Birgitte Ahring | Engineering and Technology | Best Researcher Award

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Prof. Birgitte Ahring | Engineering and Technology | Best Researcher Award

Professor ,Washington State University ,United States

Dr. Birgitte Kiær Ahring is a distinguished global expert in biofuels, renewable energy, and clean technologies. Currently a Professor at Washington State University (WSU) and Head of the BioScience & Technology Group at the Bioproducts, Science & Engineering Laboratory (BSEL), she has led pioneering research in cellulosic ethanol, biogas, and renewable natural gas. With a career spanning decades, she has held prominent roles across academia, industry, and policy—including as founder of BioGasol Aps and advisor to international organizations such as the UNDP and World Bank. Dr. Ahring’s leadership in Denmark and the U.S. has driven the advancement of sustainable energy systems globally. Her commitment to translating science into practice has earned her numerous accolades, including Washington State’s Research Excellence Award and a gubernatorial honor as “Washingtonian for the Day.” With over 555 scientific contributions and 11 patents, she remains a driving force in the bioeconomy and environmental innovation.

Professional Profile

orcid

🎓 Education

Dr. Birgitte Kiær Ahring holds a Ph.D. in a life sciences field related to biotechnology or bioengineering, though her exact alma mater and thesis details are not listed. Her academic trajectory is rooted in biotechnology and chemical/biological engineering, fields that underpin her extensive contributions to renewable energy and clean technologies. Her foundational education laid the groundwork for a multifaceted career that bridges science, engineering, policy, and industrial application. She has also been involved in academic leadership and curriculum development through professorships at institutions such as the Technical University of Denmark (DTU), University of California, Los Angeles (UCLA), and Washington State University. Her interdisciplinary background and international engagements—ranging from Denmark to the U.S., and from Africa to Asia—reflect a rich academic foundation and lifelong commitment to sustainable energy research and education.

💼 Experience

Dr. Ahring’s professional journey reflects over three decades of leadership in biotechnology and renewable energy. Since 2008, she has served as Professor at WSU and previously directed the BSEL, where she established state-of-the-art research facilities. She founded and led BioGasol Aps and was CEO of the Maxifuel Pilot Plant in Denmark. From 2002–2008, she led the Danish Centre for Biofuels and BST division at DTU. At UCLA, she served as Professor of Civil & Environmental Engineering. Her governmental and advisory roles include being a Board Member of Energinet.dk and a consultant to USDA and multiple UN agencies. She has contributed to renewable energy implementation across Latin America, Africa, and Asia. She continues to advise research campaigns and editorial boards internationally. Through this experience, she has merged policy, practice, and research into a cohesive and influential professional impact.

🏆 Awards and Honors

Prof. Birgitte Ahring has earned numerous prestigious awards that honor her transformative research and global influence in bioengineering. In 2008, she received the Washington State Star Researcher Award valued at $2.5 million for excellence in renewable energy innovation. In 2021, she was recognized with the WSU Chancellor’s Distinguished Research Excellence Award. She was named “Washingtonian for the Day” by Governor Jay Inslee in 2022, acknowledging her service to the state’s clean energy transition. In 2023, she received the Anjan Boise Outstanding Research Award, and in 2024, she earned WSU’s Research Excellence Award. These accolades reflect her leadership in scientific discovery, commercialization, and sustainability-focused innovation. Additionally, her numerous editorial and board appointments in academia and industry further affirm her authority in the global bioeconomy and her role as a mentor and policy influencer.

🔍 Research Focus

Prof. Ahring’s research centers on clean technology for biofuels, biochemicals, and renewable natural gas (RNG). She is a world leader in cellulosic ethanol production, thermophilic anaerobic digestion, and advanced wet oxidation (AWOEx) pretreatment technologies. Her work explores the decarbonization of energy systems through biological and chemical conversion of lignocellulosic biomass, waste feedstocks, and CO₂ into fuels and valuable bio-products. She is especially focused on microbial consortia engineering and syngas fermentation to develop sustainable aviation fuel (SAF) and medium-chain volatile fatty acids. She has significantly advanced microbial hydrogen kinetics and homoacetogenesis, aiming to optimize the energy yields and carbon efficiencies in bioreactors. Her integrated approach—spanning lab research, pilot plants, and industrial applications—bridges science, engineering, and policy. Through over 555 publications and collaborative global research, Prof. Ahring is reshaping bioresource technology and offering scalable solutions for climate-resilient energy systems.

