Tag: Sustainable Engineering Award

Ching-Yuan Lin | Engineering | Research Excellence Award

Published on by World Science Awards

Research Excellence Award

Ching-Yuan Lin – Ten-Chen Medical Group Ten Chan General Hospital, Taiwan

Ching-Yuan Lin
Affiliation Ten-Chen Medical Group Ten Chan General Hospital
Country Taiwan
Scopus ID 57219406802
Documents 4
Citations 13
h-index 2
Subject Area Engineering
Event World Science Awards

Ching-Yuan Lin is a Taiwanese medical technologist, biomedical engineering researcher, and healthcare administrator affiliated with Ten-Chen Medical Group Ten Chan General Hospital. His work primarily focuses on cold atmospheric plasma technologies for sterilization and infection control in medical environments. With a professional background combining laboratory medicine, healthcare management, and biomedical engineering research, Lin contributes to clinical innovation by developing sterilization systems that enhance patient safety and hospital hygiene practices. His work addresses real clinical challenges such as the sterilization of sensitive medical instruments and the control of multidrug-resistant bacteria in healthcare environments [1].

Abstract

The research work of Ching-Yuan Lin focuses on the development and application of cold atmospheric plasma systems for medical sterilization and infection control. His investigations explore plasma-based technologies capable of eliminating microorganisms while preserving the integrity of delicate medical devices. Through interdisciplinary research combining biomedical engineering and laboratory medicine, Lin contributes to the design of plasma sterilization systems that enhance hospital hygiene and improve clinical safety. His work particularly addresses challenges in sterilizing medical ultrasound probes and managing multidrug-resistant bacterial contamination in clinical environments [2].

Keywords

Cold atmospheric plasma; dielectric barrier discharge; ultrasound probe sterilization; infection control; plasma sterilization; multidrug-resistant bacteria; biomedical engineering; clinical sterilization technologies.

Introduction

Advancements in biomedical engineering have enabled the development of innovative sterilization technologies designed to improve clinical hygiene and patient safety. Cold atmospheric plasma has emerged as a promising technology capable of effectively neutralizing pathogens while operating at temperatures suitable for delicate medical instruments. Ching-Yuan Lin’s research integrates plasma science with clinical laboratory applications, focusing on sterilization methods that address the growing challenge of multidrug-resistant bacteria in healthcare environments. His work contributes to the development of sterilization systems that combine efficiency, safety, and compatibility with modern medical equipment [3].

Research Profile

Ching-Yuan Lin holds a Bachelor of Science in Medical Technology from Chung Shan Medical University and a Master of Science in Medical Administration from Taipei Medical University. He is currently pursuing doctoral studies in Biomedical Engineering at Chung Yuan Christian University. Professionally, he has served as Director of the Department of Laboratory Medicine at Ten Chan General Hospital since 2011 and is scheduled to assume the role of Vice Superintendent in 2025. His leadership and professional service include acting as Secretary General of the Taiwan Association of Medical Technologists, contributing to the advancement of medical laboratory science and professional development in Taiwan [1].

Research Contributions

Ching-Yuan Lin’s research contributions focus on plasma sterilization technologies designed for real clinical applications. His work includes the development of a dual-mode plasma sterilization system that balances rapid antimicrobial action with the biological requirements of wound healing. Additionally, his research explores the application of plasma sterilization to sensitive medical equipment such as ultrasound probes, ensuring that sterilization procedures do not damage the devices while maintaining effective microbial elimination. These innovations address practical challenges encountered in hospital environments and support improved infection prevention protocols [2].

Publications

  • Peer-reviewed articles indexed in Scopus focusing on plasma sterilization and biomedical engineering applications.
  • Research studies addressing infection control using cold atmospheric plasma technologies.
  • Collaborative clinical research related to sterilization technologies and multidrug-resistant bacteria.

Research Impact

The research conducted by Ching-Yuan Lin contributes to the advancement of plasma-based sterilization technologies in healthcare environments. By developing systems capable of sterilizing delicate medical instruments without causing structural damage, his work supports safer clinical procedures and improved infection prevention strategies. The integration of plasma technology with hospital sterilization practices represents an important step toward addressing antimicrobial resistance and enhancing healthcare quality. His contributions also support interdisciplinary collaboration between biomedical engineering and clinical laboratory medicine [3].

