Kusnandar | Engineering | Research Excellence Award

Published on by Top Teachers

Research Excellence Award

Kusnandar
National Research and Innovation Agency, Indonesia

Kusnandar
Affiliation National Research and Innovation Agency
Country Indonesia
Scopus ID 57217677745
Documents 7
Citations 55
h-index 4
Subject Area Engineering
Event Top Teachers Awards
Google Scholar kbNqvhgAAAAJ

Kusnandar is an Indonesian engineering researcher and academic specialist recognized for contributions to thermal systems, refrigeration engineering, HVAC technologies, energy modeling, and sustainable thermal management. His interdisciplinary research integrates numerical simulations, machine learning methods, experimental validation, and energy-efficient system design for manufacturing environments and building applications. His scholarly works have addressed thermal compensation techniques, cooling optimization, machine tool thermal behavior, and sustainable energy management systems in industrial and educational infrastructure.[1][2]

Abstract

This article documents the academic and research achievements of Kusnandar in the field of engineering, with emphasis on thermal systems, refrigeration technologies, computational modeling, and energy-efficient building applications. His work combines experimental methods, machine learning approaches, CFD simulations, and energy optimization techniques for industrial and institutional environments. Through collaborative research in Indonesia and Taiwan, he has contributed to sustainable cooling systems, thermal compensation in machine tools, and HVAC performance enhancement. His scholarly publications and technical engagements demonstrate interdisciplinary integration between manufacturing systems, thermal sciences, and energy engineering.[3][4]

Keywords

Thermal Systems, HVAC Engineering, Refrigeration, Heat Transfer, Machine Learning, CFD Simulation, Sustainable Cooling, Energy Modeling, Experimental Validation, Manufacturing Systems, Energy Efficiency, Thermal Compensation.

Introduction

Engineering research related to energy conservation and thermal management has become increasingly important in industrial manufacturing, educational infrastructure, and sustainable urban systems. Kusnandar has contributed to this field through investigations involving refrigeration systems, HVAC optimization, thermal behavior in machine tools, and predictive modeling using data-driven methods. His academic profile reflects a combination of engineering practice, industrial collaboration, and applied computational analysis.[5]

He obtained a Ph.D. from the Graduate Institute of Precision Manufacturing at National Chin-Yi University of Technology (NCUT), Taiwan, after completing graduate and undergraduate studies in mechanical engineering in Indonesia. His research trajectory integrates thermal engineering with computational and machine learning techniques, particularly in relation to energy efficiency and sustainable manufacturing systems.[6]

Research Profile

Kusnandar has developed expertise across multiple engineering domains involving heat transfer, thermal systems, and energy-efficient infrastructure. His research profile demonstrates the integration of experimental investigations with computational modeling and industrial applications. The majority of his research focuses on thermal management systems, energy conversion, and predictive analysis for manufacturing and building environments.[7]

  • Thermal Systems, Energy Conversion, Refrigeration, HVAC, and Heat Transfer.
  • Numerical Modeling using CFD, FEM, and hybrid thermal simulation techniques.
  • Machine learning applications for predictive thermal behavior analysis in machine tools.
  • Sustainable cooling technologies and renewable energy integration.
  • Experimental validation, sensor integration, and thermal monitoring systems.

In addition to academic research, he has participated in commissioning systems and energy audit projects in Taiwan involving hotels, hospitals, biotechnology facilities, and cleanroom environments. These collaborative activities expanded his expertise in HVAC balancing, energy performance testing, and industrial thermal optimization.[8]

Research Contributions

Kusnandar’s research contributions are primarily associated with sustainable thermal management, building energy optimization, refrigeration engineering, and machine tool thermal analysis. His studies frequently combine field measurements, simulation frameworks, and machine learning prediction models to improve engineering efficiency and operational stability.[9]

  • Development of predictive thermal compensation models for machine tool systems using machine learning techniques.
  • Research on coupling air conditioning systems with refrigeration showcase equipment for energy-efficient retail environments.
  • Energy-efficient retrofitting approaches for institutional hot water heating systems.
  • Investigation of industrial enclosure cooling performance and thermal stability enhancement.
  • Energy modeling and field measurement analysis for university and manufacturing buildings.

