Prof. Yanlong Tai | Machine Learning | Best Researcher Award

Prof. Yanlong Tai | Machine Learning | Best Researcher Award

Prof. Yanlong Tai, shenzhen institute of science and technology, China academic of science, China

Prof. Dr. Yanlong Tai is a distinguished researcher and professor in the field of smart sensing and flexible electronics. He is the Principal Investigator of the Smart-Sensing-Lab (SM-SE Lab.-SIAT) and serves as the Head of both the SIAT-UAEU International Smart Sensing & Energy Joint Lab and the SIAT-Fudan University (Zhuhai) Joint Innovation Center. Currently, he is a Full Professor at the Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), China, and a Joint Professor at the University of Science & Technology Shenzhen. Dr. Tai earned his Ph.D. from Fudan University, China (2009-2012), and was a visiting student at OHM University, Germany (2011-2012). He also holds Bachelor’s and Master’s degrees from Anhui University (2001-2008). His professional journey includes extensive research experience across multiple international institutions. He served as a Postdoctoral Researcher at University of California, Davis, USA (2012-2013), Fraunhofer ENAS, Chemnitz, Germany (2013-2014), and KAUST, Saudi Arabia (2014-2017). He later worked as a Research Scientist at Masdar Institute, UAE (2017-2019) before joining SIAT as a Professor in 2019.

Professional Profile:

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Summary of Suitability for Best Researcher Award – Prof. Dr. Yanlong Tai

Prof. Dr. Yanlong Tai is an outstanding researcher and innovator, making him a highly suitable candidate for the Best Researcher Award. His extensive experience, leadership roles, and impactful research in smart materials, energy harvesting, and wearable electronics position him as a global leader in advanced sensing technologies.

🎓 Education

  • Ph.D. (2009 – 2012)Fudan University, China

  • Visiting Student (2011 – 2012)OHM University, Germany

  • Bachelor & Master Degree (2001 – 2008)Anhui University, China

💼 Work Experience

  • Professor (2019 – Present) – Shenzhen Institutes of Advanced Technology (SIAT), CAS, China

  • Research Scientist (2017 – 2019) – Masdar Institute, United Arab Emirates

  • Postdoc Researcher (2014 – 2017) – King Abdullah University of Science and Technology (KAUST), Saudi Arabia

  • Postdoc Researcher (2013 – 2014) – Fraunhofer ENAS, Chemnitz, Germany

  • Postdoc Researcher (2012 – 2013) – University of California, Davis, USA

🏆 Achievements, Awards & Honors

  • 📌 Principal Investigator of Smart-Sensing-Lab (SM-SE Lab.-SIAT)

  • 🏅 Head of SIAT-UAEU International Smart Sensing & Energy Joint Lab

  • 🏅 Head of SIAT-Fudan University (Zhuhai) Joint Innovation Center

  • 🎖️ Full Professor at SIAT, CAS, Shenzhen, China

  • 🎖️ Joint Professor at the University of Science & Technology, Shenzhen

Publication Top Notes:

CITED:663
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Dr. Xianchao Zhu | Reinforcement Learning | Best Researcher Award

Dr. Xianchao Zhu | Reinforcement Learning | Best Researcher Award 

Dr. Xianchao Zhu, School of Artificial Intelligence and Big Data/Henan University of Technology, China

Dr. Xianchao Zhu is a Lecturer at the School of Artificial Intelligence and Big Data at Henan University of Technology, a position he has held since 2022. He completed his Ph.D. in Physics at the Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, where his research focused on “Abstraction-based Reinforcement Learning Algorithms and its Quantization.” Prior to his doctoral studies, Dr. Zhu earned a Master of Science in Computer Architecture from the School of Computer, Central China Normal University, with a thesis on “Research on Dimensionality Reduction Visualization Method of High-Dimensional Biological Data Based on Gradient Descent and Adaptive Learning.” His academic interests span artificial intelligence, reinforcement learning, and high-dimensional data analysis.

Professional Profile:

 

ORCID

Education

  • Ph.D. in Physics
    Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China
    2018 – 2022
    Thesis Title: Abstraction-based Reinforcement Learning Algorithms and its Quantization.
  • M.Sc. in Computer Architecture
    School of Computer, Central China Normal University
    2015 – 2018
    Thesis Title: Research on Dimensionality Reduction Visualization Method of High-Dimensional Biological Data Based on Gradient Descent and Adaptive Learning.

Employment History

  • Lecturer
    School of Artificial Intelligence and Big Data, Henan University of Technology
    2022 – Present

Publication top Notes:

Salience Interest Option: Temporal abstraction with salience interest functions

Generalization Enhancement of Visual Reinforcement Learning through Internal States

Efficient relation extraction via quantum reinforcement learning

MDMD options discovery for accelerating exploration in sparse-reward domains