Award Suitability

Ching-Yuan Lin’s work aligns with the objectives of the Research Excellence Award by demonstrating meaningful contributions to applied biomedical engineering and healthcare innovation. His research emphasizes practical medical applications that directly improve patient safety and clinical hygiene. Through the development of plasma sterilization technologies and leadership in laboratory medicine, Lin exemplifies interdisciplinary research that bridges engineering science and healthcare practice. Such contributions highlight the relevance of his work within global scientific and medical innovation communities.

Conclusion

The research and professional contributions of Ching-Yuan Lin demonstrate the integration of biomedical engineering innovation with practical clinical implementation. His work on plasma sterilization technologies contributes to improved infection control strategies and safer healthcare practices. By addressing challenges related to sterilization efficiency and equipment safety, his research supports the broader goals of medical engineering and public health advancement. These efforts position his work within the evolving landscape of healthcare technology and scientific recognition.

References

  1. Elsevier. (n.d.). Scopus author details: CHING-YUAN LIN, Author ID 57219406802. Scopus.https://www.scopus.com/authid/detail.uri?authorId=57219406802
  2. ORCID. (n.d.). ORCID record for CHING-YUAN LIN.https://orcid.org/0009-0009-4293-8076
  3. Laroussi, M. (2018). Cold atmospheric plasma in biomedical applications. Plasma Processes and Polymers.https://pmc.ncbi.nlm.nih.gov/articles/PMC13077500/

Feyyaz Alpsalaz | Engineering | Research Excellence Award

Published on by World Science Awards

Research Excellence Award

Feyyaz Alpsalaz
Department of Artificial Intelligence and Machine Learning, Faculty of Science and Arts, Amasya University

Feyyaz Alpsalaz
Affiliation Amasya University
Country Turkey
Scopus ID 59221704100
Documents 16
Citations 141
h-index 7
Subject Area Engineering
Event World Science Awards

Feyyaz Alpsalaz is an academic researcher affiliated with the Department of Artificial Intelligence and Machine Learning at Amasya University in Türkiye. His research integrates advanced computational intelligence with engineering systems, focusing on machine learning applications in energy systems, predictive maintenance, explainable artificial intelligence, and intelligent fault detection. His scholarly work contributes to the development of robust AI-based analytical models that enhance the reliability, monitoring, and predictive capabilities of modern technological infrastructures. His research outputs have appeared in international journals including Scientific Reports, IEEE Access, and IET Renewable Power Generation, reflecting interdisciplinary engagement across artificial intelligence, electrical engineering, and environmental monitoring systems [1].

Abstract

This article summarizes the research profile and academic contributions of Dr. Feyyaz Alpsalaz, a researcher specializing in artificial intelligence and machine learning applications in engineering systems. His work focuses on predictive analytics, hybrid machine learning models, explainable artificial intelligence, and intelligent diagnostics for power systems and environmental monitoring. Through interdisciplinary collaboration and data-driven methodologies, his studies contribute to advancements in predictive fault detection, renewable energy monitoring, and intelligent agricultural disease detection systems. The integration of deep learning, ensemble learning, and signal processing techniques within his work highlights the growing importance of AI-driven solutions in complex engineering infrastructures [1].

Keywords

  • Artificial Intelligence
  • Machine Learning
  • Explainable Artificial Intelligence
  • Fault Detection Systems
  • Renewable Energy Monitoring
  • Predictive Maintenance

Introduction

The rapid development of artificial intelligence has transformed the analysis and management of complex technological systems. Researchers across engineering and computational sciences are increasingly integrating machine learning algorithms to enhance predictive capabilities and optimize system performance. Dr. Feyyaz Alpsalaz contributes to this evolving domain by applying machine learning methodologies to energy infrastructure monitoring, environmental prediction systems, and biomedical data analysis. His research emphasizes robust hybrid models and explainable AI techniques designed to improve interpretability and reliability in high-stakes decision-making environments [2].

Research Profile

Dr. Alpsalaz conducts research at the intersection of artificial intelligence, electrical engineering, and environmental monitoring. His work explores the design of hybrid machine learning frameworks capable of identifying anomalies, forecasting environmental parameters, and diagnosing mechanical faults in complex engineering systems. His research integrates deep neural networks, ensemble learning strategies, signal processing methods, and explainable AI models to improve predictive accuracy and system interpretability. These approaches have been applied across multiple domains including renewable energy performance monitoring, power transformer diagnostics, acoustic motor fault detection, and crop disease identification using computer vision technologies [3].