His applied engineering research demonstrates practical relevance to industrial sustainability and energy conservation initiatives, particularly in manufacturing systems and educational facilities. The interdisciplinary nature of his work supports broader engineering objectives involving environmental performance and operational reliability.[10]

Publications

Kusnandar has authored and co-authored research publications in internationally recognized engineering and energy journals. His publication record demonstrates continuing engagement with thermal engineering, machine tool analysis, and energy efficiency research.[11]

  1. Kusnandar, Nasril, Danny M Gandana, Agus Widodo, and Galang I Islami. “Thermal environment effect on machine tool ball screw based on experimental investigation and numerical simulation via machine learning prediction.” Journal of Engineering, 2026. DOI: https://doi.org/10.1155/je/6435980
  2. Kusnandar, Nasril, Danny M Gandana, Agus Widodo, and Galang I Islami. “A review of thermal effect and compensation techniques in machine tools.” Scientia Iranica, 2025 (Under Review).
  3. Kusnandar, Luo W. J., Permana I., Wang F. J., and Bayarkhuu G. “Energy Efficient for a Machine Tool Building in a University through Field Measurement and Energy Modelling.” Energy Engineering, 2023, Vol. 120(6), pp. 1387–1399. DOI: https://doi.org/10.32604/ee.2023.027459
  4. Kusnandar, Permana I., Chiang W. M., Wang F. J., and Liou C. “Energy Consumption Analysis for Coupling Air Conditioners and Cold Storage Showcase Equipment in a Convenience Store.” Energies, 2022, 15(13), 4857. DOI: https://doi.org/10.3390/en15134857
  5. Chiang W. M., Wang F. J., and Kusnandar. “Performance improvement of an industrial control enclosure cooling system.” Thermal Science, 2022, Vol. 26(3A), pp. 2043–2052. DOI: https://doi.org/10.2298/TSCI201205177C
  6. Wang F. J., Kusnandar, Lin H., and Tsai M. “Energy Efficient Approaches by Retrofitting Heat Pumps Water Heating System for a University Dormitory.” Buildings, 2021, Vol. 11, 356. DOI: https://doi.org/10.3390/buildings11080356

Research Impact

The research impact associated with Kusnandar’s academic work is reflected in the integration of energy-efficient engineering methods with sustainable manufacturing and building operation systems. His publications address practical industrial challenges related to thermal instability, cooling efficiency, and energy consumption reduction.[12]

His studies involving machine tool thermal behavior contribute to manufacturing precision and operational reliability, while his building energy modeling research supports improved environmental performance and energy conservation strategies. The application of machine learning within thermal engineering also demonstrates the growing role of intelligent predictive systems in engineering analysis.[13]

Award Suitability

Kusnandar’s academic background, international research collaborations, engineering publications, and contributions to sustainable thermal management support his suitability for recognition through the Top Teachers Awards. His work demonstrates a combination of research productivity, educational engagement, and applied engineering innovation within the broader field of energy and thermal systems engineering.[14]

His professional experience includes teaching, institutional leadership, postdoctoral research, and industrial collaboration across Indonesia and Taiwan. The integration of academic scholarship with real-world engineering applications reflects a sustained contribution to engineering education and technological development.[15]

Conclusion

Kusnandar represents an engineering academic whose research activities contribute to advancements in thermal systems, energy-efficient technologies, refrigeration engineering, and computational thermal analysis. Through scholarly publications, interdisciplinary methodologies, and international collaborative activities, he has participated in the development of sustainable engineering solutions relevant to manufacturing and building environments. His academic profile aligns with contemporary engineering priorities emphasizing sustainability, efficiency, and intelligent thermal management systems.[16]

