Mr. Shuaikang Chang | thermal | Best Researcher Award

Mr. Shuaikang Chang | thermal | Best Researcher Award

Mr. Shuaikang Chang, CHONGQING UNIVERSITY, China

Shuaikang Chang is a dedicated Ph.D. candidate at Chongqing University, China, specializing in Safety Science and Engineering. His research focuses on the transformative potential of ultra-high-pressure abrasive waterjet machining, particularly its application for thermosensitive and hard-to-machine materials. With a strong foundation in Safety Engineering from his undergraduate studies, Chang has contributed significantly to the field through his pioneering research on the thermal deformation mechanisms in abrasive waterjet machining. He has actively participated in national and special technology innovation grants, where his work addresses advanced engineering solutions for challenging machining processes. Chang’s research collaborations with fellow experts have yielded insights into the thermal effects, cycling mechanisms, and microstructural transformations associated with machining titanium alloys, enhancing their applicability across industries.

Professional Profile

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Summary of Suitability for the Research for Best Researcher Award

Shuaikang Chang’s focused research, early contributions through publication, and engagement in high-impact projects position him as a competitive candidate for the Research for Best Researcher Award. His work aligns with the award’s objective to honor outstanding research contributions and innovation, making him a strong contender for this recognition.

🎓 Education

Shuaikang Chang is currently pursuing his Ph.D. in Safety Science & Engineering through an integrated Master’s and Ph.D. program at Chongqing University. He completed his Bachelor of Engineering (BEng) in Safety Engineering at the same institution, where he developed a solid grounding in engineering principles and safety protocols. During his postgraduate studies, Chang has been associated with the School of Resources and Safety Engineering, Chongqing University. His academic journey reflects a progressive focus on machining technologies and material safety, driven by an interdisciplinary approach. Chang’s coursework and practical experience have centered on the innovative application of waterjet machining, supported by his participation in specialized research projects and high-impact studies that push the boundaries of conventional engineering. He has skillfully leveraged academic resources to deepen his expertise, aligning with his aspiration to create safer and more effective industrial solutions.

💼  Experience 

Shuaikang Chang has been an active postgraduate researcher at the School of Resources and Safety Engineering, Chongqing University, since 2021. His experience primarily revolves around developing advanced abrasive waterjet machining techniques tailored for complex materials. Chang’s research evaluates ultra-high-pressure abrasive waterjets for thermosensitive and hard-to-machine materials, focusing on thermal cycling mechanisms and deformation behaviors. His expertise also extends to cryogenic techniques, investigating the effects of liquid nitrogen-assisted waterjet machining on material properties. Throughout his studies, he has contributed to multiple high-profile research grants, including a National Natural Science Foundation of China project that examined rock fracturing mechanisms using flash boiling liquid carbon dioxide jets. Chang’s insights have informed safer, more efficient machining processes, as evidenced by his publications in respected journals. His work reflects both technical rigor and a commitment to advancing machining technology for industrial applications.

🏅  Awards and Honors

Shuaikang Chang has received recognition for his contributions to engineering and safety science. His achievements include awards related to his pioneering research on abrasive waterjet machining, where he has advanced the understanding of thermal effects and deformation mechanisms on complex materials. Through his involvement in significant research grants from the National Natural Science Foundation of China and the Special Key Project for Technological Innovation in Chongqing, Chang has demonstrated excellence in both academic and applied research settings. His work has been acknowledged for its impact on the field of high-pressure waterjet technology, earning him the esteem of his peers and supervisors. Chang continues to receive commendations for his studies on material properties and safety protocols in machining processes, solidifying his reputation as a leading researcher within his field.

🌍  Research Focus 

Shuaikang Chang’s research focuses on the development and application of ultra-high-pressure abrasive waterjet machining for materials that are traditionally difficult to process. His work investigates the thermal deformation and material property changes induced by high-pressure jet technology, with a particular emphasis on thermosensitive alloys like Ti-6Al-4V. Chang’s research explores how varying jet pressures and the introduction of liquid nitrogen affect the microstructure and macro-properties of materials, aiming to extend the applicability of this machining technology. His studies on the deformation mechanisms and thermal cycling behaviors have the potential to influence several industries by improving safety, efficiency, and material integrity in manufacturing processes. Chang’s research is backed by notable grants, including projects under the National Natural Science Foundation of China, allowing him to push the boundaries of abrasive machining for broader, innovative applications.

