Dr. Peng Zhi | Deep Learning | Best Researcher Award

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Dr. Peng Zhi | Deep Learning | Best Researcher Award 

Dr. Peng Zhi, Lanzhou University, China

Peng Zhi is a Ph.D. candidate in Computer Science at Lanzhou University, China, specializing in computer vision, deep learning, and autonomous driving. He earned his Bachelor’s and Master’s degrees in Computer Science and Technology from Lanzhou University in 2017 and 2020, respectively. His research focuses on LiDAR-camera fusion, 3D object detection, and AI applications in intelligent transportation systems. He has published several high-impact papers in renowned journals and conferences, contributing to advancements in autonomous vehicle perception and artificial intelligence. Additionally, he has co-authored the book Theories and Practices of Self-Driving Vehicles, further solidifying his expertise in the field.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Peng Zhi is a strong candidate for the Best Researcher Award, given his innovative contributions to computer vision, deep learning, and autonomous driving. As a Ph.D. candidate at Lanzhou University, he has been actively involved in research that enhances LiDAR-based 3D object detection, cross-domain generalization, and deep learning applications in autonomous systems.

🎓 Education

  • Ph.D. in Computer Application Technology (2021 – Present)
    Lanzhou University, Lanzhou, China
  • Master’s in Computer System Architecture (2017 – 2020)
    Lanzhou University, Lanzhou, China
  • Bachelor’s in Computer Science and Technology (2013 – 2017)
    Lanzhou University, Lanzhou, China

💼 Work Experience

  • Ph.D. Candidate & Researcher (2021 – Present)
    Lanzhou University, Lanzhou, China

    • Conducts advanced research in computer vision, deep learning, and autonomous driving
    • Publishes in top-tier journals and conferences
    • Develops LiDAR and camera fusion models for 3D object detection

🏆 Achievements & Contributions

  • Published Multiple Research Papers 📄 in top journals and conferences, including Tsinghua Science and Technology, Electronic Research Archive, and IEEE ITSC
  • Author of a Book on Self-Driving Vehicles 📘 Theories and Practices of Self-Driving Vehicles (Elsevier, 2022)
  • Developed DefDeN Model 🤖 A deformable denoising-based LiDAR and camera feature fusion model for 3D object detection
  • Research on Autonomous Driving 🚗 Focused on boundary distribution estimation and cross-domain generalization for LiDAR-based 3D object detection

🏅 Awards & Honors

  • Best Paper Award 🏆 at an International Conference on Intelligent Transportation Systems (ITSC)
  • Outstanding Researcher Award 🎖️ at Lanzhou University for contributions to AI and autonomous driving
  • National Scholarship 🏅 for academic excellence in computer science and AI research

Publication Top Notes:

Cross-Domain Generalization for LiDAR-Based 3D Object Detection in Infrastructure and Vehicle Environments

Prof. Jin Ho Suh | Deep Neural Network Awards | Best Researcher Award

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Prof. Jin Ho Suh | Deep Neural Network Awards | Best Researcher Award

Prof. Jin Ho Suh, Pukyong National University, South Korea

Dr. Jin-Ho Suh is a distinguished professor and expert in robotics, currently leading the Field Robotics Laboratory (FRLab) within the Major of Mechanical System Engineering at Pukyong National University, South Korea. With a Ph.D. in Control Engineering from the Tokyo Institute of Technology, Japan, and over two decades of academic and professional experience, Dr. Suh has significantly contributed to the fields of robotics and mechanical systems. He has held prominent roles, including Director of the Institute of Control, Robotics, and Systems, and is a Senior Member of IEEE. His leadership extends to national initiatives as the Chairman of the National Core Technology Committee for Robotics in South Korea and as an expert member of the Presidential Advisory Council on Science & Technology.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award: Prof. Jin-Ho Suh

Prof. Jin-Ho Suh, a distinguished researcher in the field of robotics and control engineering, holds a Ph.D. in Control Engineering from the Tokyo Institute of Technology and currently serves as a professor at Pukyong National University in South Korea. His extensive academic and professional experience, combined with significant contributions to the field, makes him an excellent candidate for the Best Researcher Award.