📚 Publication Top Notes

 Membrane Technologies for Separating Volatile Fatty Acids Produced Through Arrested Anaerobic Digestion: A Review

  • Journal: Clean Technologies, June 2025

  • Authors: Angana Chaudhuri, Budi Mandra Harahap, Birgitte K. Ahring

  • Summary:
    This review explores state-of-the-art membrane-based separation technologies for volatile fatty acids (VFAs) derived from arrested anaerobic digestion. It emphasizes operational efficiency, selectivity, and integration potential in biorefineries, highlighting nanofiltration, pervaporation, and forward osmosis as promising routes for sustainable VFA recovery.

Advancing Thermophilic Anaerobic Digestion of Corn Whole Stillage: Lignocellulose Decomposition and Microbial Community Characterization

  • Journal: Fermentation, June 2024

  • Authors: Alnour Bokhary, Fuad Ale, Richard Garrison, Birgitte K. Ahring

  • Summary:
    The study investigates thermophilic anaerobic digestion (AD) of corn whole stillage, focusing on lignocellulosic breakdown and microbial dynamics. It reveals enhanced methane yield and stable digestion due to synergistic microbial interactions, underlining the importance of community structure in optimizing AD processes.

 Acetate Production by Moorella thermoacetica via Syngas Fermentation: Effect of Yeast Extract and Syngas Composition

  • Journal: Fermentation, September 2023

  • Authors: Budi Mandra Harahap, Birgitte K. Ahring

  • Summary:
    This paper examines acetate production from syngas using Moorella thermoacetica. It discusses how varying yeast extract concentrations and syngas composition affect yields, emphasizing the role of nutrient balance and gas ratios in optimizing microbial fermentation for bio-based acetic acid.

 Enhancing Acetic Acid Production in In Vitro Rumen Cultures by Addition of a Homoacetogenic Consortia from a Kangaroo

  • Journal: Fermentation, September 2023

  • Authors: Renan Stefanini Lopes, Birgitte K. Ahring

  • Summary:
    Innovative research demonstrating the enhancement of acetic acid production in rumen cultures by adding kangaroo-derived homoacetogens. The study also investigates methanogen inhibition and almond biochar’s role in altering fermentation profiles, suggesting applications in livestock and bioenergy.

 Acetate Production from Syngas Produced from Lignocellulosic Biomass Materials along with Gaseous Fermentation of the Syngas: A Review

  • Journal: Microorganisms, April 2023

  • Authors: Budi Mandra Harahap, Birgitte K. Ahring

  • Summary:
    This comprehensive review analyzes the full cycle of acetate production from biomass-derived syngas. It discusses gasification parameters, microbial strain selection, and bioreactor design, proposing integrated systems for sustainable acetate generation from lignocellulosic residues.

Conclusion

Engineering Award, Technology Award, Best Engineering Award, Global Technology Award, Engineering Innovation Award, Technology Excellence Award, Emerging Engineer Award, Tech Pioneer Award, Digital Engineering Award, STEM Innovation Award, Engineering and Technology Recognition, Academic Technology Award, Young Engineer Award, Women in Engineering Award, Smart Tech Award, Mechanical Engineering Award, Electrical Engineering Award, Civil Engineering Award, Software Engineering Award, Engineering Leadership Award, AI Technology Award, Robotics Award, Engineering Design Award, Sustainable Engineering Award, Innovative Engineer Award, Best Technologist Award, Engineering R&D Award, Engineering Educator Award, Future Tech Award, Engineering Breakthrough Award, Global Engineering Talent Award, Tech Achievement Award, Industry Technology Award, Next Gen Engineering Award, Excellence in Technology Award, Engineering Startup Award, Engineering Invention Award, Engineering Visionary Award, Lifetime Achievement in Engineering Award, Engineering and Technology Research Award

