Tanyo Tanev | Machine Learning | Best Researcher Award

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Mr. Tanyo Tanev | Machine Learning | Best Researcher Award

Technical University of Sofia | Bulgaria

Tanyo Tanev appears to be a highly suitable candidate for the Best Researcher Award. His exceptional blend of technical expertise, academic pursuit, and professional achievements in the renewable energy and electrical engineering domains clearly demonstrates research excellence and innovation. As a Ph.D. candidate at the Technical University of Sofia, he has published five scientific papers and is working on additional studies focused on photovoltaic (PV) power plants and the application of machine learning and deep learning models in energy systems-fields of growing global importance. Professionally, he has led the design and development of large-scale PV power plants worldwide, managing complex engineering, optimization, and data-driven simulation tasks. His strong background in Autocad, PVcase, PVsyst, Python, and AI frameworks like TensorFlow and Keras, combined with managerial experience and creative problem-solving, highlights his research-driven approach to technological advancement. Tanyo’s ability to merge academic knowledge with practical innovation, leadership in renewable energy projects, and continuous pursuit of scientific progress make him an outstanding contender for the Best Researcher Award.

Profiles: Scopus

Featured Publications

"Modeling of Battery Storage of Photovoltaic Power Plants Using Machine Learning Methods", T. Tanev and R. Stanev, Energies, 2025.

Anna Crisci | Statistics | Best Research Article Award

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Prof. Anna Crisci | Statistics | Best Research Article Award

University of Naples Federico II | Italy

Prof. Anna Crisci is a Research Associate in Statistics at the Department of Economics, Management, and Institutions of the University of Naples Federico II. She earned her PhD in Economics in 2011 at the Second University of Naples (now the University of Campania “Luigi Vanvitelli”), with a dissertation on estimation methods for structural equation models applied to innovation performance in manufacturing firms. Over the years, she has built extensive teaching experience in statistics and market research across leading Italian universities, including Federico II University of Naples, the University of Campania “Luigi Vanvitelli,” and Pegaso Telematic University, delivering both core and supplementary courses at undergraduate and postgraduate levels. She has been actively engaged in organizing and chairing sessions at prestigious international conferences, serving on scientific and organizing committees such as CLADAG 2025, ENBIS 2017, and IRSYSC 2019. Her research contributions and expertise have been recognized with the National Scientific Qualification for Associate Professor (13/D1 – Statistics), editorial board memberships for journals such as Mathematical and Computational Applications (MDPI) and Journal of Applied Quantitative Methods, and guest editorship of special issues on advanced numerical methods. A committed reviewer for high-impact journals including SEPS, Quality & Quantity, and Social Indicators Research, she is also an active member of the Italian Statistical Society and its “Statistics for the Evaluation and Quality of Services” research group. Prof. Crisci’s scholarly activity reflects a strong commitment to advancing statistical methodologies for applied research in economics, management, and social sciences.

Profiles: Orcid ID

Featured Publications

"Decomposition of the Main Effects and Interaction term by using Orthogonal Polynomials in Multiple Non Symmetrical Correspondence Analysis."

"Weighted log ratio analysis by means of Poisson factor models: a case study to evaluate the quality of the public services offered to the citizens."

"The confidence ellipses in decomposition Multiple Non- Symmetrical Correspondence Analysis."

"Estimation methods for the Structural Equation Models: Maximum Likelihood, Partial Least Squares and Generalized Maximum Entropy."

"Permutation Test for group comparison in PLS-Modeling."

Jiyoon Lee | Graph Data | Best Researcher Award

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Ms. Jiyoon Lee | Graph Data | Best Researcher Award

Ewha Womans University | South Korea

Ms. Jiyoon Lee is a doctoral researcher in Big Data Analytics at Ewha Womans University, Seoul, Korea, with expertise in graph data structures, algorithms, and GeoAI applications. Her research explores urban mobility, safety, and congestion management through advanced spatiotemporal modeling. She has presented her work at major conferences, including SIGSPATIAL 2025, where she introduced a novel GraphLSTM-Attn framework for modeling stopped vehicle dynamics on urban backstreets, and Asiacarto 2024, where she proposed a CCTV-based trajectory algorithm for road congestion and alleyway safety. Her scholarly contributions include multiple publications in the ISPRS International Journal of Geo-Information, such as studies on pedestrian congestion and safety in urban alleyways and the development of PGTFT, a lightweight graph-attention temporal fusion transformer for predicting pedestrian congestion in shadow areas. Through her innovative research at the intersection of graph data and GeoAI, she continues to advance data-driven solutions for safer and more efficient urban environments.