References

  1. Elsevier. (n.d.). Scopus author details: Kusnandar, Author ID 57217677745. Scopus. https://www.scopus.com/authid/detail.uri?authorId=57217677745
  2. Google Scholar. (n.d.). Kusnandar citation profile and scholarly metrics. https://scholar.google.com/citations?hl=id&user=kbNqvhgAAAAJ
  3. Kusnandar et al. (2026). Thermal environment effect on machine tool ball screw based on experimental investigation and numerical simulation via machine learning prediction. https://doi.org/10.1155/je/6435980
  4. Kusnandar et al. (2023). Energy Efficient for a Machine Tool Building in a University through Field Measurement and Energy Modelling. https://doi.org/10.32604/ee.2023.027459
  5. Energies Journal. (2022). Energy Consumption Analysis for Coupling Air Conditioners and Cold Storage Showcase Equipment in a Convenience Store. https://doi.org/10.3390/en15134857
  6. National Chin-Yi University of Technology. (n.d.). Graduate Institute of Precision Manufacturing academic records.
  7. Research profile documentation relating to HVAC engineering, thermal systems, CFD simulations, and machine learning applications in engineering systems.
  8. Industry collaborative project records involving commissioning systems, energy audits, and HVAC balancing activities in Taiwan from 2019–2023.
  9. Thermal Science. (2022). Performance improvement of an industrial control enclosure cooling system. https://doi.org/10.2298/TSCI201205177C
  10. Buildings Journal. (2021). Energy Efficient Approaches by Retrofitting Heat Pumps Water Heating System for a University Dormitory. https://doi.org/10.3390/buildings11080356
  11. Publication data compiled from Scopus indexing and Google Scholar author records.
  12. Engineering research concerning sustainable thermal management and energy optimization systems in manufacturing environments.
  13. Research applications involving machine learning integration in predictive thermal engineering systems.
  14. Top Teachers Awards. (n.d.). Academic recognition and global teaching excellence platform. https://topteachers.net/
  15. Professional records relating to teaching, academic administration, and postdoctoral research appointments in Indonesia and Taiwan.
  16. Comprehensive academic summary compiled from publication records, institutional affiliations, and engineering research activities.

Fazal e Wahab | Engineering | Innovative Research Award

Published on by Top Teachers

Innovative Research Award

Fazal e Wahab
Hubei Polytechnic University
Fazal e Wahab
Affiliation Hubei Polytechnic University
Country China
Scopus ID 57216410031
Documents 14
Citations 111
h-index 7
Subject Area Engineering
Event Top Teachers Awards
ORCID 0000-0003-4827-170X
Google Scholar 8t4Pxo8AAAAJ

Fazal e Wahab is an academic researcher and engineering educator affiliated with Hubei Polytechnic University, China. His scholarly work primarily focuses on speech enhancement, signal processing, machine learning applications, and low-latency intelligent systems for embedded and edge computing environments. Over the course of his academic and professional career, he has contributed to research in audio-visual speech enhancement, real-time denoising systems, neural network optimization, and applied engineering technologies. His publications in internationally indexed journals and conferences demonstrate sustained engagement with contemporary developments in communication engineering and intelligent multimedia systems.[1]

Abstract

This academic article documents the scholarly profile, research achievements, and educational contributions of Fazal e Wahab in the field of engineering and intelligent signal processing. His work addresses challenges associated with speech enhancement, audiovisual communication systems, and machine learning implementation for resource-constrained edge devices. Through interdisciplinary research involving signal processing, neural networks, embedded systems, and audio enhancement technologies, he has contributed to practical and computationally efficient methods for real-time communication systems. His publication record includes SCI-indexed journal articles, conference proceedings, funded engineering projects, and collaborative international research activities.[2]

Keywords

Speech Enhancement, Signal Processing, Edge Computing, Deep Learning, Audio-Visual Systems, Engineering Education, Machine Learning, Embedded Systems, Real-Time Denoising, Communication Engineering.

Introduction

The development of intelligent speech processing systems has become increasingly important in modern communication engineering, particularly in environments requiring low-latency and computationally efficient solutions. Researchers working in this field address technical challenges associated with noise suppression, speech intelligibility, audio enhancement, and multimodal communication systems. Fazal e Wahab has participated in this evolving research area through studies focused on lightweight neural architectures, edge-device optimization, and robust audiovisual speech enhancement frameworks.[3]

In addition to research activities, he has contributed extensively to university-level engineering education through undergraduate teaching, curriculum development, laboratory instruction, and supervision of student innovation projects. His academic trajectory includes higher education and research engagement in Pakistan and China, reflecting international academic collaboration and interdisciplinary engineering practice.[4]

Research Profile

Fazal e Wahab completed a Ph.D. in Information and Communication Engineering at the University of Science and Technology of China (USTC) in 2025. His doctoral research focused on optimized lightweight deep learning models for real-time single-channel speech enhancement systems. His investigations emphasized computational efficiency, streaming denoising, echo cancellation, and dereverberation systems applicable to edge and embedded hardware environments.[5]

His academic experience also includes an M.S. in Electrical Engineering from CECOS University and a B.S. in Electronic Engineering from Dawood University of Engineering and Technology. Professionally, he has served as a lecturer, researcher, engineering instructor, and instrumentation engineer, contributing both to industrial engineering operations and university-level technical education.[6]

  • Research specialization in speech enhancement and audio signal processing.
  • Experience in machine learning for edge and embedded systems.
  • Academic supervision of funded engineering projects and applied research.
  • Participation in international scientific collaboration and peer review activities.

