Yinyan Liu | Network Visualization | Best Researcher Award

Published on by Network Science

Dr. Yinyan Liu | Network Visualization | Best Researcher Award

The University of Sydney | Australia

Author Profiles

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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

 

Linfu Jiang | Network Analysis | Best Researcher Award

Published on by Network Science

Dr. Linfu Jiang | Network Analysis | Best Researcher Award

Zhejiang Ocean University | China

Author Profile

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EARLY ACADEMIC PURSUITS

Dr. Linfu Jiang's academic journey began with a strong foundation in data science and engineering, which led him to specialize in the field of predictive modeling of medical data. His early academic years were marked by an interdisciplinary approach that combined elements of healthcare, statistics, and artificial intelligence. His education fostered a deep interest in the practical implications of machine learning and statistical methods for improving patient care, laying the groundwork for his future endeavors in intelligent health systems and clinical decision support.

PROFESSIONAL ENDEAVORS

Dr. Jiang is currently serving as a faculty member at the School of Information Engineering, Zhejiang Ocean University, where he engages in teaching and advanced research. Since joining in August 2023, he has taken a proactive role in integrating health informatics and data analytics into academic curricula while mentoring students in real-world problem-solving through data. Beyond academia, Dr. Jiang has been involved in industry collaborations, offering consultancy services in the development of predictive health platforms, community-based disease screening systems, and smart medical technologies.

CONTRIBUTIONS AND RESEARCH FOCUS ON NETWORK ANALYSIS

Dr. Jiang’s research is distinguished by his contributions to data-driven clinical prediction models that integrate both medical and social health factors. He focuses particularly on chronic disease management, intelligent health systems, and the application of machine learning for early disease detection. Notably, he co-authored and served as the first corresponding author on a groundbreaking SCI-indexed paper examining social relationships and their role in motoric cognitive risk syndrome, which utilized network analysis within a multilayer health ecology model. Another significant contribution is his work on the PCHD-TabNet, a novel deep learning model for ten-year prediction of coronary heart disease, which underscores his expertise in integrating health data with AI-driven insights.

IMPACT AND INFLUENCE

Dr. Jiang's work holds significant practical value for public health, especially in the context of community-level healthcare interventions. His research has led to the development of personalized screening tools, predictive algorithms, and smart health management platforms that are being translated into real-world healthcare applications. His emphasis on model interpretability and clinical relevance makes his work not only academically significant but also impactful in policy and practice. His collaborations with clinicians, data scientists, and public health professionals have enabled the seamless application of theory into meaningful healthcare solutions.

ACADEMIC CITES

Dr. Jiang’s scholarly influence is evident through his publications in high-impact journals. He has authored:

  • “Central and Bridging Roles of Social Relationships Within the Multilayer Health Ecology Model in Motoric Cognitive Risk Syndrome” published in Journal of the American Medical Directors Association (2025), with DOI: [10.1016/j.jamda.2025.105771], a JCR Q1 paper.

  • “Ten-Year Prediction of Coronary Heart Disease Based on PCHD-TabNet”, published in Data Analysis and Knowledge Discovery (2023), which showcases the integration of AI with health data analytics.

These contributions reflect the academic community’s growing recognition of his work, especially in healthcare AI and social determinants of health.

LEGACY AND FUTURE CONTRIBUTIONS

Looking ahead, Dr. Jiang is poised to make even greater contributions to precision medicine and digital health transformation. With three patents currently under process on predictive algorithms for chronic disease management, he continues to push the boundaries of innovation. His vision includes expanding research into social determinants of health, refining models for real-time disease prediction, and enhancing community health infrastructures using AI and network-based health ecology models. His commitment to multidisciplinary collaboration ensures that his future work will remain relevant, scalable, and deeply rooted in patient-centric outcomes.

OTHER HIGHLIGHTS

  • Industry Engagement: Active involvement in predictive health modeling for smart systems and community care.

  • Collaborative Research: Interdisciplinary work with public health experts, clinicians, and data scientists.

  • Teaching and Mentorship: Nurturing future researchers in intelligent health systems at Zhejiang Ocean University.

  • Professional Development: Actively seeking memberships in reputed medical informatics societies to extend professional influence and networks.

NOTABLE PUBLICATIONS

"Central and Bridging Roles of Social Relationships Within the Multilayer Health Ecology Model in Motoric Cognitive Risk Syndrome: A Network Analysis" 

  • Author: Liming Su; Linfu Jiang; Yiting Ma; Zhonghua Wang; Xiaoying Wang; Yang Lin
  • Journal: Journal of the American Medical Directors Association
  • Year: 2025

"Ten-Year Prediction of Coronary Heart Disease Based on PCHD-TabNet" 

  • Author: Linfu Jiang
  • Journal: Data Analysis and Knowledge Discovery
  • Year: 2023