Jie Li | Computational Methods | Best Researcher Award

Assoc. Prof. Dr. Jie Li | Computational Methods | Best Researcher Award

Teacher at Chongqing University of Science and Technology, China

Li Jie is an accomplished doctor, associate professor, and master’s supervisor at Shanghai Jiaotong University, where he also serves as a postdoctoral fellow. As the deputy director of the 2011 Collaborative Innovation Center for Smart Security in Chongqing, he leads initiatives in smart neurosurgery and participates actively in various professional committees related to artificial intelligence and smart transportation. An Associate Editor for IEEE Transactions on Emerging Topics in Computational Intelligence, he has contributed significantly to international conferences.

Profile🎓

Early Academic Pursuits🌱

Li Jie began his academic journey with a strong focus on artificial intelligence and smart technologies, laying a solid foundation for his future endeavors. His time at Tsinghua University and later at the University of Rhode Island enriched his understanding and broadened his research perspectives, preparing him for a distinguished career in academia and industry.

Professional Endeavors 💼

As a postdoctoral fellow at Shanghai Jiaotong University, Li Jie has undertaken significant leadership roles, including serving as the deputy director of the 2011 Collaborative Innovation Center for Smart Security in Chongqing. His involvement with the Smart Neurosurgery Group and various professional committees reflects his commitment to advancing healthcare through innovative technology and collaboration.

Contributions and Research Focus 🔍

Li Jie’s research primarily centers on smart security and neurosurgery, where he utilizes artificial intelligence to enhance medical practices. He has hosted 16 funded projects and has published over 40 academic papers in high-impact journals, showcasing his dedication to contributing valuable knowledge to the field.

Impact and Influence 🌍

With a reputation as a thought leader, Li Jie has made significant contributions that have influenced both academia and industry. His role as an Associate Editor for IEEE Transactions on Emerging Topics in Computational Intelligence and participation in various international conferences underscore his influence in shaping research agendas and fostering collaborations.

Academic Citations 📚

Li Jie’s work is widely recognized, as evidenced by his 40 published papers and the acclaim received for his book, “Artificial Intelligence.” His research has garnered citations that highlight its relevance and impact, establishing him as a respected figure in his field.

Technical Skills ⚙️

Possessing a robust set of technical skills, Li Jie excels in areas such as computational intelligence, data analysis, and machine learning. His expertise in securing over 40 invention patents demonstrates his innovative approach and practical application of technology in research.

Teaching Experience 👨‍🏫

As a master’s supervisor and associate professor, Li Jie has mentored numerous students, instilling in them a passion for research and innovation. His teaching methods emphasize practical applications of theory, preparing students for successful careers in technology and science.

Legacy and Future Contributions 🔮

Li Jie’s legacy is marked by his commitment to advancing smart technologies in healthcare. Looking ahead, he aims to expand his research collaborations internationally and engage in interdisciplinary projects, furthering the impact of his work on society and technology. His vision for the future underscores a dedication to innovation that will shape the next generation of researchers and practitioners.

Publication Top Notes📖

Metric learning based multi-branch network for tongue manifestation recognition
  • Authors: Ren, S., Wu, R., Luo, Q., Wang, Y., Li, J.
    Publication Year: 2024
FASCNet: An Edge-Computational Defect Detection Model for Industrial Parts
  • Authors: Li, J., Wu, R., Zhang, S., Chen, Y., Dong, Z.
    Publication Year: 2024
Multi-scale attention-based lightweight network with dilated convolutions for infrared and visible image fusion
  • Authors: Li, F., Zhou, Y., Chen, Y., Dong, Z., Tan, M.
    Publication Year: 2024
A Mixed-Precision Transformer Accelerator With Vector Tiling Systolic Array for License Plate Recognition in Unconstrained Scenarios
  • Authors: Li, J., Yan, D., He, F., Dong, Z., Jiang, M.
    Publication Year: 2024
A novel medical text classification model with Kalman filter for clinical decision making
  • Authors: Li, J., Huang, Q., Ren, S., Deng, B., Qin, Y.

           Publication Year: 2023

 

Rehmat Bashir | Advanced Computing | Best Researcher Award

Dr. Rehmat Bashir | Advanced Computing | Best Researcher Award 

Lecturer at University of Engineering and Technology, Lahore, Pakistan

Rehmat Bashir is a dedicated researcher and lecturer in Mechanical Engineering with a focus on fracture mechanics and stress corrosion cracking. Born on July 19, 1991, in Pakistan, he is currently based at Xi’an University of Science and Technology in China. With exceptional communication skills, Rehmat excels at connecting with students and colleagues from diverse backgrounds. He has a passion for exploring nature, which reflects his curiosity and desire for continuous learning. Throughout his academic career, he has been committed to advancing knowledge in his field, contributing to several high-impact publications, and mentoring master’s students in their research endeavors.