Research Contributions

The research contributions of Fazal e Wahab are associated with efficient speech enhancement systems using lightweight neural network architectures. His studies investigate methods for reducing computational complexity while maintaining speech intelligibility and enhancement quality in real-time applications. This area of research is particularly relevant for embedded systems, mobile communication technologies, and assistive audio interfaces.[7]

His published work includes investigations into gated convolutional recurrent neural networks, dual-transformer architectures, multimodal audiovisual processing systems, and adaptive deep learning techniques for speech enhancement. Several publications focus on resource-constrained devices and edge deployment scenarios, demonstrating applied relevance in consumer electronics and intelligent communication technologies.[8]

  • Development of lightweight deep learning models for speech enhancement.
  • Research on audio-visual speech enhancement frameworks using transformer architectures.
  • Optimization of neural systems for edge and embedded devices.
  • Contribution to intelligent signal processing and real-time communication systems.
  • Supervision of funded engineering innovation and assistive technology projects.

Publications

The publication record of Fazal e Wahab includes journal articles and conference papers indexed in SCI, EI, and Scopus databases. His publications span topics related to speech enhancement, multimedia systems, signal processing, energy systems, and intelligent engineering applications.[9]

  1. “Lightweight Adaptive Deep Learning for Efficient Real-Time Speech Enhancement on Edge Devices,” IEEE Transactions on Consumer Electronics, 2025.
  2. “Compact Deep Neural Networks for Real-Time Speech Enhancement on Resource-Limited Devices,” Speech Communication, 2024.
  3. “Efficient Gated Convolutional Recurrent Neural Networks for Real-Time Speech Enhancement,” International Journal of Interactive Multimedia and Artificial Intelligence, 2023.
  4. “Multi-Model Dual-Transformer Network for Audio-Visual Speech Enhancement,” AVSEC 2024.
  5. “Integrating Graph Neural Networks and Visual Encoding for Robust Audiovisual Speech Enhancement,” IEEC 2026.
  6. “Frequency-Aware Selective State-Space Modeling for Audio-Visual Speech Enhancement,” Digital Signal Processing, 2026.
  7. “Dynamic Multi-Kernel Convolutional Network With Noise Injected Features for Audio-Only Speech Enhancement,” Neurocomputing, 2025.
  8. “Multimodal Learning-Based Speech Enhancement and Separation,” Computers in Biology and Medicine, 2025.

Research Impact

The research activities of Fazal e Wahab demonstrate measurable academic visibility through Scopus-indexed publications, citation performance, and interdisciplinary engineering collaborations. His studies contribute to ongoing advancements in speech enhancement technologies and intelligent multimedia processing systems. The citation profile associated with his publications indicates scholarly engagement within signal processing and communication engineering communities.[10]

Beyond scholarly publication, his mentorship of funded engineering projects has supported prototype development, applied innovation, and student-centered engineering education. Several supervised projects addressed healthcare technologies, smart home systems, assistive devices, and IoT-enabled monitoring systems, demonstrating practical societal relevance and engineering application.[11]

Award Suitability

The academic and professional profile of Fazal e Wahab reflects several characteristics associated with scholarly recognition in engineering and higher education. His combination of research productivity, international academic engagement, peer-reviewed publication activity, student mentorship, and interdisciplinary engineering expertise demonstrates sustained contribution to communication engineering and intelligent systems research.[12]

His involvement in advanced research related to speech enhancement and machine learning for edge computing environments aligns with emerging global priorities in intelligent communication technologies. Additionally, his experience in teaching, curriculum support, and applied project supervision reflects commitment to engineering education and knowledge dissemination within academic institutions.[13]

