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

Enes Kavrut | Engineering | Research Excellence Award

Published on by Top Teachers

Mr. Enes Kavrut | Engineering | Research Excellence Award

Iğdır University | Turkey

Dr. Enes Kavrut is an Assistant Professor at Iğdır University, specializing in food engineering, gastronomy, and innovative food technologies. He holds a PhD in Bioengineering and a doctorate in Veterinary Public Health and Food Safety, reflecting a strong interdisciplinary foundation. His research focuses on edible film packaging, food safety, antimicrobial applications, and sustainable bio-packaging solutions. Dr. Kavrut has authored over 10 international peer-reviewed journal articles, including publications in high-impact journals such as Food Chemistry and LWT, along with multiple book chapters and conference papers. He actively collaborates with international researchers on topics like hydrogen-enriched food systems and agri-food innovations. His work contributes significantly to improving food quality, safety, and shelf-life, supporting sustainable food systems and public health advancement.

Citation Metrics (Scopus)

40
30
20
10

Citations 30

h-index 3

Documents 7

Citations

h-index

Documents

Featured Publications

Y Çelebi, E Kavrut, M Bulut, Y Çetintaş, A Tekin, AA Hayaloğlu (2024).
Incorporation of hydrogen-producing magnesium into minced beef meat protects the quality attributes and safety of the product during cold storage. Food Chemistry | Journal Article · 2024 · 📊 Citations: 17

D Alwazeer, M Bulut, MM Ceylan, Y Çelebi, E Kavrut, Y Çetintaş, A Tekin (2024).
Hydrogen incorporation into butter improves its microbial and chemical stability, biogenic amine safety, quality attributes, and shelf-life
LWT – Food Science and Technology | Journal Article · 2024 · 📊 Citations: 9

T Engin, A Çiğdem, E Kavrut, B Tan, D Alwazeer, K Bekbayev (2025).
Use of hydrogen-rich solvent and principal component analysis improves the recovery of phytochemicals from grape wastes
Journal of Agriculture and Food Research | Journal Article · 2025 · 📊 Citations: 5

E Kavrut (2023).
Iğdır Halk Mutfak Kültüründe Yer Alan Lezzetlerin Değerlendirilmesi
Gastro-World | Journal Article · 2023 · 📊 Citations: 5

E Kavrut (2021).
Kıyma ve Kıyma Benzeri Ürünlerde ‘Hamburger Hastalığı’ olarak E. coli O157:H7’nin varlığı
Bayburt Üniversitesi Fen Bilimleri Dergisi | Journal Article · 2021 · 📊 Citations: 5

Zina Boussada | Engineering | Research Excellence Award

Published on by Top Teachers

Dr. Zina Boussada | Engineering | Research Excellence Award

Company for Petroleum Research and Operations | Tunisia

Dr. Zina Boussada is an emerging researcher in electrical engineering whose work bridges advanced control systems, intelligent automation, renewable energy technologies, and high-performance power electronics. Her scientific contribution focuses on the modeling, optimization, and control of induction motors, photovoltaic systems, and microgrid energy management using intelligent and hybrid computational approaches. She has contributed extensively to sensorless motor control through ANFIS-based strategies, multilevel NPC inverter topologies, stator-flux orientation techniques, and advanced inverter modulation methods, enhancing system efficiency, stability, and predictive performance in industrial and renewable energy applications. Her research extends to photovoltaic cell modeling, hybrid optimization frameworks, exponential smoothing forecasting, diode-clamped inverter strategies, and comparative inverter control techniques, addressing key challenges in modern smart-grid and clean-energy systems. She has collaborated with several research groups and contributed to journals and international conferences in the areas of energy systems, green technologies, and intelligent electrical drives. Her publication record reflects steady scholarly growth, supported by contributions in peer-reviewed journals such as Symmetry, WSEAS Transactions on Systems and Control, the International Journal of Environmental Sciences, and various high-impact conference proceedings. She has also published multiple studies on photovoltaic modeling and multilevel inverter technologies, reinforcing her position within the renewable-energy research community. Her citation metrics indicate increasing academic visibility, with Scopus reporting approximately 490 citations from 482 citing documents, 23 indexed documents, and an h-index of 9. Google Scholar metrics show comparable academic impact, reflecting a growing global readership and recognition for her work in intelligent control and energy-system optimization. Overall, her research trajectory demonstrates strong potential for continued advancement in sustainable energy technologies, intelligent control methodologies, and high-performance electrical systems, positioning her as a promising candidate for the Research Excellence Award.

