Zhen Guo | Renewable Energy | Editorial Board Member

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Dr. Zhen Guo | Renewable Energy | Editorial Board Member

Dr. Zhen Guo | Wuhan University of Technology | China

Dr. Zhen Guo is an emerging researcher specializing in intelligent fault diagnosis, deep learning, anomaly detection, and engineering signal processing, with emphasis on developing reliable data-driven methods for modern industrial systems. His work addresses key challenges in rotating machinery, gearboxes, propellers, and wind turbines by integrating advanced machine learning models with domain-specific signal processing techniques to enhance diagnostic accuracy under real-world constraints. Dr. Guo’s research explores multi-scale wavelet decomposition, adaptive feature fusion, and high-dimensional sampling strategies to mitigate multi-level class imbalance and improve the robustness of condition-monitoring frameworks. He has introduced innovative unsupervised anomaly detection approaches using deep convolutional support generative adversarial networks, enabling effective detection in scenarios where labeled data are insufficient or costly. His contributions also include transfer-learning architectures with channel-attention residual networks and LLM-assisted fine-tuning to achieve few-shot fault recognition in complex systems such as autonomous underwater vehicle propellers. Additionally, he has advanced wavelet-random-forest methods for modeling high-dimensional imbalance samples and proposed unified pattern-fusion strategies for mining alarm data in large-scale industrial facilities using adaptive discretization and time-clustering mechanisms. Dr. Guo’s work published in leading journals such as Mechanical Systems and Signal Processing, Scientific Reports, Ocean Engineering, Measurement, and Measurement Science and Technology demonstrates his commitment to bridging the gap between theoretical advances and practical reliability engineering. Supported by competitive research funding, he continues to design predictive frameworks that improve equipment health assessment, Remaining Useful Life estimation, and maintenance decision-making across industrial environments, contributing significantly to the advancement of intelligent diagnostic technologies.

Profile: Scopus | ORCID

Featured Publications

Guo, Z. (2025). Multi-scale wavelet decomposition and feature fusion for rotating machinery fault diagnosis under multi-level class imbalance. Mechanical Systems and Signal Processing.

Guo, Z. (2025). Unsupervised anomaly detection for gearboxes based on the deep convolutional support generative adversarial network. Scientific Reports, (Published July 1, 2025).

Guo, Z. (2025). Channel attention residual transfer learning with LLM fine-tuning for few-shot fault diagnosis in autonomous underwater vehicle propellers. Ocean Engineering.

Guo, Z. (2025). Fault diagnosis of rotating machinery with high-dimensional imbalance samples based on wavelet random forest. Measurement.

Guo, Z. (2025). Alarm data mining in complex industrial facilities using adaptive discretization based on time clustering and unified pattern fusion mining. Measurement Science and Technology, (Published January 31, 2025).

Lourdes Casas Cardoso | Green Technology | Best Researcher Award

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Prof. Dr. Lourdes Casas Cardoso | Green Technology | Best Researcher Award

Professor, Universidad de Cádiz, Spain

Prof. Dr. Lourdes Casas Cardoso is a distinguished academic and researcher specializing in supercritical fluids, advanced separation processes, and supercritical impregnation, with a strong focus on sustainable applications in the agri-food and biomedical sectors. She earned her Bachelor’s Degree in Chemistry from the Marta Abreu Central University of Las Villas (UCLV), Cuba, in 1996, followed by a Master’s in Organic Chemistry with a specialization in Natural Products from the University of Havana in 2001, a Diploma in Advanced Studies from the University of Cádiz in 2004, and a PhD from the same university in 2006. She began her academic career as a professor at UCLV, Cuba, where she served for a decade, before joining the University of Cádiz, Spain, in 2007, where she advanced from researcher to full professor. Since May 2023, she has held the position of University Professor at UCA. Her research has concentrated on the reutilization of byproducts and industrial waste using innovative separation techniques, including supercritical carbon dioxide and pressurized liquids, leading to significant advancements in green technologies. She has published 80 indexed articles, six book chapters, and participated in over 80 international conferences, accumulating 1,420 citations and an h-index of 26. She has supervised four doctoral theses, directed funded research projects, coordinated multiple industry collaborations, and co-authored three patents. Additionally, she has held leadership roles such as Coordinator of the Chemical Engineering Degree at UCA and has received recognition for excellence in teaching. Her career reflects a remarkable integration of research, teaching, and innovation.

Profile:  Scopus  |  ORCID  |  Google Scholar

Featured Publications

Otero-Pareja, M. J., Casas, L., Fernández-Ponce, M. T., Mantell, C., & de la Ossa, E. M. (2015). Green extraction of antioxidants from different varieties of red grape pomace. Molecules, 20(6), 9686–9702.

Fernández-Ponce, M. T., Casas, L., Mantell, C., Rodríguez, M., & de la Ossa, E. M. (2012). Extraction of antioxidant compounds from different varieties of Mangifera indica leaves using green technologies. The Journal of Supercritical Fluids, 72, 168–175.