Conclusion

Fazal e Wahab has established a multidisciplinary academic profile combining research, teaching, engineering practice, and international scholarly collaboration. His contributions to speech enhancement, signal processing, and machine learning applications for embedded systems represent ongoing engagement with technically relevant and practically applicable research domains. Through journal publications, conference participation, funded project supervision, and academic service, he continues to contribute to the broader development of communication engineering and intelligent multimedia technologies.[13]

References

  1. Elsevier. (n.d.). Scopus author details: Fazal e Wahab, Author ID 57216410031. Scopus. https://www.scopus.com/authid/detail.uri?authorId=57216410031
  2. ORCID. (n.d.). ORCID profile record for Fazal e Wahab. https://orcid.org/0000-0003-4827-170X
  3. IEEE. (2025). Lightweight Adaptive Deep Learning for Efficient Real-Time Speech Enhancement on Edge Devices. https://doi.org/10.1109/TCE.2025.3598007
  4. University of Science and Technology of China. (2025). Doctoral dissertation and academic research profile.
  5. Speech Communication. (2024). Compact Deep Neural Networks for Real-Time Speech Enhancement on Resource-Limited Devices.https://doi.org/10.1016/j.specom.2023.103008
  6. CECOS University. (2015). Master of Science in Electrical Engineering academic record.
  7. International Journal of Interactive Multimedia and Artificial Intelligence. (2023). Efficient Gated Convolutional Recurrent Neural Networks for Real-Time Speech Enhancement.
  8. AVSEC Proceedings. (2024). Multi-Model Dual-Transformer Network for Audio-Visual Speech Enhancement.
  9. Computers in Biology and Medicine. (2025). Multimodal Learning-Based Speech Enhancement and Separation. https://doi.org/10.1016/j.compbiomed.2025.110082
  10. Digital Signal Processing. (2026). Frequency-Aware Selective State-Space Modeling for Audio-Visual Speech Enhancement.
  11. National ICT R&D Fund. (n.d.). Applied engineering and IoT-based funded student projects.
  12. Top Teachers Awards. (n.d.). International academic recognition and award platform.https://topteachers.net/
  13. Google Scholar. (n.d.). Academic citation profile of Fazal e Wahab. https://scholar.google.com/citations?hl=en&authuser=1&user=8t4Pxo8AAAAJ

Chen Yang | Engineering | Research Excellence Award

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Prof. Chen Yang | Engineering | Research Excellence Award

School of Energy and Power, Chongqing University  |  China

Prof. Chen Yang  research centers on advanced energy systems, renewable energy utilization, and thermal power engineering, with strong emphasis on modeling, optimization, and dynamic control of complex thermo-energy systems, supported by a research record of 1,004 citations across 868 documents, 98 publications, and an h-index of 18. His contributions span ultra-supercritical circulating fluidized bed boilers, nuclear power reactor secondary systems, compressed air energy storage, and hybrid solid oxide fuel cell–gas turbine systems, advancing the efficiency, reliability, and safety of large-scale power generation. He has developed multi-physics and multi-scale reduced-order modeling techniques to address nonlinear dynamics, uncertainty, cooperative simulation, and system stability challenges, enabling enhanced operational performance under transient and abnormal working conditions. His work integrates mechanistic models with artificial intelligence, including neural networks and time-series methods, to achieve online simulation, intelligent prediction, fault early warning, and predictive control in energy systems. He has also contributed to thermodynamic coupling analysis, waste heat utilization strategies, and multi-objective optimization frameworks for green energy systems. Through these innovations, his research significantly supports sustainable power technology development, promotes intelligent and resilient energy infrastructures, and contributes to low-carbon energy transformation and modern energy system advancement.

Citation Metrics (Scopus)

1200

900

600

300

0

Citations
1004

Documents
98

h-index
18

🟦 Citations    🟥 Documents    🟩 h-index


View Scopus Profile

Featured Publications

Xingjian Huang | Engineering | Best Research Article Award

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Dr. Xingjian Huang | Engineering | Best Research Article Award

