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.

 

 

Sanyogita Manu | Engineering and Technology | Best Researcher Award

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Ms. Sanyogita Manu | Engineering and Technology | Best Researcher Award

PhD Candidate, The University of British Columbia, Canada

Publication Profile

Google scholar

Strengths for the Award

  1. Innovative Research Focus: Sanyogita’s work addresses a significant issue—indoor environmental quality during a time when many transitioned to remote work due to the pandemic. Her systematic study has the potential to inform guidelines and policies related to home office setups, highlighting its relevance in current public health discussions.
  2. Methodological Rigor: The research employs a robust methodology, utilizing continuous monitoring of various IEQ parameters alongside subjective assessments from participants. This comprehensive approach enhances the reliability of her findings.
  3. Professional Affiliations and Contributions: Sanyogita is actively engaged in professional organizations related to her field, serving on committees and reviewing journals. Her involvement in international conferences signifies her commitment to advancing research in IEQ and energy-efficient design.
  4. Publication Record: With multiple peer-reviewed publications and conference proceedings, Sanyogita demonstrates a solid track record in disseminating her research findings, contributing to the academic community’s understanding of indoor environments.
  5. Awards and Recognition: Her prior achievements and recognitions, including scholarships and awards, underscore her dedication and excellence in research.

Areas for Improvement

  1. Broader Impact Assessment: While her research is focused on WFH settings, there may be an opportunity to expand her study to include diverse populations and different geographical locations to enhance the generalizability of her findings.
  2. Interdisciplinary Collaboration: Collaborating with professionals from related fields such as psychology, sociology, or occupational health could enrich her research and offer a more holistic understanding of the WFH experience.
  3. Public Engagement: Engaging in public outreach or workshops to share her findings with broader audiences, including policymakers and the general public, could enhance the impact of her work and foster practical applications of her research.

Education

Sanyogita holds a Master’s degree in Interior Architecture and Design, specializing in Energy and Sustainability from CEPT University, India, where her dissertation focused on optimizing window performance in commercial buildings. She also earned her Bachelor’s degree in Interior Design from the same institution, with a dissertation exploring the thermal effects of furniture in interior environments. 🎓

Experience

With extensive experience in academia and research, Sanyogita has contributed to various projects assessing indoor environmental conditions and energy efficiency in buildings. She has served on several scientific committees and has been actively involved in peer review for reputable journals, reflecting her expertise in the field. 🏢

Research Focus

Her research primarily focuses on indoor environmental quality (IEQ) and its impact on occupant well-being and productivity, particularly in work-from-home settings. Sanyogita employs a systematic approach to evaluate both perceived and observed IEQ, utilizing a variety of environmental monitoring tools. 🔍

Awards and Honours

Sanyogita is a member of multiple prestigious organizations, including the International Society of Indoor Air Quality and Climate (ISIAQ) and the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE). She has been recognized for her contributions to building performance simulation and energy conservation, reflecting her commitment to sustainable practices. 🏆

Publication Top Notes

Manu, S., & Rysanek, A. (under review). A novel dataset of indoor environmental conditions in work-from-home settings. Building and Environment.

Manu, S., & Rysanek, A. (2024). A Co-Location Study of 87 Low-Cost Environmental Monitors: Assessing Outliers, Variability, and Uncertainty. Buildings, 14(9), Article 9. Link

Manu, S., et al. (2024). A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings. Building and Environment, 111652. Link

Doctor-Pingel, M., et al. (2019). A study of indoor thermal parameters for naturally ventilated occupied buildings in the warm-humid climate of southern India. Building and Environment, 151, 1-14. Link

Manu, S., et al. (2019). Performance evaluation of climate responsive buildings in India – Case studies from cooling dominated climate zones. Building and Environment, 148, 136-156. Link

Gupta, R., et al. (2019). Customized performance evaluation approach for Indian green buildings. Building Research & Information, 47(1), 56–74. Link

Conclusion

Sanyogita Manu’s research on indoor environmental quality in work-from-home settings is both timely and significant. Her methodological rigor, publication record, and active participation in professional communities demonstrate her dedication to advancing knowledge in her field. While there are areas for improvement, her strengths strongly position her as a worthy candidate for the Best Researcher Award. Her work has the potential to influence policy and improve well-being in residential work environments, making her contributions invaluable in today’s context.