Publication Profile

Scopus | Orcid 

Featured Publications

Boussada, Z., Omri, B., & Ben Hamed, M. (2025). High-performance sensorless control of induction motor via ANFIS and NPC inverter topology. Symmetry.

Boussada, Z., Omri, B., & Ben Hamed, M. (2025). Data-driven optimization for efficient integration of photovoltaic agents in residential microgrid systems. Euro-Mediterranean Journal for Environmental Integration.

Xingjian Huang | Engineering | Best Research Article Award

Published on by Top Teachers

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.

 

Vasso Papadimitriou | Engineering | Best Researcher Award

Published on by Top Teachers

Ms. Vasso Papadimitriou | Engineering | Best Researcher Award

Aristotle University of Thessaloniki | Greece

Ms. Vasso Papadimitriou is an accomplished researcher and academic affiliated with the Aristotle University of Thessaloniki and the Region of Central Macedonia, Greece. Her research primarily focuses on construction project management, cost estimation models, and the integration of Artificial Intelligence (AI) and Machine Learning (ML) techniques, particularly Artificial Neural Networks (ANNs), in the field of building renovation and project planning. She has contributed significantly to the development of predictive and hybrid models that enhance accuracy in early-stage and final cost estimation for construction and renovation projects. Dr. Papadimitriou’s innovative work combines ANN methodologies, including Radial Basis Function (RBF) and Multilayer Perceptron (MLP) networks, with Multi-Criteria Decision-Making (MCDM) approaches such as the TOPSIS Methodology to create efficient, data-driven tools for project assessment and optimization. Her research also aligns with Sustainable Development Goals (SDG 9 and SDG 17), focusing on promoting innovation, infrastructure, and partnerships for sustainable growth. She has published in international peer-reviewed journals indexed in Scopus, Web of Science (SCI-Expanded, ESCI), and other scientific databases. According to Scopus, she has 6 publications, 3 citations, and an h-index of 1. On Google Scholar, she holds 14 total citations, an h-index of 3, and an i10-index of 1, while ResearchGate records 6 publications, 11 citations, and an h-index of 2. Her interdisciplinary approach bridges civil engineering, computer science, and digital construction, contributing to advancements in cost modeling and sustainable infrastructure management. Through her publications and research collaborations, Dr. Papadimitriou continues to make impactful contributions to the field of engineering innovation and AI-driven construction technology. Her outstanding achievements and innovative contributions to predictive modeling and sustainable construction management make her a deserving nominee for the Best Researcher Award.

Publication Profile

Scopus | Google Scholar

Featured Publications

Papadimitriou, V. E., & Aretoulis, G. N. (2024). A final cost estimating model for building renovation projects. Buildings, 14(4), 1072.

Papadimitriou, V. E., Aretoulis, G. N., & Papathanasiou, J. (2024). Radial Basis Function (RBF) and Multilayer Perceptron (MLP) comparative analysis on building renovation cost estimation: The case of Greece. Algorithms, 17(9), 390.

Papadimitriou, V., & Aretoulis, G. (2023). Neural network models as a cost prediction tool to prevent building construction projects from a failure—A literature review. Proceedings of the Erasmus+ PROSPER Project International Scientific Conference, 1–10.

Papadimitriou, V. E., & Aretoulis, G. N. (2025). An innovative approach regarding efficient and expedited early building renovation cost estimation utilizing ANNs and the TOPSIS methodology. Algorithms, 18(11), 696.

Kritikos, P., Papadimitriou, V., & Aretoulis, G. N. (2021). Required project designers’ attributes as perceived by male and female engineers. International Journal of Decision Support System Technology (IJDSST), 13(4), 1–15.