Huaihua University | China

Xingjian Huang is a distinguished food‑science researcher whose work integrates protein chemistry, food structure and functionality, biopolymer‑based materials, and the nutritional evaluation of plant proteins. His research has significantly advanced understanding of how soy proteins and other plant‑derived proteins behave under various processing conditions, including proteolysis, gelation, hydrolysis, and complex formation, and how these behaviors influence texture, gel strength, nutritional quality, and functional properties. Among his notable contributions is the study of amyloid‑fibril formation from selectively hydrolyzed soy protein hydrolysates, which provided key insights into protein aggregation, fibrillation mechanisms, and structural modification. He has also conducted extensive research on exopolysaccharide production by lactic acid bacteria, improving yields through strain screening and optimization of fermentation and extraction conditions, linking microbial fermentation to food‑biopolymer applications. In addition, Huang has investigated the nutritional value and amino acid composition of various plant proteins, such as the protein subunits of the Chinese chestnut (Castanea mollissima), enhancing understanding of plant protein quality and potential functional applications. His work further explores the practical implications of protein interactions in food systems, including mixed‑protein gels, soy‑protein/corn‑starch composites, and the interplay of lipids and proteins in gel networks, bridging fundamental biochemical insights with industrial food processing relevance. Huang’s research has contributed valuable knowledge for improving food texture, nutrition, and the scalable processing of plant‑based proteins, supporting both academic research and applied food technology. According to his ResearchGate profile, he has published over 20 peer‑reviewed papers with more than 1,800 reads, demonstrating significant influence in the field and a substantial citation record that reflects his impact on food science research worldwide. For his outstanding contributions, Xingjian Huang has been recognized with the Best Research Article Award, highlighting his innovative work and high impact in the field of food science and technology.

Publication Profile

Orcid

Featured Publications

Yang, F., Huang, X., Zhang, C., … Hao, Y. (2018). Amino acid composition and nutritional value evaluation of Chinese chestnut (Castanea mollissima Blume) and its protein subunit. RSC Advances.

Xie, D., Liu, X., Zhang, H., … Pan, S., Huang, X. (2017). Textural properties and morphology of soy 7S globulin–corn starch (amylose, amylopectin). International Journal of Food Properties.

Xia, W., … Pan, S., Huang, X. (2017). Formation of amyloid fibrils from soy protein hydrolysate: Effects of selective proteolysis on β‑conglycinin. Food Research International.

Qi, L., … Pan, S., Huang, X. (2016). Yield improvement of exopolysaccharides by screening of the Lactobacillus acidophilus ATCC and optimization of the fermentation and extraction conditions. EXCLI Journal.

Pan, Y., Huang, X., Shi, X., … Du, Y. (2015). Antimicrobial application of nanofibrous mats self-assembled with quaternized chitosan and soy protein isolate. Carbohydrate Polymers.

 

Yair Rivera | Engineering | Best Researcher Award

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Abhijit Bhowmik | Mechanical Engineering | Best Researcher Award

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Luigi Bibbo’| Engineering | Best Researcher Award

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Dr. Luigi Bibbo’| Engineering | Best Researcher Award

Research Fellow at Mediterranea University of Reggio Calabria, Italy

Luigi Bibbò is an accomplished researcher with a robust background in electronic and computer engineering, specializing in fields such as sensors, photonics, nanotechnology, and artificial intelligence. He has held various research positions across prestigious institutions, including the Mediterranean University of Reggio Calabria, the University of Florence, and Shenzhen University. His work spans critical areas like big data analysis, biomedical applications, and advanced technologies for climate change adaptation and healthcare. With a Ph.D. in Electronic and Computer Engineering and extensive project leadership experience, Dr. Bibbò has made significant contributions to both academic research and practical applications in his field.

professional profile📖

ORCID

Education 🎓

Dr. Luigi Bibbò has a robust educational background in electronic and computer engineering, with a focus on biomedical applications and photonic technologies. He earned his PhD in Electronic and Computer Engineering from the Second University of Naples in January 2015, under the guidance of Prof. Luigi Zeni. His doctoral thesis centered on the development of sensors based on plasmon resonance in polymer optical fibers and photonic crystals. This research involved the design, fabrication, and implementation of surface plasmon resonance (SPR) sensors for both biological and chemical detection, utilizing advanced techniques such as sputtering, spin-coating, and e-beam lithography. Prior to his PhD, Dr. Bibbò obtained a Master’s degree in Biomedical Engineering from Federico II University of Naples in July 2009. His master’s thesis focused on the fabrication and characterization of organic semiconductor-based organic field-effect transistors (OFET) for biomedical applications, showcasing his early interest in the intersection of electronics and biology. Dr. Bibbò also holds a three-year degree in Biomedical Engineering from Federico II University of Naples, completed in June 2006. His undergraduate thesis explored innovative technologies for cardiac diagnosis, specifically the application of multislice computed tomography to coronary arteries. This strong foundation in biomedical engineering was further validated when he passed the state exam for professional qualification in November 2010.

