Mr.Jiaqi Wang| Microstructure | Best Researcher Award
Mr, Jiaqi Wang,Northeastern University, Shenyang, China, China.
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Summary:
Mr. Jiaqi Wang is a promising researcher with a solid background in mechanical engineering, particularly in the study of smart materials and advanced machining techniques. His academic achievements, leadership in research projects, and contributions to innovative machining solutions make him a strong contender for the Research for Best Researcher Award. His focus on sustainable technologies also aligns with current industry trends.
Professional Profiles:
š Education :
Master of Mechanical Engineering (2022.09āPresent),Northeastern University, China
Wang Jiaqi is currently pursuing his Master’s degree in Mechanical Engineering at Northeastern University. His studies focus on advanced topics, including mechanical control systems, optimization design, and robotic systems design. These areas provide him with a strong foundation in engineering principles and mechanical innovation.,Bachelor of Mechanical Engineering (2018.09ā2022.06)
Northeastern University, China,Wang completed his undergraduate degree at the same institution. His coursework focused on mechanical control, sensor technology, and micro mechanical design, laying the groundwork for his expertise in these domains.
š¢Ā Experience:
Graduate Innovation Ability Training Project (2024.01-2025.01, Principal Investigator)
Research on Green and Efficient Milling Removal Mechanism and Damage Suppression Strategy of NiTi Intelligent Alloy
In this ongoing project, Wang proposed a novel method using supercritical carbon dioxide nanofluid in low-temperature micro lubrication to enhance cooling and lubrication performance. The objective is to improve the milling efficiency and reduce damage in NiTi alloy processing.,Invention Patent Project (2023.12-2024.02, Principal Investigator)
An Electromagnetic Rotating Rapid Tool Drop Device and Method for Freezing Cutting Transient
Wang developed an electromagnetic rotating tool drop device specifically for freezing cutting processes. Functional testing of this device has been successfully completed.,National Natural Science Foundation of China Project (2024.01-2026.12, Team Member)
Research on Multi-effect Collaborative Milling Removal Mechanism and Damage Suppression Strategy of SiCnp/NiTi SMA Intelligent Composite Materials
Wang plays a key role in finite element modeling and simulation research on intelligent composite materials, contributing to the overall project goal of developing new damage suppression strategies.
š ļøSkills:
Proficient in finite element modeling and simulation techniques,Experienced in mechanical optimization design,Skilled in micro mechanical design and sensor technology,Knowledgeable in advanced manufacturing processes, including green milling and damage suppression,Expertise in robotic system design and control technologies
Research Focus :
Wang Jiaqi’s research centers on the green and efficient machining of advanced smart materials, especially NiTi alloys and intelligent composites. His passion lies in developing methodologies that minimize damage during machining by employing enhanced cooling and lubrication techniques, such as supercritical carbon dioxide nanofluids. His work also involves finite element modeling to simulate the behavior of these materials under various machining conditions.
š¬Awards:
2024 Graduate First Class Academic Scholarship2023 Graduate First Class Academic Scholarship,2022 University Second Class Academic Scholarship
Conclusion:
In conclusion, Mr. Wang is a strong candidate for the Research for Best Researcher Award. His leadership in advanced research projects, academic achievements, and innovative contributions in the field of NiTi alloys demonstrate a high level of competency and promise. While there are areas for growth, particularly in international recognition and diversification of research, his current achievements already position him as a deserving candidate for the award.
Publications :
UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-Wise Perspective with Transformer
UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-Wise Perspective with Transformer