 

 

Qiusong Liang | Engineering | Best Researcher Award

Published on by Top Teachers

Ms. Qiusong Liang | Engineering | Best Researcher Award

Northeast Forestry University | China

Ms. Qiusong Liang is a promising mechanical engineering researcher whose work focuses on advanced simulation, optimization, and design of electro-hydraulic and electromechanical systems. Her research emphasizes multi-objective optimization, structural dynamics, and fluid–structure interaction analysis to enhance the performance and reliability of servo and direct-drive valve mechanisms. She skillfully integrates computational tools such as ANSYS, SolidWorks, Maxwell, and AMESim for high-precision modeling and simulation, contributing significantly to innovations in flow control mechanisms, torque motor optimization, and cavitation noise reduction in hydraulic systems. Her recent studies explore the dynamic characteristics of torque motors and the coupling effects between electromagnetic and fluid systems, leading to improved high-response servo valve technologies for industrial and military applications. Ms. Liang’s research excellence and innovative approach have been recognized through publications in internationally indexed journals and notable contributions to engineering design projects. She maintains an active research profile with Scopus- and Google Scholar–indexed publications, accumulating documented citations and a growing h-index that reflect her rising academic influence in the field of mechanical system optimization and applied simulation engineering. Her commitment to applied research, precision design, and interdisciplinary collaboration has earned her recognition as a recipient of the Best Researcher Award, highlighting her as one of the emerging leaders in smart mechanical systems and sustainable automation technologies.

Publication Profile

Orcid

Featured Publications

  • Zhang, J., Liang, Q., Sun, J., Yan, B., Hu, Z., & Sun, W. (2025, October 29). Multi-objective optimization of torque motor structural parameters in direct-drive valves based on genetic algorithm. Actuators, 14(11), 527.

Mehran Pourgholi | Engineering | Best Researcher Award

Published on by Top Teachers

Assist. Prof. Dr. Mehran Pourgholi | Engineering | Best Researcher Award

Islamic Azad University | Iran

Assist. Prof. Dr. Mehran Pourgholi, an accomplished researcher in Civil and Structural Engineering, has made notable contributions to the fields of system identification, structural health monitoring, inverse problems, and stochastic subspace methods. His research focuses on enhancing the reliability of modal analysis and vibration-based damage detection in large-scale structures such as dams and steel buildings. Dr. Pourgholi integrates advanced computational approaches including entropy-based model selection, optimization algorithms, and error analysis frameworks to improve accuracy in structural system modeling. His collaborative work with experts from the University of Tabriz and Islamic Azad University has produced high-impact studies published in leading international journals such as the Journal of Vibration and Control, Mechanical Systems and Signal Processing, and Engineering Reports. According to Google Scholar, Dr. Pourgholi has 77 citations (68 since 2020), an h-index of 4, and an i10-index of 2, while Scopus records 51 citations across 46 documents with an h-index of 3. His influential publications on stochastic subspace identification and modal analysis have advanced understanding of dynamic behavior in civil structures. Recognized for his scholarly excellence, he has been honored with the Best Researcher Award for his significant impact in the field of structural system identification and vibration analysis.

Publication Profile

Scopus | Orcid | Google Scholar 

Featured Publications

Tarinejad, R., & Pourgholi, M. (2018). Modal identification of arch dams using balanced stochastic subspace identification. Journal of Vibration and Control, 24(10), 2030–2044.

Pourgholi, M., Mohammadzadeh Gilarlue, M. M., Vahdaini, T., & Azarbonyad, M. (2023). Influence of Hankel matrix dimension on system identification of structures using stochastic subspace algorithms. Mechanical Systems and Signal Processing, 186, 109893.

Pourgholi, M., Tarinejad, R., Khabir, M. E., & Mohammadzadeh Gilarlue, M. M. (2023). System identification of Karun IV Dam using balanced stochastic subspace algorithm considering the uncertainty of results. Journal of Vibration and Control, 29(23–24), 5342–5356.

Tarinejad, R., Pourgholi, M., & Yaghmaei-Sabegh, S. (2016). Signal processing of dynamic tests results using subspace identification based on orthogonal decomposition technique (SI-ORT). Modares Mechanical Engineering, 15(10), 104–116.