 

Kai Zhang | Mechanical Engineering | Best Researcher Award

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Assoc. Prof. Dr. Kai Zhang | Mechanical Engineering | Best Researcher Award

Associate Professor, Shenyang University of Chemical Technology, China

ZHANG Kai is an accomplished Associate Professor at Shenyang University of Chemical Technology, specializing in artificial intelligence algorithms, robotics, and mechanical system optimization. With a doctoral degree in mechanical engineering, he has made significant contributions to intelligent fault diagnosis, machine vision, and the reliability of rotating machinery. Over the past five years, he has authored more than 30 academic papers, including 9 SCI-indexed and 11 EI-indexed articles, with 7 appearing in top-tier JCR Q1 journals. Dr. Zhang has led a sub-project under China’s National Key R&D Program and participated in several National Natural Science Foundation initiatives. His innovative research in adaptive optimization algorithms has also resulted in four patents. Committed to academic excellence and engineering innovation, Dr. Zhang continues to mentor students and lead pioneering research that bridges AI and mechanical design. His work enhances predictive maintenance, system reliability, and intelligent manufacturing technologies.

Profile

Scopus

Education 

ZHANG Kai earned his Doctorate in Mechanical Engineering, focusing on intelligent systems and optimization algorithms. His academic foundation is grounded in multidisciplinary studies that bridge traditional mechanical principles with cutting-edge computer science, especially in artificial intelligence and robotics. During his postgraduate years, he explored complex optimization problems, laying the groundwork for future research in algorithm development and machine learning applications in mechanical systems. His doctoral thesis was recognized for its innovation in adaptive optimization strategies for mechanism design. Dr. Zhang’s education equipped him with both theoretical acumen and practical engineering problem-solving skills, which he has since applied across a range of high-impact projects in academia and applied research. His passion for teaching and mentoring has also led to the development of curricula that integrate AI tools into traditional mechanical engineering coursework.

Experience 

Currently serving as Associate Professor at the Shenyang University of Chemical Technology, ZHANG Kai has over a decade of experience in academia and research. He has led and participated in multiple national-level projects, including a key sub-project under the National Key Research and Development Program. Over the past five years, he has published more than 30 peer-reviewed papers, many of which have been recognized in prestigious SCI and EI journals. He specializes in intelligent fault diagnosis for rotating machinery, differential evolution algorithms, and machine vision systems. His engineering expertise extends to vibration analysis and online health monitoring technologies. Dr. Zhang is also a key contributor to various academic initiatives aimed at improving the integration of AI within traditional mechanical systems. He is deeply involved in supervising graduate students and promoting interdisciplinary research within his department.

Research Focus

ZHANG Kai’s research lies at the intersection of mechanical engineering and artificial intelligence. His primary interests include the development of adaptive evolutionary algorithms, fault diagnosis techniques for rotating machinery, and intelligent machine vision systems. He applies AI-based solutions such as particle swarm optimization and differential evolution to solve multi-constraint mechanical design problems. His studies have enhanced the accuracy and efficiency of vibration monitoring, online health diagnostics, and fault tolerance systems in industrial equipment. With a growing emphasis on smart manufacturing, Dr. Zhang aims to bridge theoretical algorithm development with real-world mechanical applications. His research has far-reaching implications in industrial automation, robotics, and mechanical system reliability. He also works on improving the robustness and flexibility of mechanical optimization through novel algorithmic approaches. As industries increasingly seek to implement predictive maintenance and automation, his research offers critical tools and strategies for system sustainability and innovation.

Publication Top Notes

  1. Zhang K, Yang M, Zhang Y, et al.
    Title: Error feedback method (EFM) based dimension synthesis optimisation for four-bar linkage mechanism
    Journal: Applied Soft Computing, 2023: 110424
    Summary: Introduced an innovative error feedback method to enhance dimension synthesis in mechanical linkages, improving mechanical efficiency through intelligent correction algorithms.