Research Contributions

  • Development of hybrid machine learning models for photovoltaic power prediction and fault detection systems.
  • Application of explainable artificial intelligence methods to interpret complex deep learning models in engineering diagnostics.
  • Implementation of acoustic signal processing combined with convolutional neural networks for electric motor fault diagnosis.
  • Machine learning frameworks for environmental forecasting, particularly air quality prediction using ensemble models.
  • Deep learning-based image classification models for agricultural disease detection and plant pathology research.

Publications

  1. Hybrid Machine Learning Approach for Enhanced Fault Detection and Power Estimation in Photovoltaic Systems. IET Renewable Power Generation. DOI: https://doi.org/10.1049/rpg2.70153
  2. Hybrid Machine Learning Approach for Predicting Power Transformer Failures Using IoT Monitoring and Explainable AI. IEEE Access. DOI: https://doi.org/10.1109/access.2025.3583773
  3. Classification of Maize Leaf Diseases with Deep Learning. Chemometrics and Intelligent Laboratory Systems. DOI: https://doi.org/10.1016/j.chemolab.2025.105412
  4. Air Quality Forecasting Using Machine Learning. Water, Air, & Soil Pollution. DOI: https://doi.org/10.1007/s11270-025-08122-8
  5. Optimized ANN–RF Hybrid Model for Fault Detection in Power Transmission Systems. Scientific Reports. DOI: https://doi.org/10.1038/s41598-025-31008-y
  6. Fault Detection in Power Transmission Lines Using Machine Learning Models. Maintenance & Reliability. DOI: https://doi.org/10.17531/ein/203949
  7. Acoustic-Based Fault Diagnosis of Electric Motors Using CNNs. Scientific Reports. DOI: https://doi.org/10.1038/s41598-025-33269-z
  8. Hybrid Deep Learning with Attention Fusion for Colon Cancer Detection. Scientific Reports. DOI: https://doi.org/10.1038/s41598-025-29447-8
  9. Hybrid Deep Learning Model for Maize Leaf Disease Classification. New Zealand Journal of Crop and Horticultural Science.
  10. Detection of Arc Faults in Transformer Windings via Transient Signal Analysis. Applied Sciences. DOI: https://doi.org/10.3390/app14209335

Research Impact

The research contributions of Dr. Alpsalaz demonstrate the growing relevance of artificial intelligence in predictive engineering systems and sustainable infrastructure management. His studies integrate machine learning techniques with engineering diagnostics to improve reliability and predictive maintenance capabilities. Through publications in peer-reviewed international journals and interdisciplinary collaboration, his work supports advancements in intelligent monitoring technologies across renewable energy, agriculture, and industrial systems. These contributions illustrate the practical impact of AI-driven analytical methods in modern scientific and engineering research environments [1].

Award Suitability

Dr. Alpsalaz’s scholarly activities demonstrate interdisciplinary innovation within artificial intelligence applications for engineering systems. His work combines computational intelligence, predictive analytics, and explainable AI frameworks to address real-world challenges in energy infrastructure and environmental monitoring. The development of hybrid AI models and their implementation in applied engineering contexts highlight the relevance of his research to contemporary technological challenges. Such contributions align with the evaluation criteria commonly associated with international research recognition programs focused on artificial intelligence innovation and technological impact [3].

Conclusion

The academic profile of Dr. Feyyaz Alpsalaz reflects the integration of artificial intelligence techniques with complex engineering applications. His research emphasizes hybrid machine learning architectures, explainable AI methodologies, and predictive diagnostic systems designed to enhance reliability across multiple technological domains. As artificial intelligence continues to transform modern engineering research, contributions such as these provide valuable insights into the development of intelligent monitoring and forecasting systems capable of supporting sustainable and resilient infrastructure.