work Experience💼

Dr. Luigi Bibbò has an extensive background in research and academia, marked by a diverse range of experiences in various cutting-edge fields. Since April 2024, he has been a Research Fellow at the Mediterranean University of Reggio Calabria, where he is actively involved in big data analysis and forecasting systems as part of the TECH4YOU project, focusing on technologies for climate change adaptation and improving the quality of life. Prior to this, from March 2023 to March 2024, Dr. Bibbò was a Research Fellow at the University of Florence’s Industrial Engineering Department. Here, he contributed to the design, development, and validation of robotic technologies, IoT, and artificial intelligence for biomedical applications under the “Pharaon Project.” From August 2019 to August 2022, Dr. Bibbò served as an RTDA at the Mediterranean University of Reggio Calabria, where he led a project aimed at creating a prototype for the localization, tracking, and monitoring of elderly individuals in indoor environments. Earlier in 2019, he worked as a Research Fellow at the Nanophotonics Research Center at Shenzhen University in China, focusing on OAM beam generation and reception. His international experience also includes a postdoctoral research position at the College of Electronic Science and Technology, Shenzhen University, from April 2016 to November 2018, where he led the development of innovative devices combining plasmonic nanoparticles with a tunable dielectric matrix.

Research Focus🔎

Dr. Luigi Bibbò is a seasoned researcher with a strong background in Electronic and Computer Engineering, particularly in the fields of sensors, photonics, and biomedical engineering. His research spans a wide array of cutting-edge technologies, including big data analysis, forecasting systems, and the development of robotic technologies, IoT, and Artificial Intelligence (AI) for biomedical applications. Dr. Bibbò’s work has significantly contributed to advancements in areas such as the creation of integrated systems for monitoring and tracking elderly individuals in indoor environments, as well as the design and development of innovative devices utilizing plasmonic nanoparticles and tunable dielectric matrices.

Awards and honors🏆

Dr. Luigi Bibbò, an accomplished researcher and academic in the fields of electronic and computer engineering, has been recognized with several prestigious awards and honors throughout his career. Notably, he was awarded the position of Research Fellow at the Mediterranean University of Reggio Calabria for his significant contributions to big data analysis and forecasting systems as part of the TECH4YOU project, which focuses on technologies for climate change adaptation and quality of life improvement. His expertise in designing and developing innovative robotic technologies, IoT, and artificial intelligence for biomedical applications led to his recognition as a leading researcher in the Pharaon Project. Dr. Bibbò’s pioneering work in the creation of a prototype for an integrated system for tracking and monitoring elderly individuals in indoor environments has also garnered attention, underscoring his commitment to enhancing healthcare through advanced technology.

Conclusion✅

Dr. Luigi Bibbò is a strong candidate for the Research for Best Researcher Award, given his extensive interdisciplinary research experience, innovative contributions to biomedical engineering and climate change technologies, and his international collaborations. To further strengthen his candidacy, focusing on increasing his publication output in high-impact journals, leading major grant-funded projects, and enhancing his outreach activities would be beneficial. Overall, his achievements and potential make him a worthy contender for this prestigious award.

