Feng Wei | Intelligent Driving | Best Researcher Award

Published on by China Scientist

 Dr. Feng Wei | Intelligent Driving | Best Researcher Award

Feng Wei is a PhD student at Tianjin University of Science and Technology, specializing in intelligent driving, image processing, and multimodal fusion. His research focuses on driver drowsiness detection, neural networks, and face super-resolution. He has successfully completed multiple research projects, published five high-impact journal articles, and applied for eight patents. Feng Wei was awarded the Silver Medal at the 49th International Exhibition of Inventions of Geneva for his innovative work on driver fatigue detection. With expertise in AI and human-computer interaction, he continues to develop advanced solutions for intelligent transportation and safety systems.

 Dr. Feng Wei | Tianjin University of Science and Technology | China

Profile

SCOPUS ID

🎓Education

  • Feng Wei is a PhD student at the College of Artificial Intelligence and the College of Mechanical Engineering at Tianjin University of Science and Technology, China. His academic journey has been focused on the intersection of artificial intelligence and mechanical engineering, equipping him with a deep understanding of cutting-edge technologies in these fields.

👨‍🏫Experience

  • Feng Wei has actively contributed to multiple research projects, successfully completing three provincial and ministerial-level projects, with one as the principal investigator. Additionally, he has led and participated in two industry-funded projects, demonstrating his ability to bridge academic research with real-world applications. His work extends to collaborative projects, including the development of an AI Facial Recognition Interaction System with a budget of 1 million CNY and a Graph Database-Based Graph Analysis System with a budget of 300,000 CNY.

🏆Awards and Recognitions

  • Feng Wei was honored with the Silver Medal at the 49th International Exhibition of Inventions of Geneva for his groundbreaking project on “Driver Fatigue and Abnormal Behavior Detection Technology Based on Multimodal Information.” This recognition highlights his innovative contributions to intelligent driving and human-computer interaction technologies.

💡Skills and Certifications

  • With expertise in artificial intelligence, image processing, and multimodal fusion, Feng Wei specializes in driver drowsiness detection, neural networks, and face super-resolution. His proficiency in advanced AI-driven technologies enables him to develop innovative solutions for complex problems in intelligent transportation systems.

🔬 Research Focus

  • Feng Wei’s research revolves around intelligent driving, focusing on driver drowsiness detection and multimodal analysis to enhance road safety. His work effectively addresses the challenge of individual driver variability in drowsy driving detection, contributing significantly to the field. He has published five high-quality journal articles, four of which are in top-tier SCI Q1 journals. Additionally, he has applied for eight patents, with one already published, showcasing his commitment to technological innovation and real-world impact.

🌎Conclusion

  • Feng Wei’s research addresses critical societal and technological challenges, particularly in transportation safety. His innovative methodologies, backed by strong academic publications, industry collaborations, and patents, establish him as a leading expert in his field. Given his outstanding contributions and global recognition, he is highly suitable for the Best Researcher Award.

📖Publications

  • A Multi-Aware Graph Convolutional Network for Driver Drowsiness Detection
    Authors: L. Lin, S. Wang, J. Yang, F. Wei
    Journal: Knowledge-Based Systems, 2024

Prof. Ni Linglin | Transportation | Best Researcher Award

Published on by China Scientist

Prof. Ni Linglin | Transportation | Best Researcher Award

Prof. Linglin Ni is a professor in the Department of Logistics Management at Beijing Wuzi University. She holds a Ph.D. in Logistics Engineering from Central South University and has completed postdoctoral research at Zhejiang University. As a visiting scholar at Rensselaer Polytechnic Institute, she gained international experience in logistics and data analysis. Her research focuses on big data analysis, logistics network optimization, and transportation econometrics. With over 15 years of teaching experience, Prof. Ni has earned accolades such as the Excellent Teacher Award and actively contributes to professional organizations, including the China Society of Logistics.

Prof. Ni Linglin | Beijing Wuzi University | China

Profile

SCOPUS  ID

ORCID ID

🎓 Education

  • Linglin Ni, Ph.D., has a distinguished academic background. She completed her Ph.D. in Logistics Engineering at Central South University (2008–2012), following a Master’s degree in Management Science and Engineering (2002–2005) and a Bachelor’s degree in Transportation and Traffic Engineering (1998–2002) at the same institution. Additionally, she pursued postdoctoral studies at Zhejiang University and gained international exposure as a visiting scholar at Rensselaer Polytechnic Institute during 2014–2015 and 2018–2019.

💼 Experience

  • Prof. Linglin Ni currently serves as a full-time faculty member in the Department of Logistics Management at Beijing Wuzi University, a role she has held since August 2022. Prior to this, she spent over 15 years as a faculty member at Zhejiang University of Finance & Economics, Hangzhou, where she contributed significantly to teaching and research in logistics and related fields. Her teaching portfolio includes courses such as Logistics, ERP Sand Table Simulation, Distribution and Distribution Center, Consumer Behavior, and Operations Research.

 🏆 Honors and Awards

  • Prof. Ni has been recognized for her outstanding contributions to academia and student mentorship. She was named Excellent Teacher of Zhejiang University of Finance & Economics in 2010–2011 and received the Excellent Tutor Award during 2011–2012. Additionally, she secured the First Prize in the Zhejiang Final of the Eighth National College “UF Cup” Contest of ERP Sand Table Simulation Operation in 2012.

🛠️ Skills and Certifications

  • Prof. Ni is proficient in logistics management, supply chain optimization, and ERP simulation, with hands-on expertise in teaching and guiding students in these domains. She is an active member of the China Society of Logistics, Zhejiang Association of Supply Chain, and Zhejiang Express Industry Association, further reflecting her professional commitment to the field of logistics and supply chain management.

🔬 Research Focus

  • Prof. Ni’s research interests lie at the intersection of logistics and advanced analytics. Her primary areas of focus include big data analysis, optimization of logistics networks, and the econometrics of transportation. Through her work, she contributes to the advancement of efficient logistics systems and transportation solutions.

Conclusion

  • Prof. Ni’s expertise, combined with her professional achievements, positions her as a deserving candidate for the “Research for Best Researcher Award.” Her contributions to logistics education, research, and optimization solutions exemplify the qualities the award seeks to honor. Recognizing her achievements would not only validate her impact but also inspire further advancements in the logistics and transportation sectors.

📄Publications

  • Using a spatial autoregressive model with spatial autoregressive disturbances to investigate origin-destination trip flows
    Authors: Ni, L., Zhang, D.
    Journal: PLoS ONE, 2024, 19(6 June), e0305932
  • Exploring the influence of relative attractiveness in green spaces on urban movements: A potential to kinetic energy framework
    Authors: Ni, L., Zhang, D., Yang, Y., Huang, J.
    Journal: Journal of Cleaner Production, 2024, 434, 139850
  • Analyzing time-varying trip distributions with a random-effect spatial OD dependence model
    Authors: Ni, L., Wang, X., Chen, X., Zhang, D.
    Journal: PLoS ONE, 2023, 18(1 January), e0280162
  • Investigating Travel Flow Differences between Peak Hours with Spatial Model with Endogenous Weight Matrix Using Automatic Vehicle Identification Data
    Authors: Zhou, Y., He, Z., Chen, J.-Y., Ni, L., Dong, J.
    Journal: Genetics Research, 2022, 2022, 7729068
  • The impact of intercity economic complementarity on HSR volume in the context of megalopolization
    Authors: Hu, X., Wang, X.C., Ni, L., Shi, F.
    Journal: Journal of Transport Geography, 2022, 98, 103222