  2. Kai Zhang, Eryu Zhu, et al.
    Title: A multi-fault diagnosis method for rolling bearings
    Journal: Signal, Image and Video Processing, 2024, 18: 8413-8426
    Summary: Developed a multi-fault detection model using signal processing and AI classification to improve maintenance systems in rotating equipment.

  3. Kai Zhang, Jiahao Zhu, Yimin Zhang, Qiujun Huang
    Title: Optimization method for linear constraint problems
    Journal: Journal of Computational Science, 2021, 51: 101315
    Summary: Proposed a new optimization framework for solving mechanical design issues with linear constraints using a hybrid computational approach.

Conclusion:

Associate Professor ZHANG Kai’s academic output, innovative methodologies, and active leadership in key research initiatives position him as a highly deserving candidate for the Best Researcher Award. His contributions significantly advance knowledge in AI-based mechanical systems and engineering reliability. Recognizing his work through this award would not only honor his individual achievements but also encourage further interdisciplinary research within his field.

Saibo She | Electrical Engineering | Best Researcher Award

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Dr Saibo She | Electrical Engineering | Best Researcher Award 

Ph.D Student, University of Manchester, United Kingdom

Saibo She is a dedicated researcher specializing in electromagnetic non-destructive testing and sensor design. Currently pursuing a PhD at the University of Manchester, UK, he previously earned his bachelor’s degree from Hunan University, China. With a strong foundation in electrical engineering, Saibo has actively contributed to various innovative research projects, focusing on defect detection and material evaluation. He is passionate about applying artificial intelligence to enhance diagnostic methodologies. Beyond academia, Saibo has demonstrated leadership in multiple competitions, reflecting his commitment to innovation and collaboration. His work has led to numerous publications and patents, marking him as a rising star in his field.

Profile

Scopus

Strengths for the Award

  1. Extensive Research Experience: Saibo has been involved in numerous significant research programs, focusing on advanced topics in non-destructive testing and electromagnetic evaluation. His work is supported by prestigious funding, such as the National Natural Science Foundation of China.
  2. Innovative Contributions: He has made substantial contributions to the field, as evidenced by multiple patents and published papers in reputable journals like the IEEE Sensors Journal and IEEE Transactions on Instrumentation and Measurement. His research on eddy current sensors demonstrates a blend of innovation and practical application.
  3. Strong Publication Record: Saibo has co-authored several papers with impactful findings, showcasing his ability to engage in high-quality research and contribute to scientific knowledge. His work on defect detection and materials evaluation reflects a commitment to advancing the field.
  4. Awards and Scholarships: His accolades, including the IEEE Instrumentation and Measurement Graduate Fellowship Award and various scholarships, highlight his academic excellence and recognition by peers and institutions.
  5. Leadership Experience: His role as a group leader in several competitions suggests strong leadership and teamwork skills, which are crucial for collaborative research environments.

Areas for Improvement

  1. Broader Impact: While his research is innovative, exploring avenues to increase the practical impact of his work in industrial applications could enhance his profile. Engaging with industry partners for real-world testing and implementation could broaden his research’s reach.
  2. Interdisciplinary Collaboration: Saibo could benefit from engaging with researchers from different fields to foster interdisciplinary collaboration, which can lead to new perspectives and innovative solutions to complex problems.
  3. Communication Skills: While his publication record is strong, focusing on enhancing presentation and outreach skills could help him communicate his research findings more effectively to diverse audiences, including policymakers and industry stakeholders.

Education

Saibo She is currently pursuing a PhD at the University of Manchester, UK, from September 2022 to June 2026. He previously obtained his bachelor’s degree from Hunan University, China, where he studied from September 2019 to June 2022. His education has provided him with a solid foundation in electrical engineering and materials science, equipping him with the knowledge and skills needed for advanced research. At both institutions, Saibo excelled academically, receiving several scholarships and awards that recognized his outstanding performance. His studies have been complemented by hands-on research experiences, enabling him to apply theoretical concepts to practical challenges in non-destructive testing and sensor technology. Saibo’s educational journey reflects a commitment to excellence and a strong desire to contribute to advancements in his field.