References

  1. Elsevier. (n.d.). Scopus author details: Feyyaz Alpsalaz, Author ID 59221704100. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=59221704100
  2. Google Scholar. (n.d.). Scholar profile of Feyyaz Alpsalaz.
    https://scholar.google.com.tr/citations?user=EP2ybTEAAAAJ&hl=tr&oi=ao
  3. ORCID. (n.d.). ORCID record for Feyyaz Alpsalaz.
    https://orcid.org/0000-0002-7695-6426

Asma Alfergani | Engineering | Best Researcher Award

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Ms. Asma Alfergani | Engineering | Best Researcher Award

University of Benghazi | Libya

Dr. Asma Mohamed Najem Alfergani is an accomplished researcher and emerging leader in electrical and electronics engineering, with research focus areas spanning microgrid control, renewable energy systems, communication-delay modeling, optimization techniques, and intelligent control strategies. With a scholarly record that includes 88 Scopus-indexed publications, 287 citations, and an h-index of 8, she has made notable contributions to advancing theoretical and applied research in microgrid stability, distributed control systems, and smart energy technologies. Her work demonstrates strong technical rigor, experimental validation, and interdisciplinary integration spanning renewable energy engineering, power electronics, communication networks, and computational intelligence. Dr. Alfergani has received multiple recognitions including the Libyan Innovation Prize, a Best Paper Award at IREC 2021, and top academic standing during both undergraduate and postgraduate studies, demonstrating a sustained trajectory of excellence. Beyond research, she has contributed significantly to academic leadership through curriculum development, quality assurance coordination, laboratory establishment, and supervision of numerous student research projects, further strengthening engineering education and research capacity in her institution and region. Her strengths include a strong research output trajectory, impactful publications in Q1 journals, mobility across domains such as optimization, microgrid modeling, and smart control systems, and a demonstrated ability to translate complex systems theory into implementable engineering solutions. She also shows strong collaboration potential with national and international partners, evidenced by participation in IEEE-indexed conferences and cross-institution academic engagements. Areas of improvement include expanding participation in large-scale international research consortia, increasing interdisciplinary industry partnerships, and enhancing visibility through keynote roles, invited talks, and cross-continental collaborations to amplify global research influence. Looking ahead, Dr. Alfergani possesses substantial potential to become a leading scientific voice in renewable energy systems, next-generation distributed control, and resilient microgrid architectures. With continued expansion of research networks, broader project leadership, and further engagement in policy-driven energy transformation initiatives, her research is well positioned to shape sustainable energy technologies, support energy security in developing regions, and contribute meaningfully to the global transition toward intelligent, carbon-neutral power systems.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

Khalil, A., Rajab, Z., Alfergani, A., & Mohamed, O. (2017). The impact of the time delay on the load frequency control system in microgrid with plug-in-electric vehicles.

Alfergani, A., Alfaitori, K. A., Khalil, A., & Buaossa, N. (2018). Control strategies in AC microgrid: A brief review.

Alfergani, A., Khalil, A., & Rajab, Z. (2018). Networked control of AC microgrid.

Alfergani, A., & Khalil, A. (2017). Modeling and control of master-slave microgrid with communication delay.

Alfergani, A., Khalil, A., Rajab, Z., Zuheir, M., Khan, S., & Aboadla, E. H. (2017). Control of Master-Slave Microgrid Based on CAN Bus.

Kasye Shitu Mulat | Engineering | Editorial Board Member

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Mr. Kasye Shitu Mulat | Engineering | Editorial Board Member

Anhui University | Ethiopia

Mr. Kasye Shitu Mulat is an accomplished Irrigation Engineer and GIS & Remote Sensing Specialist with extensive academic, research, and professional experience in water resources, climate change impacts, hydrological modeling, and sustainable agricultural development. Born on 02 October 1991 in Borena Mekane Selam, Ethiopia, he currently serves as a Lecturer and Researcher at Assosa University, where he contributes to teaching, scientific research, and community-centered development initiatives. Mr. Kasye earned his Bachelor of Science in Water Resource and Irrigation Management from Aksum University with Very Great Distinction (CGPA 3.64). He later completed his MSc in Irrigation Engineering at Haramaya University, achieving an “A” thesis grade and a CGPA of 3.79. Further expanding his scientific expertise, he obtained a second Master of Science in GIS and Remote Sensing from Wollo University. His multidisciplinary background positions him at the forefront of research linking climate dynamics, hydrological systems, and agricultural water management. He has authored more than 11 peer-reviewed publications and has four additional manuscripts under review in reputable international journals. His research outputs span topics such as climate change impacts on irrigation potential, hydrological modeling of river basins, statistical downscaling, kriging-based spatial analyses, land use/land cover dynamics, and soil–water interactions. His works have contributed to improving understanding of the Upper Blue Nile Basin, Borkena Catchment, and other key Ethiopian watersheds. In addition to academic research, Mr. Kasye has led impactful community engagement projects, including free-energy garden irrigation initiatives and wheat production enhancement programs across Benishangul-Gumuz. These interventions have strengthened food security, improved smallholder livelihoods, and promoted climate-resilient agricultural practices. With advanced skills in ArcGIS, SWAT, HBV, R, GAMS, CropWat, and hydrological modeling software, he collaborates with agricultural offices, university research committees, and interdisciplinary teams. His contributions continue to influence regional water resource planning, climate adaptation strategies, and sustainable development efforts in Ethiopia.