📖 Publications Top Notes

Title: Thermal effects and deformation mechanisms in abrasive waterjet machining: insights from Ti-6Al-4V alloy for broader applications

 

Dr. Soheila Kookalani | Construction | Best Researcher Award

Dr. Soheila Kookalani | Construction | Best Researcher Award

Dr. Soheila Kookalani, Cambridge University, United Kingdom

Soheila Kookalani is a distinguished Research Associate at the University of Cambridge, specializing in Civil and Structural Engineering. She has a profound expertise in steel reuse, the circular economy, life-cycle assessment, and the integration of digital twin technologies in construction. Her research focuses on leveraging artificial intelligence and machine learning to optimize structural designs, promoting sustainability in construction. Soheila holds a Ph.D. in Civil and Structural Engineering from Shanghai Jiao Tong University, where she pioneered research on GFRP elastic gridshells. With a commitment to environmental responsibility, she continuously explores innovative ways to integrate sustainable practices into building designs, aiming to revolutionize construction methodologies. She has numerous publications in leading journals, demonstrating her contribution to both academia and the industry. Her work emphasizes sustainable engineering practices that align with modern technological advancements, particularly in the realm of structural optimization and reuse strategies.

Professional Profile

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Summary of Suitability for the Research for Best Researcher Award

Soheila Kookalani’s innovative approach to structural engineering, coupled with her strong commitment to sustainability and integration of advanced technologies, positions her as a highly suitable candidate for the Research for Best Researcher Award. Her work has significant implications for the future of sustainable construction, making her a valuable asset to both academia and industry.

🎓 Education 

Soheila Kookalani pursued her academic journey with a solid foundation in architectural and civil engineering. She earned her Bachelor of Science in Architectural Engineering from Azad University in Iran, where her thesis explored hybrid architecture in cinematic arts. She then advanced her studies with a Master of Science in Civil and Structural Engineering from Hohai University, China, focusing on the seismic performance of hybrid structures in high-rise buildings. Her academic journey culminated with a Ph.D. from Shanghai Jiao Tong University, China, where she focused on the structural optimization of GFRP elastic gridshells using machine learning techniques. Her doctoral research contributed to advancing knowledge in structural design and building sustainability. Throughout her studies, Soheila has consistently integrated innovative technologies, such as artificial intelligence and machine learning, into her research, making her an authority in the field of structural design and optimization for sustainable construction.

💼 Experience 

Soheila Kookalani has accumulated extensive experience in civil and structural engineering, with a primary focus on sustainable design practices. She currently serves as a Research Associate at the University of Cambridge, where she is engaged in a groundbreaking project on the reuse of structural steel in construction. Her experience spans across diverse areas, including the circular economy, life-cycle assessment, building information modeling (BIM), and digital twin technology. From 2018 to 2022, she conducted research on GFRP elastic gridshells as part of her Ph.D. at Shanghai Jiao Tong University. Prior to this, Soheila gained practical experience working on seismic performance evaluation of hybrid structures during her Master’s at Hohai University. Her expertise also extends to the application of artificial intelligence in optimizing structural designs, demonstrating her capacity to bridge the gap between theoretical research and practical application in sustainable construction.

🏅Awards and Honors 

Throughout her academic and professional career, Soheila Kookalani has been recognized for her outstanding contributions to civil and structural engineering. She has received several prestigious awards and honors, including recognition from leading engineering conferences and academic institutions. Her work on the integration of AI and machine learning in structural design has garnered international attention, earning her accolades for innovation in sustainable construction. Soheila has also been honored for her research on GFRP elastic gridshells, receiving commendations for excellence in structural optimization and sustainable design. Her role as a published author in top-tier engineering journals has further solidified her reputation as a leading researcher in the field. Additionally, Soheila’s contributions to the reuse of structural steel and her involvement in cutting-edge projects at the University of Cambridge have earned her numerous industry awards, highlighting her commitment to environmental responsibility and sustainable engineering practices.

🌍 Research Focus 

Soheila Kookalani’s research is centered on the intersection of civil engineering, sustainability, and advanced technology. Her primary focus is on steel reuse, promoting a circular economy in construction through the reuse of structural components. She is also deeply involved in life-cycle assessments, aiming to reduce the environmental impact of construction projects. Her research integrates building information modeling (BIM) and digital twin technology to enhance the design, monitoring, and optimization of construction projects. Soheila is particularly interested in applying artificial intelligence (AI) and machine learning to optimize structural designs, especially in the context of GFRP elastic gridshells. Her work on generative AI in structural engineering seeks to streamline design processes and improve sustainability. By combining these advanced technologies, her research contributes to developing more efficient, eco-friendly building practices that align with global sustainability goals.

📖 Publication Top Notes

  • BIM-based augmented reality for facility maintenance management
    • Cited by: 24
  • Structural analysis of GFRP elastic gridshell structures by particle swarm optimization and least square support vector machine algorithms
    • Cited by: 18
  • Shape optimization of GFRP elastic gridshells by the weighted Lagrange ε-twin support vector machine and multi-objective particle swarm optimization algorithm considering …
    • Cited by: 14
  • An analytic approach to predict the shape and internal forces of barrel vault elastic gridshells during lifting construction
    • Cited by: 14
  • Effect of Fluid Viscous Damper parameters on the seismic performance
    • Cited by: 14