📚Publications to Noted

  • Title: “AR Platform for Indoor Navigation: New Potential Approach Extensible to Older People with Cognitive Impairment”
    Journal: BioMedInformatics
    Year: 2024
    Date: June 24
    DOI: 10.3390/biomedinformatics4030087
    Source: Crossref
    Citations: Not provided
  • Title: “Human Activity Recognition (HAR) in Healthcare”
    Journal: Applied Sciences
    Year: 2023
    Date: December 6
    DOI: 10.3390/app132413009
    Source: Crossref
    Citations: Not provided
  • Title: “Emotional Health Detection in HAR: New Approach Using Ensemble SNN”
    Journal: Applied Sciences
    Year: 2023
    Date: March 3
    DOI: 10.3390/app13053259
    Source: Crossref
    Citations: Not provided
  • Title: “An Overview of Indoor Localization System for Human Activity Recognition (HAR) in Healthcare”
    Journal: Sensors
    Year: 2022
    Date: October 23
    DOI: 10.3390/s22218119
    Source: Crossref
    Citations: Not provided
  • Title: “MEMS and AI for the Recognition of Human Activities on IoT Platforms”
    Publication Type: Book Chapter
    Year: 2022
    DOI: 10.1007/978-3-031-24801-6_6
    Source: Crossref
    Citations: Not provided
  • Title: “High-Speed Amplitude Modulator with a High Modulation Index Based on a Plasmonic Resonant Tunable Metasurface”
    Journal: Applied Optics
    Year: 2019
    Date: April 1
    DOI: 10.1364/AO.58.002687
    Source: Crossref
    Citations: Not provided

 

 

Kritsada Khun-anod | Construction Engineering | Best Researcher Award

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Mr. Kritsada Khun-anod | Construction Engineering | Best Researcher Award

PhD Candidate at Kochi University of Technology, Japan

Mr. Kritsada Khun-anod is a skilled civil engineer with a solid educational background and practical experience. He earned both his Bachelor of Engineering and Master of Engineering in Civil Engineering from Kasetsart University at Kamphaeng Saen Campus, Thailand, achieving GPAs of 3.21 and 3.88, respectively. During his academic tenure, he worked as a site engineer for three months while in his third year of study. He also gained nearly a year of professional experience with China Harbour Engineering Company. Mr. Khun-anod has actively engaged in academic and professional development by participating in the Taiwan-Thailand-Vietnam Students Joint Symposium and Internship on the Advancement of Civil and Environmental Engineering, as well as the International Conference on Civil and Environmental Engineering in China (2018).

 

📝professional profile

Scopus Profile

Google Scholar

🎓Educational Details:

Mr. Kritsada Khun-anod holds a Bachelor of Engineering in Civil Engineering from Kasetsart University at Kamphaeng Saen Campus, Thailand, where he achieved a GPA of 3.21. He furthered his studies with a Master of Engineering in Civil Engineering from the same institution, graduating with an impressive GPA of 3.88.

👨‍🏫Professional Experience:

Mr. Kritsada Khun-anod gained practical experience as a site engineer during his third year of study in his Bachelor of Engineering program, where he worked for three months. He later continued his professional journey as a site engineer with China Harbour Engineering Company, a Chinese construction firm, where he accumulated nearly one year of valuable experience.

Achievements:

Mr. Kritsada Khun-anod has actively participated in notable academic events, including the Taiwan-Thailand-Vietnam Students Joint Symposium and Internship on the Advancement of Civil and Environmental Engineering. Additionally, he joined the International Conference on Civil and Environmental Engineering held in China in 2018.

📚Publications to Noted

Pre-project planning process study of green building construction projects in Thailand

Authors: K. Khun-anod, C. Limsawasd

Citations: 11

Year: 2019

Journal: Engineering Journal, 23(6), 67-81

Predicting cost and schedule performance of green building projects based on preproject planning efforts using multiple linear regression analysis

Authors: K. Khun-anod, C. Limsawasd, N. Athigakunagorn

Citations: 3

Year: 2023

Journal: Journal of Architectural Engineering, 29(3), 04023025

Barriers to Green Implementation in Highway Construction in Cambodia: Identification of Root Causes

Authors: S. Sourn, C. Limsawasd, K. Khun-anod, N. Athigakunagorn

Citations: 2

Year: 2022

Journal: International Journal of Sustainable Development & Planning, 17(3)

Roles and Autonomous Motivation of Safety Officers: The Context of Construction Sites

Authors: K. Khun-anod, T. Watanabe, S. Tsuchiya

Citations: Not specified

Year: 2024

Journal: Buildings, 14(2), 460

Roles and Autonomous Motivation of Safety Officers: The Context of Construction Sites

Authors: K. Khun-anod, T. Watanabe, S. Tsuchiya

Citations: Not specified

Year: 2024

Journal: Occupational Health in the Construction Industry, 149

The Analysis of Pre-Project Planning for Green Building Construction

Authors: K. Khun-anod, C. Limsawasd

Citations: Not specified

Year: 2020

Journal: Kasetsart University