Experience 

Saibo She has extensive research experience, starting in July 2019, where he has been involved in multiple significant projects. His work includes analyzing mechanical stress wave mechanisms in silicon carbide power electronic devices and exploring damage mechanisms using nonlinear electromagnetic acoustic emission methods. He has contributed to research funded by the National Natural Science Foundation of China and participated in projects related to non-destructive testing techniques. Saibo’s main responsibilities include the simulation and analysis of electromagnetic fields, the design and evaluation of electromagnetic sensors, and hardware circuit design. He has also constructed experimental platforms for testing and validation purposes. His involvement in these projects showcases his technical expertise and ability to tackle complex engineering problems, making him a valuable asset in the field of non-destructive evaluation.

Awards and Honors 

Saibo She has received numerous awards and honors throughout his academic career. In March 2023, he was awarded the IEEE Instrumentation and Measurement Graduate Fellowship Award. He is a recipient of the China Scholarship Council (CSC) and University of Manchester Joint Scholarship, covering the period from 2022 to 2026. During his time at Hunan University, he received several accolades, including the Graduate Student National Scholarship for two consecutive years (2020-2021 and 2019-2020) and the Academic First-Class Scholarship. Additionally, he was recognized as an Outstanding Graduate Student for the 2019-2020 academic year. His achievements in competitions include the Central China Second Prize in the China Sensor Innovation and Entrepreneurship Competition and multiple awards in electronic design competitions. These recognitions underscore his dedication to research excellence and innovation in engineering.

Research Focus

Saibo She’s research focuses on the design of eddy current array sensors and the evaluation of ferromagnetic materials, particularly through the study of hysteresis loops and Barkhausen magnetic noise. He is keenly interested in defect diagnosis and identification utilizing artificial intelligence algorithms, aiming to enhance the capabilities of non-destructive testing techniques. His work addresses challenges in materials science and engineering, particularly in improving the reliability and efficiency of sensor technologies. By integrating machine learning approaches into traditional testing methods, Saibo seeks to push the boundaries of current evaluation techniques. His research not only contributes to academic knowledge but also has practical implications for industries requiring advanced non-destructive testing solutions. Saibo’s commitment to innovation and his technical expertise position him as a leading researcher in the field, with the potential to significantly advance the understanding and application of electromagnetic testing methods.

Publication Top Notes

  • Flexible Differential Butterfly-Shape Eddy Current Array Sensor for Defect Detection of Screw Thread 📄
  • Flexible Floral Eddy Current Probe for Detecting Flaws in Metal Plate 📄
  • Optimal Design of Remote Field Eddy Current Testing Probe for Ferromagnetic Pipeline Inspection 📄
  • An Innovative Eddy Current Sensor with E-Core Ferrite Resistant to Lift-Off and Tilt Effects 📄
  • Inspection of Defects Depth for Stainless-Steel Sheets Using Four-Coil Excitation Sensor and Deep Learning 📄
  • Evaluation of Defects Depth for Metal Sheets Using Four-Coil Excitation Array Eddy Current Sensor and Improved ResNet18 Network 📄
  • Thickness Measurement and Surface-Defect Detection for Metal Plate Using Pulsed Eddy Current Testing and Optimized Res2Net Network 📄
  • Simultaneous Measurements of Metal Plate Thickness and Defect Depth Using Low Frequency Sweeping Eddy Current Testing 📄
  • Size-Distinguishing Miniature Electromagnetic Tomography Sensor for Small Object Detection 📄
  • Diffusion Velocity of Eddy Current in Metallic Plates Using Point-Tracing Method 📄
  • Temperature Monitoring of Vehicle Brake Drum Based on Dual Light Fusion and Deep Learning 📄

Conclusion

Saibo She is an excellent candidate for the Research for Best Researcher Award due to his impressive research accomplishments, innovative contributions, and strong leadership capabilities. By addressing the areas for improvement, such as expanding the practical impact of his research and enhancing interdisciplinary collaborations, he can further strengthen his profile. His trajectory indicates a promising future in research and innovation, making him a worthy recipient of this award.