Pourgholi, M., Ghannadi, M., & Gavgani, S. S. (2024). Modal analysis of earthquake records for dams using stochastic subspace based on error analysis. Engineering Reports, 6(8), e12822

 

Hadjsadok Abdelkader | Sustainable Materials | Innovative Research Award

Published on by Top Teachers

Afshin Khodaparast | Low-carbon | Excellence in Research

Published on by Top Teachers

Dr. Afshin Khodaparast | Low-carbon | Excellence in Research

Researcher at Shahid beheshti university, Iran

Afshin Khodaparast is a distinguished civil engineer and researcher based in Tehran, Iran. He specializes in sustainable concrete materials and earthquake engineering, focusing on developing innovative green concrete solutions. With extensive academic training and industry experience, he has contributed to multiple high-impact research projects, particularly in earthquake-resistant structures and self-compacting earth concrete. As the CEO of ARPACIVIL, Afshin is dedicated to advancing eco-friendly construction technologies and implementing cutting-edge methodologies in the civil engineering sector. He has published extensively in renowned journals and conferences, showcasing his expertise in structural performance and materials science. Passionate about continuous learning and professional collaboration, Afshin actively participates in prestigious engineering societies such as ASCE and ACI. His work aims to bridge the gap between sustainable materials and resilient infrastructure, making significant strides in environmental conservation and structural safety.

professional profiles📖

 

Scopus Profile

Education 🎓

Afshin holds a Ph.D. in Earthquake Engineering from Shahid Beheshti University (2019-2024), where he researched the feasibility of self-compacted earth concrete in construction under the supervision of Dr. Kianoosh Samimi. He completed his Master of Science in Earthquake Engineering at Noshirvani University of Technology (2013-2016), focusing on the behavior of tall buildings under rotational earthquake components. His Bachelor of Science in Civil Engineering from Islamic Azad University (2009-2013) laid the foundation for his expertise in structural analysis and design. His strong academic background, coupled with a passion for sustainable materials, has positioned him at the forefront of civil engineering research.

work Experience💼

As the CEO of ARPACIVIL, Afshin leads innovative construction and research projects, particularly in green materials and earthquake-resistant structures. His experience includes working on high-rise buildings with outrigger systems, investigating self-compacting earth concrete, and evaluating seismic responses in structures. He has been an integral part of earthquake damage assessment teams, including the 2017 Kermanshah Earthquake Response Team. With hands-on experience in advanced structural analysis software such as ETABS, SAP2000, OpenSees, and ABAQUS, he has conducted numerous simulations to optimize building safety. His leadership roles in civil engineering organizations reflect his dedication to advancing structural engineering practices globally.

Research Focus

Afshin’s research revolves around earthquake engineering, green concrete technology, and sustainable construction materials. His Ph.D. dissertation explores the application of self-compacted earth concrete to enhance sustainability and reduce carbon emissions in the construction industry. His work also investigates seismic responses in high-rise structures, focusing on outrigger and belt-truss systems to improve structural resilience. He has published extensively on the impact of recycled fine aggregates, nano-silica, and rotational earthquake components on building performance. His interdisciplinary research aims to create environmentally friendly and disaster-resilient infrastructures.

Awards & Honors🏆 

Afshin has been recognized for his contributions to civil engineering research, particularly in sustainable materials and earthquake engineering. He has received accolades for his publications on self-compacting earth concrete, high-rise structural behavior, and recycled materials in construction. As an executive board member of the Qaemshahr Engineers Association, he has played a key role in engineering education and innovation. His active membership in ASCE, ACI, and the Iranian Earthquake Engineering Association further underscores his commitment to professional excellence.

Conclusion✅

Afshin Khodaparast is a strong candidate for the Excellence in Research Award. His contributions to earthquake engineering, sustainable materials, and innovative concrete solutions align well with the award’s criteria. His extensive research output, leadership, and professional engagement make him a deserving nominee. Strengthening global collaborations and focusing on high-impact research funding will further solidify his standing in the field.

📚Publications to Noted

Title: Effect of Pumice on Self-Compacting Earth Concrete: Mechanical and Microstructural Characteristics, and Life Cycle Assessments

👨‍🔬 Authors:

Afshin Khodaparast (A. Khodaparast)

Kianoosh Samimi (K. Samimi)

Javad Eslami (J. Eslami)

Mahyar Pakan (M. Pakan)

📅 Year: 2025