Qi Liang | Pattern Recognition | Excellence in Research

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Mr Qi Liang | Pattern Recognition | Excellence in Research

Master in Tongji University at China

Qi Liang is a dedicated researcher and master’s student at Tongji University, PR China, specializing in mechanical engineering. With a strong foundation in industrial engineering from Jiangsu University of Science and Technology, Qi has a keen interest in advancing technology through innovative research. Recognized for introducing self-supervised learning methods in semiconductor applications, Qi’s work aims to solve complex challenges in pattern recognition. Their publication in Engineering Applications of Artificial Intelligence reflects a commitment to high-impact research. With multiple ongoing projects and a focus on practical applications, Qi is paving the way for efficient solutions in the semiconductor industry.

Profile

Google Scholar

Strengths for the Award

  1. Innovative Research: Qi Liang has introduced a self-supervised learning method for few-shot learning in semiconductor applications, demonstrating originality and a significant contribution to the field.
  2. Publication Record: The recent publication in Engineering Applications of Artificial Intelligence showcases a commitment to high-quality research, adding to the credibility of the work.
  3. Diverse Research Interests: With a focus on computer vision, multi-modal learning, and fault diagnosis, Qi’s work spans multiple cutting-edge areas, which increases the potential impact of the research.
  4. Practical Applications: The research addresses real-world challenges in the semiconductor industry, offering low-cost, efficient methods that have immediate applicability.
  5. Academic Engagement: Qi’s active involvement in ongoing projects and industry collaborations indicates a robust engagement with both academic and practical aspects of research.

Areas for Improvement

  1. Broader Collaboration: Expanding collaborations with international researchers could enhance the research’s visibility and applicability on a global scale.
  2. Increased Publication Volume: While the current publication is commendable, a more extensive publication record could further establish Qi’s expertise and leadership in the field.
  3. Outreach and Communication: Engaging in more outreach activities, such as conferences and seminars, could help disseminate findings and foster connections within the research community.

Education 

Qi Liang graduated with a Bachelor’s degree in Industrial Engineering from Jiangsu University of Science and Technology, where foundational principles of engineering and technology were mastered. Currently, Qi is pursuing a Master’s degree in Mechanical Engineering at Tongji University, one of China’s prestigious institutions, now in their third year of the program. This advanced education has allowed Qi to engage deeply with cutting-edge topics, particularly in computer vision and machine learning. Through rigorous coursework and research, Qi has developed expertise in areas such as pattern recognition, self-supervised learning, and fault diagnosis, equipping them with the skills necessary to tackle complex engineering problems and contribute significantly to both academic and industrial advancements.

Experience

Qi Liang has gained substantial experience through multiple research projects, totaling five completed or ongoing initiatives that emphasize practical applications of machine learning in semiconductor manufacturing. In addition to academic research, Qi has participated in three consultancy and industry-sponsored projects, bridging the gap between theoretical knowledge and real-world applications. Their collaborative efforts in research have led to valuable partnerships and a broader understanding of the industry’s challenges and needs. As the first to implement self-supervised learning techniques in few-shot learning tasks related to wafer map pattern recognition, Qi has showcased exceptional innovation. This unique approach has opened new avenues for cost-effective and efficient solutions within the semiconductor sector, positioning Qi as an emerging leader in their field.

Research Focus 

Qi Liang’s research focuses on the intersection of computer vision and machine learning, with a strong emphasis on pattern recognition, keypoint detection, and image retrieval. Specializing in self-supervised and multi-modal learning, Qi aims to develop innovative methodologies that minimize the reliance on labeled data while maximizing efficiency and applicability in industrial contexts. Current research projects explore dynamic adaptation mechanisms for few-shot learning, specifically tailored for wafer map pattern recognition in the semiconductor industry. Qi is also interested in signal processing and fault diagnosis, seeking to improve reliability and performance in manufacturing processes. This research direction not only contributes to the academic community but also addresses pressing industry challenges, promoting advancements in automation and smart manufacturing.

Publication Top Notes

  • Masked Autoencoder with Dynamic Multi-Loss Adaptation Mechanism for Few Shot Wafer Map Pattern Recognition 📄

Conclusion

Qi Liang’s innovative contributions to the field of mechanical engineering and computer vision make a strong case for the Excellence in Research award. The unique approach to self-supervised learning in few-shot learning for wafer map pattern recognition signifies both a breakthrough in methodology and practical application in the semiconductor industry. With a few strategic improvements, Qi has the potential to further amplify the impact of their research and cement their status as a leading researcher in their field.