 

 

Gokhan Basar | Mechanical Engineering | Best Researcher Award

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Dr. Gokhan Basar | Mechanical Engineering | Best Researcher Award

Research Assistant at Industrial Engineering, Turkey

Dr. Gokhan Basar is a dedicated researcher and assistant professor in the Department of Industrial Engineering at Osmaniye Korkut Ata University, Turkey. Born on January 1, 1989, in Tarsus, Turkey, he has developed a strong academic and professional foundation in mechanical engineering. Dr. Basar holds a PhD in Mechanical Engineering, specializing in the production of reinforced aluminum matrix composites. He has contributed significantly to the field through his research on friction stir welding and optimization techniques, establishing himself as an expert in machinability and mechanical properties of materials. His commitment to advancing engineering knowledge is evident in his numerous publications and active participation in national and international conferences.

Profile:

Google Scholar

Strengths for the Award:

  1. Diverse Research Areas: Dr. Basar has an extensive range of research interests including Friction Stir Welding, machinability of materials, and optimization techniques. This diversity reflects a strong capability to contribute to various fields within engineering.
  2. Academic Qualifications: With a PhD in Mechanical Engineering and multiple relevant master’s and bachelor’s degrees, Dr. Basar possesses a solid educational foundation that underpins his research.
  3. Significant Contributions: His published works, including book chapters and numerous journal articles, indicate active engagement in research. The citation metrics (42 citations and an H-index of 4) highlight that his work is recognized and valued by the academic community.
  4. Research Methodology Expertise: Dr. Basar’s proficiency in experimental design and optimization methods, particularly the Taguchi Method and Grey Relational Analysis, showcases his ability to apply advanced statistical techniques to real-world engineering problems.
  5. Active Conference Participation: Regular attendance at national and international conferences demonstrates a commitment to staying updated with the latest developments in his field and sharing his findings with the broader scientific community.
  6. Journal Refereeing: Serving as a referee for multiple reputable journals illustrates his involvement in the academic process and recognition by peers.

Areas for Improvement:

  1. Increased Collaboration: While Dr. Basar has a solid publication record, collaboration with researchers from diverse fields could enhance the breadth and impact of his research.
  2. Enhancing Citation Impact: Although his citation metrics are commendable, focusing on publishing in high-impact journals could further increase his visibility and citation rate.
  3. Broader Public Engagement: Engaging with industry stakeholders and public forums could help translate his research findings into practical applications, increasing societal impact.
  4. Exploration of Emerging Technologies: Staying abreast of emerging technologies in materials science and mechanical engineering could provide new avenues for research and innovation.

Education:

Dr. Gokhan Basar’s educational journey began with a Bachelor’s degree in Mechanical Engineering, which laid the groundwork for his advanced studies. He earned his MSc in Mechanical Engineering from Iskenderun Technical University (2013-2016), where he focused on optimizing welding parameters in friction stir welding. His research culminated in a thesis that highlighted his proficiency in practical applications of engineering principles. Dr. Basar continued his academic pursuit at Osmaniye Korkut Ata University, where he completed his PhD in Mechanical Engineering (2017-2023). His doctoral research investigated the production of SiC and B4C particle-reinforced aluminum matrix composites through powder metallurgy, further showcasing his ability to innovate in materials engineering. Throughout his academic career, Dr. Basar has demonstrated a strong commitment to educational excellence and research development.

Experience:

Dr. Gokhan Basar has amassed extensive experience in academia, starting his career as a Research Assistant in the Department of Mechanical Engineering at Iskenderun Technical University from 2013 to 2016. His responsibilities included conducting research, assisting in teaching, and engaging in various engineering projects. In 2016, he transitioned to Osmaniye Korkut Ata University, where he currently serves as a Research Assistant in the Department of Industrial Engineering. In this role, Dr. Basar has focused on advancing knowledge in the fields of friction stir welding, materials machinability, and optimization methods. He has participated in numerous conferences, enhancing his professional network and contributing to the scientific community. His dedication to research and education has positioned him as a prominent figure in mechanical engineering, with a strong emphasis on innovative practices and experimental design.

