity of Technology | China

Ghazi Abbas is a researcher specializing in machine learning applications in finance and economics, with a particular focus on predicting default risk and financial risk management. His work explores interpretable hybrid stacking models for multi-class loan default prediction, contributing to data-driven decision-making in financial systems. His research is recognized in international journals, accumulating citations across Google Scholar and Scopus, reflecting measurable scholarly impact, with a current h-index of 1 and total citations of 8. Ghazi’s contributions highlight the integration of advanced computational techniques into economic modeling, demonstrating strong potential for innovation in financial risk prediction and management.

Citation Metrics (Google Scholar)

15

10

5

0

Citations 8

i10-index 0

h-index 1

       🟦     Citations   🟥 i10-index   🟩 h-index


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Featured Publications

Dr. Adina Aniculaesei | Technology | Best Researcher Award

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 systemsProceedings of the 1st International Workshop on Software Engineering for AI (2018). Cited by 70
  • Towards the verification of safety‑critical autonomous systems in dynamic environmentsarXiv preprint (2016). Cited by 42
  • Automated generation of requirements‑based test cases for an adaptive cruise control systemIEEE Workshop on Validation, Analysis and Evolution of Software Tests (2018). Cited by 24
  • UML‑based analysis of power consumption for real‑time embedded systemsIEEE 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 cages5th International Symposium on Future Active Safety Technology Toward Zero Accidents (2019). Cited by 14