Ahmed Deabs | Mechanical Engineering | Best Researcher Award

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Assoc Prof Dr. Ahmed Deabs | Mechanical Engineering | Best Researcher Award

Production Engineering and Mechanical Design, Faculty of Engineering, Shebin Elkom, Menoufia University, Egypt

Ahmed Deabs is a dedicated academic and mechanical engineer with a strong background in production engineering and mechanical design. Currently, he serves as a Lecturer at the Faculty of Engineering, Menofia University, and an Adjunct Lecturer at Delta Technological University, Egypt. Ahmed’s expertise spans across CAD, FEM, machine design, and vibration signal processing, making him a versatile educator and researcher in the field.

Publication Profile

 

Strengths for the Award:

  1. Academic and Teaching Excellence: Ahmed Deabs has a strong academic background with significant teaching experience in various engineering disciplines. His ability to teach over 20 different courses, ranging from “Machine Tool Design” to “Engineering Mechanics,” highlights his versatility and expertise in Production Engineering and Mechanical Design.
  2. Research Contributions: He has several publications in reputable journals and conferences, showcasing his research in areas like CAD, FEM, and parallel robots. His work on topics like “Computer Aided Design of Multi-Stage Gearboxes” and “Optimizing Vertical Pump Reliability” demonstrates his commitment to advancing engineering knowledge.
  3. Industrial and Practical Experience: Ahmed’s involvement in industrial projects, including the design and supervision of mechanical systems like renewable electricity generation systems and industrial production lines, underscores his practical skills and ability to apply research in real-world scenarios.
  4. Technological Proficiency: His proficiency in various engineering and computer tools like SOLIDWORKS, AUTOCAD, MATLAB, and his certifications (e.g., CSWP, CSWA) further bolster his technical capabilities, making him a well-rounded candidate for the award.
  5. Community and Educational Outreach: Ahmed’s initiative in creating and managing free educational resources, including YouTube channels and forums, reflects his dedication to sharing knowledge and supporting the engineering community.

Areas for Improvement:

  1. Research Impact: While Ahmed has a solid number of publications, there could be a focus on increasing the impact and citation of his research. Engaging in more collaborative research projects and targeting high-impact journals could further elevate his academic profile.
  2. International Exposure: Expanding his research collaborations and academic presence internationally could enhance his recognition. Participation in more global conferences and partnerships with international researchers would be beneficial.
  3. Grant Acquisition: Increasing his involvement in competitive research projects and securing grants would demonstrate his capability to lead large-scale research initiatives, further supporting his candidacy for the award.

 

🎓 Education

Ahmed Deabs holds a solid academic foundation in engineering, beginning as a Demonstrator in the Production Engineering and Mechanical Design Department at Menofia University in 2012. He advanced to Assistant Lecturer in 2016 and became a Lecturer in 2022. He also began serving as an Adjunct Lecturer at Delta Technological University in 2023, broadening his teaching experience.

🛠️ Experience

Ahmed has an extensive teaching portfolio, having taught over 20 different courses across various engineering disciplines. His experience includes supervising laboratories, contributing to accreditation projects, and participating in continuous improvement initiatives at Menofia University. His industrial work includes freelance mechanical design and supervising machine fabrication processes for Egyptian and Arabic companies.

🔍 Research Focus

Ahmed’s research interests are diverse, including Computer-Aided Design (CAD), Finite Element Method (FEM), machine design, and parallel robots. He also explores advanced topics like artificial neural networks, deep learning, and vibration signal processing, contributing to the evolution of mechanical engineering.

🏆 Awards and Honors

Ahmed has been recognized for his contributions to engineering education and research, particularly through his involvement in continuous improvement projects and his role in updating laboratory instruments at Menofia University. He also holds several certifications, including SOLIDWORKS and AUTOCAD, reflecting his commitment to professional development.

📄 Publications

“Computer Aided Design of Multi-Stage Gearboxes” – International Journal of Advanced Engineering and Global Technology (IJAEGT), Vol. 2, Issue 12, 2014. Cited by 11 articles Link to Publication

“Structural Modifications of 1K62 Engine Lathe Gearbox Casing” – International Journal of Advanced Engineering and Global Technology (IJAEGT), Vol. 3, Issue 2, 2015. Cited by 9 articles Link to Publication

“Parallel Robot – Review Article” – Journal of Engineering Science and Technology Review, 2021. Cited by 6 articles Link to Publication

“Assessment of Parallel Robot Dynamic Characteristics Using Experimental Modal Analysis and Finite Elements” – The First International Conference in Technological University Education and its Role in Industry, Energy and Environmental Conservation (ICCTU 2022), 2022. Cited by 3 articles Link to Publication

“Optimizing Vertical Pump Reliability: Investigating Main Shaft Challenges through Integrated Design and Testing Strategies“ – Water Science, 2024. Cited by 5 articles Link to Publication

 

Conclusion:

Ahmed Deabs is a strong candidate for the Researcher Award, given his extensive academic, research, and industrial contributions. His commitment to education, both in the classroom and through online platforms, alongside his technical expertise, makes him a well-rounded and deserving nominee. Focusing on increasing the impact of his research and expanding his international collaborations could further strengthen his candidacy. Overall, his achievements and contributions make him a suitable contender for the award.