Research Focus:

Dr. Gokhan Basar’s research focuses primarily on advanced welding techniques, particularly Friction Stir Welding (FSW), and the machinability and mechanical properties of materials. His expertise extends to optimization methods, including the Taguchi Method, Response Surface Methodology, and Grey Relational Analysis, enabling him to develop effective strategies for improving material performance and process efficiency. He is particularly interested in the production of composite materials, investigating the use of SiC and B4C particles in aluminum matrices to enhance their mechanical properties. His research also includes the design of experiments and multi-response optimization, providing insights into surface quality and operational parameters in various manufacturing processes. Dr. Basar’s commitment to innovation in mechanical engineering drives his work to address contemporary challenges and contribute to the evolution of engineering practices.

Publications Top Notes:

  1. Optimization of machining parameters in face milling using multi-objective Taguchi technique 📄
  2. Modeling and optimization of face milling process parameters for AISI 4140 steel 📄
  3. Determination of the optimum welding parameters for ultimate tensile strength and hardness in friction stir welding of Cu/Al plates using Taguchi method 📄
  4. Optimization of cutting parameters in hole machining process by using multi-objective Taguchi approach 📄
  5. Modeling and optimization for fly ash reinforced bronze-based composite materials using multi-objective Taguchi technique and regression analysis 📄
  6. Multi-response optimization in drilling of MWCNTs reinforced GFRP using grey relational analysis 📄
  7. Delik İşleme Prosesinde Kesme Parametrelerin Taguchi Metodu ve Regresyon Analiz Kullanılarak Modellenmesi ve Optimizasyonu 📄
  8. Kolemanit ve Boraks Takviyeli Fren Balatalarının Sürtünme Performansı 📄
  9. Sıcak presleme yöntemi ile üretilmiş uçucu kül takviyeli bronz matrisli fren balata malzemelerinin sürtünme-aşınma özellikleri üzerine kolemanit miktarının etkisi 📄
  10. Mathematical Modeling and Optimization of Milling Parameters in AA 5083 Aluminum Alloy 📄
  11. 316L Paslanmaz Çeliklerin Frezeleme işlemindeki Yüzey Pürüzlülüğün ANFIS ile Modellenmesi 📄
  12. Bronz Esaslı Kompozit Sürtünme Malzemelerin Üç Nokta Eğme Mukavemetinin Taguchi Metodu ile Optimizasyonu 📄
  13. Statistical Investigation of the Effect of CO2 Laser Cutting Parameters on Kerf Width and Heat Affected Zone in Thermoplastic Materials 📄
  14. A new hybrid meta-heuristic optimization method for predicting UTS for FSW of Al/Cu dissimilar materials 📄
  15. Prediction of surface hardness in a burnishing process using Taguchi method, fuzzy logic model and regression analysis 📄
  16. Multi-objective optimization of cutting parameters for polyethylene thermoplastic material by integrating data envelopment analysis and SWARA-based CoCoSo approach 📄
  17. Kompozit Malzemelerin Delme İşleminde İtme Kuvvetinin Taguchi Metodu ile Optimizasyonu ve Regresyon Analizi ile Tahmini 📄
  18. Tepki yüzeyi metodolojisi kullanılarak nanokompozitin delinmesinde oluşan itme kuvvetinin modellenmesi ve analizi 📄
  19. Analysis and Optimization of Ball Burnishing Process Parameters of AA 7075 Aluminium Alloy with Taguchi Method 📄
  20. The Effect of Colemanite and Borax Reinforced to the Friction Performance of Automotive Brake Linings 📄

Conclusion:

Dr. Gokhan Basar exemplifies the qualities of a strong candidate for the Research for Best Researcher Award. His extensive research experience, educational background, and contributions to the field of engineering position him as a noteworthy researcher. By focusing on collaboration, increasing his publication impact, and engaging with the broader community, he could further enhance his profile as a leading researcher. His commitment to advancing knowledge in his areas of expertise makes him a deserving candidate for this prestigious award.