Chao-Chen Gu | Engineering | Best Researcher Award

Prof Dr. Chao-Chen Gu | Engineering | Best Researcher Award

Prof., Shanghai Jiao Tong University, China

Chao-Chen Gu is a distinguished professor at the School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University. Renowned for his contributions to the fields of electromechanical systems, intelligent robotics, and precision instruments, he has pioneered research in intelligent machine vision and advanced motion control. With numerous national and provincial key projects under his belt, Professor Gu is a leading figure in his domain, recognized for his innovative approach to solving complex engineering problems.

Profile

Strengths for the Award

  1. Extensive Research Projects: Professor Gu has completed over ten national and provincial-level key projects. This demonstrates his active involvement in significant research efforts that likely have substantial community impact.
  2. Innovative Contributions: His work in machine vision and precision control, especially innovations in micro precision measurement, robot vision cognition, and high-order nonlinear system disturbance rejection and control, indicates a focus on advanced technology that can significantly benefit various sectors, including healthcare, manufacturing, and robotics.
  3. High Volume of Patents and Publications: With over 70 patents and 80 published works, Professor Gu’s contributions to his field are well-documented and recognized, highlighting his role in advancing technology and engineering.
  4. Industry Projects: The completion of more than five consultancy or industry projects suggests practical applications of his research, which is a key factor for community impact.

Areas for Improvement

  1. Professional Memberships and Collaborations: There is a lack of listed professional memberships and collaborations. Engaging more with professional organizations and collaborating with other researchers or institutions could enhance the reach and impact of his work.
  2. Books and Editorial Appointments: No books or editorial appointments were mentioned. Authoring books and holding editorial positions could further establish his authority in his field and disseminate his research more broadly.
  3. Explicit Community Impact: While his research is undoubtedly advanced, the specific community impact of his projects could be more explicitly stated. Providing concrete examples of how his work has benefitted communities or specific sectors would strengthen his application.

🎓 Education:

Chao-Chen Gu earned his bachelor’s degree from Shandong University in 2007, followed by a Ph.D. in Mechanical Engineering from Shanghai Jiao Tong University in 2013. His academic journey has equipped him with a solid foundation in mechanical engineering and advanced technological systems, propelling his research career forward.

🧑‍💼 Experience:

Currently serving as a professor at Shanghai Jiao Tong University, Chao-Chen Gu has led more than ten key national and provincial-level projects. His expertise spans electromechanical systems, intelligent robotics, and precision instruments, with a notable focus on intelligent machine vision and advanced motion control.

🔬 Research Interests:

Chao-Chen Gu’s research interests lie in the realms of electromechanical systems, intelligent robotics, and precision instruments. He is particularly focused on intelligent machine vision and advanced motion control, contributing significantly to innovations in micro precision measurement, robot vision cognition, and high-order nonlinear system disturbance rejection and control.

🏆 Awards:

Chao-Chen Gu has not specified individual awards, but his prolific contributions to research and numerous completed projects reflect his standing as a leader in his field.

Publications 

  1. An integrated AHP and VIKOR for design concept evaluation based on rough number
    Authors: GN Zhu, J Hu, J Qi, CC Gu, YH Peng
    Journal: Advanced Engineering Informatics
    Year: 2015
    Cited by: 329 articles
    Link to publication
  2. Complementary patch for weakly supervised semantic segmentation
    Authors: F Zhang, C Gu, C Zhang, Y Dai
    Journal: Proceedings of the IEEE/CVF International Conference on Computer Vision
    Year: 2021
    Cited by: 131 articles
    Link to publication
  3. FCBS model for functional knowledge representation in conceptual design
    Authors: CC Gu, J Hu, YH Peng, S Li
    Journal: Journal of Engineering Design
    Year: 2012
    Cited by: 48 articles
    Link to publication
  4. Corporate innovation and R&D expenditure disclosures
    Authors: C Chen, J Gu, R Luo
    Journal: Technological Forecasting and Social Change
    Year: 2022
    Cited by: 30 articles
    Link to publication
  5. Imaging Mueller matrix ellipsometry with sub-micron resolution based on back focal plane scanning
    Authors: C Chen, X Chen, C Wang, S Sheng, L Song, H Gu, S Liu
    Journal: Optics Express
    Year: 2021
    Cited by: 26 articles
    Link to publication
  6. SVMs multi-class loss feedback based discriminative dictionary learning for image classification
    Authors: BQ Yang, XP Guan, JW Zhu, CC Gu, KJ Wu, JJ Xu
    Journal: Pattern Recognition
    Year: 2021
    Link to publication

 

Xinke Liu | Engineering | Best Researcher Award

Assoc Prof Dr. Xinke Liu | Engineering | Best Researcher Award

Assoc. Prof. Shenzhen University, China

👨‍🏫 Liu, Ph.D. is an accomplished Associate Professor at Shenzhen University, specializing in wide bandgap semiconductor materials and electronic devices. With a prolific publication record of over 110 papers as a first or corresponding author, he has garnered more than 3040 citations and an impressive h-index of 31. His research focuses on the development of advanced GaN power electronics using CMOS-compatible materials and processes, aiming to revolutionize wide-bandgap power devices for future computing, 5G/6G communication, and electric cars.

Profile

Google Scholar

Education

🎓 Liu completed his Sc. long in Material Science from the National University of Singapore in 2004. He also holds a Graduate Certificate in Management of Technology from the National University of Singapore, obtained between 2011-2012.

Experience

🔬 Liu has a rich professional background, including hosting roles and research fellowships. He worked with Professor Ali Javey at the University of California, Berkeley, focusing on electronic devices related to novel 2D materials. He also collaborated with Professor Kah-Wee Ang at the National University of Singapore, and served as a professor at the Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, where he researched GaN-based and GaN/2D heterojunction power devices.

Research Interests

🧠 Liu’s research interests include the development of advanced GaN power electronics using CMOS-compatible materials and processes. He explores advanced electronic devices such as Schottky Barrier Diodes (SBDs), PN Diodes (PNDs), High Voltage High Electron Mobility Transistors (HV-HEMTs), and Radio Frequency High Electron Mobility Transistors (RF-HEMTs). His work aims to produce electronic and optoelectronic chips that will drive innovation in wide-bandgap power devices for computing, communication, and automotive industries.

Awards

🏅 Liu has received numerous awards, including the Shenzhen Youth Science and Technology Award (2023), IEEE Senior Member (2021), Guangdong Provincial Science and Technology Progress Award (2022), and the Excellent Teaching Award of Shenzhen University (2020). He is recognized as one of Stanford University’s World’s Top 2% Scientists (2019, 2020, 2022) and has earned the Shenzhen Peacock Plan B Award (2014), among other honors.

Publications

Artificial synapses based on multiterminal memtransistors for neuromorphic application

Few-layer black phosphorus carbide field-effect transistor via carbon doping

Impact and Origin of Interface States in MOS Capacitor with Monolayer MoS2 and HfO2 High-k Dielectric

Down to ppb level NO2 detection by ZnO/rGO heterojunction based chemiresistive sensors

2D III-Nitride Materials: Properties, Growth, and Applications