Profiles: Orcid ID

Featured Publications

"PGTFT: A Lightweight Graph-Attention Temporal Fusion Transformer for Predicting Pedestrian Congestion in Shadow Areas"

"Correction: Lee, J.; Kang, Y. A Dynamic Algorithm for Measuring Pedestrian Congestion and Safety in Urban Alleyways. ISPRS Int. J. Geo-Inf. 2024, 13, 434"

"A Dynamic Algorithm for Measuring Pedestrian Congestion and Safety in Urban Alleyways"

Yinyan Liu | Network Visualization | Best Researcher Award

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Dr. Yinyan Liu | Network Visualization | Best Researcher Award

The University of Sydney | Australia

Author Profiles

Scopus

Orcid ID

Google Scholar

Early Academic Pursuits

Dr. Yinyan Liu demonstrated exceptional academic aptitude from the beginning of her educational journey. She earned a Bachelor of Engineering in Measuring & Controlling Technology and Instrument from North China Electric Power University, receiving multiple scholarships for outstanding performance. She continued her studies with a Master’s in Control Engineering at Tsinghua University, where she ranked among the top 2% of students and was awarded the National Scholarship by China’s Ministry of Education. Dr. Liu further advanced her expertise by completing a Ph.D. in Electrical & Information Engineering at the University of Sydney, supported by the University of Sydney International Scholarship and a Top-up Scholarship, reflecting her strong dedication to research and innovation in engineering.

Professional Endeavors

Following her doctoral studies, Dr. Liu embarked on a distinguished career bridging academia and industry. She has served as a Lecturer at the University of Sydney, overseeing teaching, course coordination, and student supervision, while conducting cutting-edge research on energy transition and sustainability. Her prior roles include a Postdoctoral Research Associate at UNSW, algorithmic engineering in industry settings, and control engineering for power plants, reflecting a rare combination of academic rigor and practical problem-solving expertise. She has also contributed as a course developer and consultant for renewable energy companies, demonstrating her ability to translate research into actionable solutions.

Contributions and Research Focus

Dr. Liu’s research primarily focuses on integrated energy systems, distributed renewable energy, and data-driven technologies for sustainability. Her work spans the development of 100% renewable energy systems, optimization algorithms for energy management, fault detection in photovoltaic systems, and innovative business models for shared energy storage. She has also advanced methods in home energy management systems, peak price forecasting, and non-intrusive load monitoring using statistical, machine learning, and deep learning techniques. Her research blends mathematical modeling, algorithmic optimization, and empirical analysis, positioning her at the forefront of sustainable energy innovation.

Impact and Influence

Dr. Liu’s research has had significant influence both academically and industrially. She has successfully collaborated with industrial partners and universities, translating complex energy challenges into practical solutions that enhance decarbonization and energy efficiency. By co-supervising students, securing grants, and contributing to interdisciplinary courses, she has fostered knowledge transfer and skill development for the next generation of energy researchers. Her work on renewable energy integration and smart energy management has potential to inform policy, improve energy infrastructure, and support sustainable societal development globally.

Academic Citations

While specific citation metrics are not provided in the available data, Dr. Liu’s consistent contributions to high-impact projects and publications in renewable energy, energy optimization, and smart grid technologies reflect a strong academic footprint. Her research in energy system modeling, fault diagnosis, and non-intrusive load monitoring positions her as a recognized contributor in both applied and theoretical domains of electrical and renewable energy engineering.

Legacy and Future Contributions

Dr. Liu has established a legacy of combining rigorous academic research with practical, real-world applications in sustainable energy. Her future work promises to further advance renewable energy integration, enhance intelligent energy management systems, and promote decentralized, data-driven solutions to global energy challenges. Her ongoing mentorship of students and collaboration with industry partners ensures that her impact will continue to grow, inspiring future researchers and practitioners in the field.

Conclusion

Dr. Yinyan Liu exemplifies a researcher whose academic excellence, professional expertise, and innovative contributions converge to advance sustainable energy systems. Her blend of theoretical rigor, practical problem-solving, and leadership in collaborative research positions her as a leading figure in her field, with a legacy that promises enduring influence on both academia and industry.

Notable Publications

“A methodological review of cost-effective data-driven fault detection and diagnosis in distributed photovoltaic systems" 

  • Author: Yinyan Liu; Earl Duran; Anna Bruce; Baran Yildiz; Bernardo Mendonca Severiano; Ibrahim Anwar Ibrahim; Jonathan Rispler; Chris Martell; Fiacre Rougieux
  • Journal: Applied Energy
  • Year: 2025

"Economic feasibility and backup capabilities of solar-battery systems for residential customers" 

  • Author: Yinyan Liu; Baran Yildiz‏
  • Journal: Energy
  • Year: 2025

"Techno-economic optimization of electric water heater and battery energy storage for residential dwellings with rooftop PV systems" 

  • Author: Yinyan Liu; Baran Yildiz
  • Journal: Energy and Buildings
  • Year: 2025

"A Flowrate Estimation Method for Gas–Water Two-Phase Flow Based on Multimodal Sensors and Hybrid LSTM-CNN Model" 

  • Author: Yuxiao Jiang; Yinyan Liu; Baijin Mao; Xing Lu; Yi Li; Lihui Peng‏
  • Journal: IEEE Transactions on Instrumentation and Measurement‏
  • Year: 2024

"A Flow Rate Estimation Method for Gas–Liquid Two-Phase Flow Based on Transformer Neural Network" 

  • Author: Yuxiao Jiang; Hao Wang; Yinyan Liu; Lihui Peng; Yanan Zhang; Bing Chen; Yi Li
  • Journal: IEEE Sensors Journal
  • Year: 2024