Profile: Scopus

Featured Publications

  1. (2025). Assessing drought dynamics in a semi-arid basin: A multi-index approach using hydrological and remote-sensing indicators. Environmental Sciences Europe.

Olufisayo Emmanuel Ojo | Engineering | Best Researcher Award

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Mr. Olufisayo Emmanuel Ojo | Engineering | Best Researcher Award

Durban University of Technology | South Africa

Mr. Olufisayo Emmanuel Ojo is an accomplished Electromechanical and Water Engineer with over 18 years of multidisciplinary experience spanning design, project management, and sustainable infrastructure development. His professional expertise centers on renewable energy systems, water and wastewater management, electromechanical optimization, and hydraulic modeling, areas in which he has contributed extensively to national and international engineering projects. With a portfolio of 88 scholarly documents, over 2,500 citations, and an h-index of 27, Mr. Ojo has demonstrated sustained research productivity and influence within the global engineering and sustainability community. He has served as a technical consultant and project engineer for numerous international development organizations, including the World Bank, African Development Bank (AfDB), French Development Agency (AFD), and USAID, where he played a key role in the design and implementation of large-scale water supply and renewable energy infrastructure. His work emphasizes sustainable development, energy efficiency, and resilience in engineering design, integrating both academic insight and field-based innovation. Mr. Ojo’s projects often focus on the optimization of electromechanical systems, renewable-powered desalination, and the application of smart technologies for improved water distribution and environmental performance. A chartered engineer and member of several professional institutions such as COREN, NSE, and IET (UK), he combines technical proficiency with strong leadership and policy-oriented vision. His interdisciplinary collaborations with researchers, engineers, and policymakers have resulted in impactful publications and innovative engineering solutions that address critical challenges in climate change adaptation, energy transition, and sustainable resource management. Mr. Ojo’s academic contributions, technical leadership, and international collaborations highlight his commitment to advancing global engineering standards. His work continues to inspire a new generation of engineers through the integration of research-driven innovation and practical sustainability, contributing to both societal progress and the achievement of global sustainable development goals.

Profile: ORCID

Featrued Publications

Ojo, O. E., & Oludolapo, O. A. (2025). Innovative recovery methods for metals and salts from rejected brine and advanced extraction processes—A pathway to commercial viability and sustainability in seawater reverse osmosis desalination. Water, 17(21), 3141.

Ojo, O. E., & Oludolapo, O. A. (2025). Cost–benefit and market viability analysis of metals and salts recovery from SWRO brine compared with terrestrial mining and traditional chemical production methods. Water, 17(19), 2855.

Ojo, O. E., & Oludolapo, O. A. (2025). Modeling a reverse osmosis desalination plant: A practical framework using Wave software. Science, Engineering and Technology, 5(2), Article 273.

Ojo, E. O., & Oludolapo, O. (2024). A review of renewable energy powered seawater desalination treatment process for zero waste. Water, 16(19), 2804.

Van Thinh Nguyen | Environmental Engineering | Best Researcher Award

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Prof. Dr. Van Thinh Nguyen | Environmental Engineering | Best Researcher Award

Department of Civil and Environmental Engineering, Seoul National University, South Korea

