Bingshuo Chen | Transport | Best Researcher Award

Published on by Academic Awards

Dr. Bingshuo Chen | Transport | Best Researcher Award

Dr. Bingshuo Chen, Research Institute of Highway, Ministry of Transport, China

Prof. Bingshuo Chen holds a Ph.D. from Beijing University of Technology, mentored by Professors Liu Xiaoming and Zhao Xiaohua.  A member of the Communist Party of China, he works at the Research Institute of Highway, Ministry of Transport.  His research focuses on driving behavior, traffic psychology, and road safety education. He has published 8 papers (3 SSCI, 2 in JCR Q1) and co-authored 2 academic books. He earned 2 national awards and 9 university honors, including the Graduate Innovation Award and Outstanding Graduate of Shandong Province. His work combines scientific insight with societal impact.

Publication Profile

Scopus

🎓 Academic Qualifications

rof. Bingshuo Chen earned his Ph.D. from Beijing University of Technology, a respected institution, under the mentorship of Professors Liu Xiaoming and Zhao Xiaohua. This academic foundation from a well-regarded university provides a strong base for high-level research activities.

🏆 Awards and Honors

Prof. Chen has received two national-level awards, notably the Third Prize in the National College Student English Competition (Category C). In addition, he has been recognized with nine university-level honors, including the Graduate Innovation Award and the title of “Outstanding Graduate of Shandong Province.” These accolades reflect academic excellence and leadership.

Research Focus

Prof. Bingshuo Chen holds a Ph.D. from Beijing University of Technology, mentored by Professors Liu Xiaoming and Zhao Xiaohua.  A member of the Communist Party of China, he works at the Research Institute of Highway, Ministry of Transport.  His research focuses on driving behavior, traffic psychology, and road safety education.  He has published 8 papers (3 SSCI, 2 in JCR Q1) and co-authored 2 academic books.  He earned 2 national awards and 9 university honors, including the Graduate Innovation Award and Outstanding Graduate of Shandong Province.  His work combines scientific insight with societal impact.

Conclusion

Prof. Bingshuo Chen is a highly suitable candidate for the Research for Best Researcher Award. His work addresses real-world challenges in traffic safety and psychology, backed by a solid record of scientific contributions and awards.

Publication Top Notes

📄 Study on Evaluation and Influencing Factors of Cognitive Driving Ability in Elderly Drivers – 2024

📄 Why do older drivers self-regulate: Psychological factors influencing self-regulation in a Chinese sample – Cited by – 8

📄 How does older and younger drivers’ risk cognition affect the safety performance: A driving simulator study of sudden lane-changing of the leading vehicle

📄 Mapping the knowledge domain of crash risk in older drivers studies: A scientometric analysis

📄 Exploring the associations of demographics and scale measures with cognitive driving behavior among older drivers in China Cited by – 6

Shuli Wen | Transportation Electrification | Best Researcher Award

Published on by Academic Awards

Assoc Prof Dr. Shuli Wen | Transportation Electrification | Best Researcher Award

Assoc Prof Dr. Shuli Wen, Shanghai Jiao Tong University, China

🎓 Assoc. Prof. Dr. Shuli Wen is an accomplished academic and researcher at Shanghai Jiao Tong University, China, specializing in Transportation Electrification, Smart Grid, and Renewable Integration. With a Ph.D. in Control Science and Engineering from Harbin Engineering University, Dr. Wen has published extensively, with an h-index of 16 and over 1,142 citations. Their research has led to significant breakthroughs in Maritime Mobile Energy Internet, enhancing port power systems’ stability and ship efficiency. Dr. Wen’s contributions include 33 SCI-indexed papers, 50 patents, and editorial roles in prestigious journals. They are a Senior IEEE member and actively collaborate with industry leaders. 🌐

 

Publication Profile

Google Scholar

🎓 Education

Dr. Shuli Wen earned a Ph.D. in Control Science and Engineering from Harbin Engineering University in 2016, following a Bachelor’s in Electrical Engineering and Automation from Harbin Institute of Technology in 2010.

Research Focus

Dr. Shuli Wen’s research focuses on optimizing ship power systems, particularly through hybrid PV/diesel/battery configurations and energy storage system (ESS) allocations. 🚢 Their pioneering work addresses complex challenges such as energy management in port environments and real-time power fluctuation identification using advanced technologies like LSTM neural networks. Dr. Wen’s contributions in spatiotemporal solar irradiation forecasting and optimal energy management for all-electric ships enhance operational efficiency and sustainability in maritime applications. Their extensive publication record and patent filings underscore their leadership in smart grid integration, renewable energy, and computational intelligence, making significant strides in advancing maritime energy systems.

 

Publication Top Notes

  • Optimal sizing of hybrid PV/diesel/battery in ship power system 📊 Cited by 431, 2015
  • Economic allocation for energy storage system considering wind power distribution 📊 Cited by 322, 2014
  • Allocation of ESS by interval optimization method considering impact of ship swinging on hybrid PV/diesel ship power system 📊 Cited by 140, 2016
  • Real-time identification of power fluctuations based on LSTM recurrent neural network: A case study on Singapore power system 📊 Cited by 122, 2019
  • Day-ahead spatiotemporal solar irradiation forecasting using frequency-based hybrid principal component analysis and neural network 📊 Cited by 110, 2019
  • Optimal sizing of hybrid energy storage sub-systems in PV/diesel ship power system using frequency analysis 📊 Cited by 105, 2017
  • Data-driven robust coordination of generation and demand-side in photovoltaic integrated all-electric ship microgrids 📊 Cited by 80, 2019
  • A hybrid ensemble model for interval prediction of solar power output in ship onboard power systems 📊 Cited by 65, 2019
  • Day-ahead spatio-temporal forecasting of solar irradiation along a navigation route 📊 Cited by 60, 2018
  • Coordinated optimal energy management and voyage scheduling for all-electric ships based on predicted shore-side electricity price 📊 Cited by 56, 2020