Fernández-Ponce, M. T., Casas, L., Mantell, C., & de la Ossa, E. M. (2015). Use of high pressure techniques to produce Mangifera indica L. leaf extracts enriched in potent antioxidant phenolic compounds. Innovative Food Science & Emerging Technologies, 29, 94–106.

Fernández-Ponce, M. T., Parjikolaei, B. R., Lari, H. N., Casas, L., Mantell, C., & de la Ossa, E. M. (2016). Pilot-plant scale extraction of phenolic compounds from mango leaves using different green techniques: Kinetic and scale up study. Chemical Engineering Journal, 299, 420–430.

El Marsni, Z., Torres, A., Varela, R. M., Molinillo, J. M. G., Casas, L., Mantell, C., & de la Ossa, E. M. (2015). Isolation of bioactive compounds from sunflower leaves (Helianthus annuus L.) extracted with supercritical carbon dioxide. Journal of Agricultural and Food Chemistry, 63(28), 6410–6421.

Sobhan Abedi | Sustainable Building | Best Researcher Award

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Mr. Sobhan Abedi | Sustainable Building | Best Researcher Award

Researcher at Air Pollution Research Center, Iran University of Medical Sciences, Tehran, Iran

Sobhan Abedi is a dedicated Occupational Health and Safety (OHS) engineer at the Air Pollution Research Center, Iran University of Medical Sciences. With a strong academic and research foundation, he has contributed to projects involving air pollution modeling, indoor air quality, artificial intelligence, and biofiltration technologies. He is skilled in scientific writing, laboratory analysis, and Python programming. Sobhan is known for his interdisciplinary approach, combining engineering, environmental science, and data analytics to address complex challenges in public health and pollution control. His enthusiasm, collaborative mindset, and technical expertise position him as a rising expert in OHS and environmental health.

Publication Profile

Google Scholar

Orcid

Academic Background

Sobhan Abedi graduated from SAMPAD (Darab) with a diploma and pre-university degree in applied sciences. He earned his BSc in Occupational Health and Safety from Shiraz University of Medical Sciences (GPA: 16) and completed his MSc in the same field at Iran University of Medical Sciences with distinction (GPA: 18.5). His academic journey reflects a consistent focus on health engineering, environmental protection, and scientific excellence. Alongside formal education, he pursued practical and technical certifications, strengthening his competencies in air quality monitoring, data analysis, and applied research in health and environmental systems.

Professional Experience

Sobhan Abedi currently works as a Research Assistant and Air Pollution Lab Officer at Iran University of Medical Sciences. Since 2021, he has led and contributed to national and international projects involving indoor air quality, green wall systems, VOCs, and particulate matter. His professional background includes hands-on sampling, pollutant modeling, CFD simulations, and AI applications in exposure assessment. He has also served as a principal investigator, co-investigator, and project manager across research and innovation initiatives. With published work in high-impact journals, Sobhan’s expertise merges environmental engineering, health sciences, and technology-driven research.

Awards and Honors

Sobhan Abedi has received recognition for his contributions to environmental health innovation, particularly in air pollution control technologies. His patented design of a modular active green wall for phytoremediation stands out among his achievements. He was also a key contributor to several ethics-approved national projects supported by academic and governmental institutions. Throughout his academic and research career, Sobhan earned accolades for scientific writing, technological innovation, and project leadership. His active participation in high-impact publications and collaborations with top researchers reflects his ongoing commitment to academic and professional excellence.

Research Focus

Sobhan Abedi’s research centers on air pollution modeling, indoor air quality, biofiltration systems, and occupational exposure assessment. He applies AI and data science to improve predictive models and risk assessment in public health. His innovative work with botanical biofilters, green infrastructure, and CFD-based simulations seeks to enhance pollutant control in urban and industrial environments. He is particularly interested in formaldehyde exposure, BTEX compounds, and airborne particulates. Sobhan also investigates environmental impacts on cognitive health and integrates multidisciplinary tools—including Python, ANSYS, and lab analytics—to drive data-informed environmental health solutions.

Publication Top Notes

Conclusion

Sobhan Abedi is an outstanding early-career researcher in the field of Environmental and Occupational Health Engineering, with a strong track record of high-impact publications in leading Elsevier journals such as Building and Environment and Journal of Building Engineering. His innovative contributions—including patented technologies like modular botanical biofilters and green wall systems—demonstrate a blend of scientific rigor and practical impact. He has led or co-executed over 10 interdisciplinary research projects addressing critical issues like air pollution, COVID-19, and neurotoxicity. Proficient in advanced tools such as Python, ANSYS, KNIME, and SPSS, and actively collaborating with top-tier academic mentors, Abedi exemplifies a rare combination of technical depth, research innovation, and collaborative leadership—making him a highly deserving candidate for a Best Researcher Award.