Prof. Dr. Van Thinh Nguyen is an accomplished researcher and academic leader renowned for his expertise in hydrodynamics, computational fluid dynamics (CFD), water resource management, and environmental modeling. With a strong foundation in civil and environmental engineering, his research focuses on the development and application of advanced numerical models to address complex hydrological and hydraulic challenges, particularly in flood forecasting, sediment transport, and climate change adaptation. Prof. Nguyen has authored or co-authored 78 scientific publications, which have collectively received over 807 citations, reflecting his significant scholarly influence and international recognition. His H-index of 17 underscores the sustained impact and quality of his research contributions across a range of interdisciplinary domains. Throughout his career, Prof. Nguyen has demonstrated an outstanding ability to integrate theoretical modeling with real-world applications. His work on high-performance environmental simulations and coupled hydrodynamic–atmospheric systems has advanced the understanding of water-related disasters and informed sustainable management practices. He has also been instrumental in developing innovative computational tools, including the SNU-Watershed Simulation (SNU-WS) system, widely used for hydrological predictions and climate resilience studies. His leadership in multi-institutional and international research collaborations has enabled knowledge transfer across regions, contributing to scientific capacity building and the practical application of research outcomes in diverse environmental contexts. Prof. Nguyen’s research has had substantial societal and environmental impact, influencing strategies for flood risk reduction, water resource planning, and climate-resilient infrastructure design. His collaborative engagements with academic, governmental, and industry partners have reinforced his commitment to using science for sustainable development. As an educator and mentor, he continues to inspire young researchers to pursue innovative, interdisciplinary approaches to solving global environmental challenges. Through his dedication to academic excellence, research innovation, and scientific collaboration, Prof. Dr. Van Thinh Nguyen exemplifies the role of a globally engaged scholar whose work bridges theory and practice for the betterment of society.

Profiles: Scopus | ORCID

Featured Publication

  1. Santana, M. B., Halje, P., Simplício, H., Richter, U., Freire, M. A. M., Petersson, P., … & Nicolelis, M. A. L. (2014). Spinal cord stimulation alleviates motor deficits in a primate model of Parkinson disease. Neuron, 84(4), 716–722.

  2. Freire, M. A. M., Guimarães, J. S., Gomes-Leal, W., & Pereira, A. (2009). Pain modulation by nitric oxide in the spinal cord. Frontiers in Neuroscience, 3(2), 175–181.

  3. Freire, M. A. M., Morya, E., Faber, J., Santos, J. R., Guimarães, J. S., Lemos, N. A. M., … & Nicolelis, M. A. L. (2011). Comprehensive analysis of tissue preservation and recording quality from chronic multielectrode implants. PLOS ONE, 6(11), e27554.

  4. Gomes-Leal, W., Corkill, D. J., Freire, M. A. M., Picanco-Diniz, C. W., & Perry, V. H. (2004). Astrocytosis, microglia activation, oligodendrocyte degeneration, and pyknosis following acute spinal cord injury. Experimental Neurology, 190(2), 456–467.

  5. Freire, M. A. M., Rocha, G. S., Bittencourt, L. O., Falcão, D., Lima, R. R., & others. (2023). Cellular and molecular pathophysiology of traumatic brain injury: What have we learned so far? Biology, 12(8), 1139.

Prof. Dr. Van Thinh Nguyen’s work drives global innovation in environmental engineering by integrating advanced computational modeling with sustainable water resource management. His research contributes to climate resilience, disaster mitigation, and eco-efficient infrastructure, empowering science and society to address the pressing challenges of a changing planet.

Ding Peng | Engineering | Best Researcher Award

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Assist. Prof. Dr. Ding Peng | Engineering | Best Researcher Award

Wuxi Institute of Technology, China

Assist. Prof. Dr. Ding Peng is a distinguished academic and researcher currently serving at Wuxi University of Technology (formerly Wuxi Institute of Technology), China, and plays a pivotal role at the Jiangsu Province Engineering Research Center for Energy Saving and Safety of New Energy Vehicles. He earned his Bachelor’s degree in Vehicle Engineering from Chongqing University in 2009, laying a strong foundation in mechanical and automotive systems that has guided his dynamic career in academia and industry. Following his graduation, Dr. Peng joined King Long United Automotive Industry (Suzhou) Co., Ltd. as a Design Engineer from 2009 to 2013, where he gained valuable industrial experience in the design and development of commercial buses. In 2013, he transitioned into academia as an Associate Professor at Wuxi University of Technology, where he has taught key courses such as Automobile Structure, Automobile Theory, Automatic Control Principle, and Intelligent Connected Vehicle Technologies. His primary research interests include thermal management technology for new energy vehicles, autonomous vehicle control systems, and intelligent and connected vehicle technologies (V2X), focusing on optimizing energy efficiency, safety, and intelligent communication between vehicles and infrastructure. Dr. Peng possesses advanced research skills in modeling, simulation, system optimization, and control algorithm development, coupled with extensive hands-on experience in applied engineering and industrial collaboration. He has authored Scopus-indexed papers, accumulated citations, achieved an h-index of 1, and obtained several national patents in vehicle thermal management and intelligent systems. Recognized for his dedication to innovation, he has successfully led numerous enterprise-driven and government-funded projects and guided students in academic competitions and innovation initiatives. Dr. Ding Peng’s work exemplifies the integration of research excellence and real-world engineering application, positioning him as a rising leader in the field of smart mobility and sustainable automotive engineering, committed to advancing global progress in intelligent transportation and new energy vehicle technologies.