 

 

 

Waqas Haroon | Transportation Engineering Award | Best Researcher Award

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Dr Waqas Haroon | Transportation Engineering Award | Best Researcher Award

Dr Waqas Haroon, International Islamic University Islamabad ,Pakistan

Waqas Haroon is a dedicated professional in the field of Civil Engineering, specializing in Transportation Engineering. He holds an M.Sc. in Transportation Engineering and a B.Sc. (Hons.) in Civil Engineering from the University of Engineering and Technology, Taxila. Currently serving as a Lecturer at the International Islamic University, Islamabad, he contributes significantly to research on asphalt and concrete materials, focusing on sustainability and performance enhancement. Waqas is a registered Professional Engineer with the Pakistan Engineering Council and actively participates in educational and administrative roles at his university. His research interests include the application of nanotechnology in construction materials and the sustainability of transportation systems.

Publication Profile

Orcid

Education

Waqas Haroon completed his M.Sc. in Transportation Engineering with an impressive aggregate of 3.54/4.00 from the University of Engineering and Technology, Taxila. Prior to this, he earned a B.Sc. (Hons.) in Civil Engineering with a grade of 3.36/4.00 from the same institution. His academic journey began with distinctions in F.Sc. and Matriculation from Punjab College of Information & Technology, Rawalpindi, and Barkat Ali Model School, Rawalpindi, respectively. Throughout his education, Waqas demonstrated a keen interest in engineering projects and research, focusing on innovative applications in asphalt and concrete technology.

Experience 

With a robust background in academia and research, Waqas Haroon has been serving as a Lecturer at the International Islamic University, Islamabad, since February 2020. His teaching portfolio includes courses in Transportation Engineering, Highway and Traffic Engineering, Surveying, and Civil Engineering Materials. Before joining IIU, he gained valuable experience as a Lab Engineer at both IIU and Swedish College of Engineering and Technology, Wah Cantt. His administrative contributions at IIU encompass roles in various committees, demonstrating his commitment to institutional development. Waqas’s career began with internships at Sheikh Zayed International Academy, Islamabad, and Allied Engineering Consultants, Lahore, where he laid the foundation for his practical skills in civil engineering.

Awards and Honors

Waqas Haroon has earned recognition for his academic and professional achievements, including qualifying as a Professional Engineer in the Transportation domain, certified by the Pakistan Engineering Council. He received a laptop under the Mian Muhammad Shahbaz Sharif Youth Initiative Scheme for his merit-based accomplishments. His academic journey was supported by an Internal Merit Scholarship during B.Sc. studies at UET Taxila and a Full Fee Merit Scholarship at Punjab College of Information, Rawalpindi. Waqas’s dedication to excellence in civil engineering education and research is further exemplified by his consistent academic achievements and contributions to innovative infrastructure solutions.

Research focus

Waqas Haroon’s research focuses on enhancing the performance and sustainability of construction materials, particularly asphalt and concrete. He explores the application of nanotechnology to improve the mechanical properties and durability of these materials, aiming to address challenges in infrastructure development. His recent studies include the evaluation of modified asphalt binders using nanomaterials, the impact of crumb rubber and silica on asphalt mixtures, and the use of organophilic nano clays in high-temperature performance of asphalt. Waqas contributes to advancing knowledge in his field through peer-reviewed publications and participation in international conferences. His research aims to promote environmentally friendly and economically viable solutions for infrastructure projects, aligning with global sustainability goals.

Publication Top Notes

Effect of nano silica on the performance of modified crumb rubber bitumen and asphalt mixtures 🛣️

Analyzing Young Adult Travelers’ Perception and Impacts of Carpooling on Traffic Sustainability 🚗

Consolidated effect of fiber-reinforcement and concrete strength class on mechanical performance, economy and footprint of concrete for pavement use 🏗️

Experimental Evaluation of a Partially Synthetic Bitumen in Road Paving Applications 🛣️

Investigation of Crumb Rubber Modification on the Performance of Bitumen and Asphalt Mixtures 🚧