Profile:

Education:

Rehmat Bashir completed his Ph.D. in Mechanical Engineering at Xi’an University of Science and Technology from September 2018 to November 2023, focusing on crucial areas such as fracture mechanics and stress corrosion cracking in nuclear power plants. Prior to this, he earned his Master’s degree in Mechanical Engineering from the University of Engineering and Technology, Lahore, Pakistan, from January 2015 to July 2017. His foundational education includes a Bachelor of Science in Mechanical Engineering from the same institution, which he completed in June 2014. This strong academic background equips him with the knowledge and skills necessary for his research and teaching roles.

Professional experience:

With nearly nine years of teaching experience, Rehmat Bashir has been a lecturer at the University of Engineering and Technology, Lahore, since September 2014. His role involves delivering lectures, supervising student research, and managing laboratory activities. Rehmat’s extensive research experience is evident through his numerous publications in reputable journals, where he addresses significant engineering challenges. He actively engages in research projects related to fracture mechanics, contributing to advancements in safety and performance in nuclear engineering. His experience in lab management and student mentorship showcases his commitment to fostering a supportive learning environment while advancing the field of mechanical engineering.

Research focus:

Rehmat Bashir’s research primarily centers on fracture mechanics, particularly the study of stress corrosion cracking and fatigue cracking in nuclear power plants. His innovative work employs advanced methodologies, such as the Extended Finite Element Method (XFEM), to analyze crack propagation and the mechanical behavior of materials under stress. By investigating the interactions between cyclic loading and cracking rates, he aims to enhance the safety and efficiency of nuclear infrastructure. His research has significant implications for material science and engineering, contributing valuable insights into the durability and reliability of critical components in high-stakes environments. Rehmat’s dedication to advancing this field positions him as a valuable asset to both academia and industry.

Publication Top Notes:

  • Title: Interaction of Cyclic Loading (Low-Cyclic Fatigue) with Stress Corrosion Cracking (SCC) Growth Rate
    Authors: Rehmat Bashir, He Xue, Rui Guo, Yueqi Bi, Muhammad Usman
    Year: 2020
    Citations: 24
  • Title: Effect of XFEM Mesh Density (Mesh Size) on Stress Intensity Factors (K), Strain Gradient (d ε / Dr) and Stress Corrosion Cracking (SCC) Growth Rate
    Authors: Rehmat Bashir, He Xue, Jianlong Zhang, Rui Guo, Nasir Hayat, Ganbo Li, Yueqi Bi
    Year: 2020
    Citations: 15
  • Title: Effect of Material Macrostructural Parameters on Quantitative Stress Corrosion Cracking Plastic Zone Using Extended Finite Element Method in Welded Joints for Light Water Reactor Environment
    Authors: Rehmat Bashir, He Xue, Jianlong Zhang, Rui Guo
    Year: 2020
    Citations: 18
  • Title: Effect of Yield Strength Distribution Welded Joint on Crack Propagation Path and Crack Mechanical Tip Field
    Authors: Bi, Yueqi; Xiaoming Yuan; Jishuang Lv; Rehmat Bashir; Shuai Wang; He Xue
    Year: 2021
    Citations: 12
  • Title: Development of a Temperature-Controlled Resistance Micro-Change Experimental Device
    Authors: He Xue, Qishen Wei, Chenqiang Ni, Pengchao Xu, Rehmat Bashir, Liang Zhang
    Year: 2018
    Citations: 8
  • Title: Development of a Temperature-Controlled Resistance Micro-Change Experimental Device
    Authors: He Xue, Qishen Wei, Chenqiang Ni, Pengchao Xu, Rehmat Bashir, Liang Zhang
    Year: 2019
    Citations: 8
  • Title: Experimental Evaluation of Methanol-Gasoline Fuel Blend on Performance, Emissions and Lubricant Oil Deterioration in SI Engine
    Authors: Muhammad Ali Ijaz Malik, Muhammad Usman, Nasir Hayat, Syed Wasim Hassan Zubair, Rehmat Bashir, Ehtasham Ahmed
    Year: n.d.
    Citations: 10
  • Title: Mechanical Properties Evaluation and Crack Propagation Behavior in Dissimilar Metal Welded Joints of 304 L Austenitic Stainless Steel and SA508 Low-Alloy Steel
    Authors: Sun, Yuman; He Xue; Fuqiang Yang; Shuai Wang; Shun Zhang; Jinxuan He; Rehmat Bashir
    Year: 2022
    Citations: 5
  • Title: Cracking Driving Force at the Tip of SCC under Heterogeneous Material Mechanics Model of Safe-End Dissimilar Metal-Welded Joints in PWR
    Authors: Sun, Yuman; He Xue; Kuan Zhao; Yubiao Zhang; Youjun Zhao; Weiming Yan; Rehmat Bashir
    Year: 2022
    Citations: 3
  • Title: Enviro-Economic Assessment of HHO–CNG Mixture Utilization in Spark Ignition Engine for Performance and Environmental Sustainability
    Authors: Usman, Muhammad; Muhammad Ali Ijaz Malik; Rehmat Bashir; Fahid Riaz; Muhammad Juniad Raza; Khubaib Suleman; Abd Ul Rehman; Waqar Muhammad Ashraf; Jaroslaw Krzywanski
    Year: 2022
    Citations: 6