Profile: Scopus

Featured Publications

  1. (2025). Research on interactive coupled preheating method utilizing engine-motor cooling waste heat in hybrid powertrains. Applied Thermal Engineering.

Kai Zhao | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Kai Zhao | Engineering | Best Researcher Award

Dalian Maritme University, China

Assoc. Prof. Dr. Kai Zhao is an accomplished researcher and academic at the School of Information Science and Technology, Dalian Maritime University, specializing in optoelectronic information science, micro-nano sensing, and environmental monitoring technologies. He obtained his Ph.D. in Mechanical and Mechatronics Engineering from the University of Waterloo, Canada, in 2019, and subsequently completed a postdoctoral fellowship at ETH Zurich, Switzerland, before joining Dalian Maritime University as an Associate Professor in 2020. His professional experience covers teaching and research in areas such as micro-nanophotonic integration, digital logic design, signal and image processing, and optoelectronic detection systems, coupled with leadership in advanced projects funded by the National Natural Science Foundation of China, Liaoning Provincial Foundation, and international innovation programs. Dr. Zhao’s research interests focus on micro-nano sensing and detection, microfluidic chips, artificial intelligence for micro-nano target recognition, intelligent sensing of marine micropollutants, microbial detection, clean energy, and invasive species identification, all of which reflect his commitment to sustainable marine technology and global environmental solutions. He is highly skilled in micro-nano device fabrication, photoelectric detection, signal analysis, microfluidics, and integrated circuit applications, with an impressive publication record of 36 research articles, cited over 704 times with an h-index of 15, in leading journals including Nature Communications, Environmental Pollution, Analytical Chemistry, ACS Applied Materials & Interfaces, IEEE Transactions on Instrumentation and Measurement, and Nanoscale. His academic excellence has been recognized with numerous awards and honors, such as the First Prize of Guangdong Environmental Protection Science and Technology Award (2024), the Innovation Team Award from the China Society of Naval Architecture and Shipbuilding (2023), the Science and Technology Progress Award of the China Instrument and Control Society (2022), and the National Teachers’ Teaching Innovation Competition Prize (2023). In conclusion, Dr. Zhao’s blend of strong academic foundations, pioneering research achievements, international collaborations, and leadership in both teaching and mentorship demonstrate his exceptional contributions to science, positioning him as a rising global leader in optoelectronics, micro-nano sensing, and environmental monitoring technologies.

Profiles:  Scopus | ORCID | Google Scholar | LinkedIn

Featured Publications

  1. chDing, S., Dang, Y. G., Li, X. M., Wang, J. J., & Zhao, K. (2017). Forecasting Chinese CO₂ emissions from fuel combustion using a novel grey multivariable model. Journal of Cleaner Production, 162, 1527–1538.

  2. Zhao, K., Wei, Y., Dong, J., Zhao, P., Wang, Y., Pan, X., & Wang, J. (2022). Separation and characterization of microplastic and nanoplastic particles in marine environment. Environmental Pollution, 297, 118773

  3. Zhao, K., Larasati, Duncker, B. P., & Li, D. (2019). Continuous cell characterization and separation by microfluidic alternating current dielectrophoresis. Analytical Chemistry, 91(9), 6304–6314.

  4. Alvarez, L., Fernandez-Rodriguez, M. A., Alegria, A., Arrese-Igor, S., Zhao, K., & others. (2021). Reconfigurable artificial microswimmers with internal feedback. Nature Communications, 12, 4762.

  5. Zhao, K., & Li, D. (2017). Continuous separation of nanoparticles by type via localized DC-dielectrophoresis using asymmetric nano-orifice in pressure-driven flow. Sensors and Actuators B: Chemical, 250, 274–284.

Jeng-Shin Sheu | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Jeng-Shin Sheu | Engineering | Best Researcher Award

National Yunlin University of Science & Technology, Taiwan

Assoc. Prof. Dr. Jeng-Shin Sheu is an accomplished academic and researcher serving as an Associate Professor in the Department of Computer Science and Information Engineering at National Yunlin University of Science and Technology, Taiwan. He earned his B.E. (1995) and M.E. (1997) in Electrical Engineering from National Yunlin University of Science and Technology and completed his Ph.D. in Electrical Engineering at National Chung Cheng University in 2002. Following his doctorate, he advanced his expertise as a Postdoctoral Researcher at National Chiao Tung University (2002–2006), before joining Yunlin University in 2006, where he has continued to contribute significantly to teaching, research, and industry-academia collaboration. His research interests span cellular mobile systems, audio and speech processing, and natural language processing (NLP), with strong applications in artificial intelligence and healthcare technologies. Notable projects include the AI Health Education Teaching and Assessment Robot and the Interactive AI-Powered Voice Personal Health Assistant, reflecting his commitment to leveraging AI for societal benefits. Dr. Sheu is also skilled in advanced computer engineering, signal processing, and AI-driven optimization frameworks, particularly in adaptive energy harvesting for UAV-assisted IRS systems. His contributions are substantiated by 31 research documents, 145 citations, and an h-index of 6, with publications in IEEE and other Scopus-indexed journals and conferences. His excellence has been recognized through several honors, including the prestigious Shīduó Award for Excellence in Teaching (2019) and Outstanding Teacher Awards in 2021 and 2025, showcasing his dual commitment to academic innovation and mentorship. With his strong academic foundation, leadership in research, and impactful projects, Dr. Sheu stands out as a dedicated scholar who has significantly advanced computer science and engineering. His blend of scholarly achievements, industry collaborations, and contributions to student development highlight his potential for further international research leadership and enduring impact on science, technology, and society.

Profile: Scopus

Featured Publications

  1. Developing NLP models for Taiwanese Hokkien with challenges, script unification, and language modeling. Journal of the Chinese Institute of Engineers: Transactions of the Chinese Institute of Engineers, Series A.

  2. Optimising energy harvesting and throughput for UAV-assisted IRS systems with adaptive energy harvesting. IET Communications.

  3. Taiwanese Hokkien in AI: Challenges, approaches, and language modeling. Conference paper.

Jiayi Zhang | Engineering | Best Researcher Award

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Ms. Jiayi Zhang | Engineering | Best Researcher Award

Shanghai University of Engineering Science, China

Ms. Jiayi Zhang is a talented young researcher in Clothing Design and Engineering, currently pursuing her studies at Shanghai University of Engineering Science after completing her undergraduate degree at Henan University of Engineering with an outstanding GPA of 3.89/5 and an average score of 89.22/100. Her academic training included advanced courses in garment CAD, experimental design, men’s and women’s structural clothing design, smart textiles, and professional English, with her graduation thesis titled “Style Design and Innovative Practice of Flexible Stab-proof Jacket,” reflecting her focus on functional textiles and protective clothing. Professionally, she gained valuable industry experience at Suzhou Gaojia Protection Technology Co., Ltd, where she assisted in jacket pattern making, sample preparation, and industrial drawing using CAD systems, demonstrating her ability to merge theoretical knowledge with practical garment production. Her research interests lie in smart textiles, wearable technologies, protective clothing innovation, and interdisciplinary applications such as triboelectric nanogenerators and UAV positioning systems. She has authored research outputs including a study on high-sensitivity flexible triboelectric nanogenerator sensors for monitoring sports training, showcasing her capacity to contribute to emerging fields that blend engineering and health applications. Jiayi is also proficient in specialized software such as CLO3D, AI, Photoshop, and garment CAD, enabling her to design and execute projects with both creative and technical precision. Her academic journey has been decorated with prestigious awards, including the National First Prize in the 2022 Higher Education Society Cup National College Student Mathematical Modeling Competition, third prize in Henan Province’s “Internet+” Innovation and Entrepreneurship Competition, and recognition in the “Challenge Cup” and provincial technology and art festivals, in addition to receiving the National Inspirational Scholarship. With her proven excellence in academics, research, and innovation, Jiayi Zhang is well-positioned to make impactful contributions to smart textile engineering and sustainable clothing design, establishing herself as a future leader in functional apparel research.

Profile: ORCID

Featured Publication

  1. Zhang, J., Li, Q., Li, J., Zhang, Y., Shen, Y., Zeng, L., Sun, G., & Xiao, C. (2024). High-sensitivity flexible triboelectric nanogenerator sensor based on recycled PA66 for the monitoring of soccer player lower limb training. Nano Energy, 126