Education 🎓

  • Ph.D. in Control Engineering
    Tokyo Institute of Technology, Japan (Dec 1998 – Mar 2002)
  • Master of Engineering
    Graduate School of Engineering, Pukyong National University, South Korea (Mar 1996 – Feb 1998)
  • Bachelor of Science in Mathematics
    Hanyang University, South Korea (Mar 1989 – Feb 1993)

Work Experience 🛠️

  • Professor (Sep 2018 – Present)
    Major of Mechanical System Engineering, Pukyong National University
  • Senior Member (Nov 2022 – Present)
    Institute of Electrical and Electronics Engineers (IEEE)
  • Director
    • Institute of Control, Robotics, and Systems (Jan 2022 – Present)
    • Korean Society for Precision and Engineering (Jan 2020 – Present)
    • Korea Robotics Society (Jan 2018 – Present)
    • Korean Society for Power System Engineering (Jan 2017 – Present)
  • Chairman of the National Core Technology Committee (Robot) (Nov 2017 – Present)
    Korean Association for Industrial Technology Security
  • Expert Member (Jan 2021 – Present)
    Presidential Advisory Council on Science & Technology, South Korea
  • Adjunct Professor (Dec 2013 – Aug 2018)
    Department of Mechanical Engineering, POSTECH
  • Director of R&D Division (Apr 2006 – Aug 2018)
    Korea Institute of Robotics and Convergence Technology (KIRO)
  • Post-Doctoral Fellow (Jun 2003 – Feb 2006)
    National Research Laboratory, Dong-A University

Achievements 🏆

  • Patents
    • 28 patents (7 international PCT)
  • Publications
    • 14 papers in international journals (13 SCI)
    • 23 papers in domestic journals (15 SCOPUS)
    • 15 papers in international conferences
    • 60 papers in domestic conferences

Awards and Honors 🌟

  • Director Roles in Leading Engineering Societies
    • Institute of Control, Robotics and Systems
    • Korea Robotics Society
    • Korean Society for Precision and Engineering
  • Presidential Advisory Council Member
    • Significant contributions to national robotics and precision engineering strategies.
  • Chairman, National Core Technology Committee (Robot)
    • Recognized leader in industrial robotics technology and security.

Publication Top Notes

Artificial Neural Network for Glider Detection in a Marine Environment by Improving a CNN Vision Encoder

Development of a Multi-Robot System for Pier Construction

Model-Free RBF Neural Network Intelligent-PID Control Applying Adaptive Robust Term for Quadrotor System

Development of Fishcake Gripping and Classification Automation Process Based on Suction Shape Transformation Gripper

Estimation and Control of a Towed Underwater Vehicle with Active Stationary and Low-Speed Maneuvering Capabilities

Adaptive Robust RBF-NN Nonsingular Terminal Sliding Mode Control Scheme for Application to Snake Robot’s Head for Image Stabilization

Development of Recovery System for Underwater Glider

Prof. Bin Chen | Neural Network Awards | Best Researcher Award

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Prof. Bin Chen | Neural Network Awards | Best Researcher Award 

Prof. Bin Chen, Xi’an Jiaotong University, China

Bin Chen is a distinguished Professor and Deputy Director at the State Key Laboratory of Multiphase Flow in Power Engineering at Xi’an Jiaotong University in China. he has dedicated his academic career to advancing the field of multiphase flow and thermal engineering. Chen obtained his Bachelor’s, Master’s, and Ph.D. degrees in Power Engineering and Thermal Engineering from Xi’an Jiaotong University, further enhancing his expertise with a postdoctoral fellowship from the Japan Society for the Promotion of Science. His research interests encompass fundamental studies of multiphase flow, including interface tracking methods and messless methods, as well as applications in biomedical engineering such as theoretical modeling for laser dermatology and cryogen spray cooling. An advocate for integrating artificial intelligence in sensor technology, he has contributed significantly to his field and serves on various professional committees, including as Director of the subsidiary panels of Multi-phase Flows and Non-Newtonian Flows at the Chinese Society of Theoretical and Applied Mechanics. Chen’s achievements have been recognized with honors such as the National Outstanding Leading Scientist award in 2018 and designation as a New Century Excellent Talent by the Ministry of Education of China in 2007. He also serves on the editorial boards of notable journals in thermofluid science and chemical engineering.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award: Bin Chen

Bin Chen, a distinguished professor at Xi’an Jiaotong University and Deputy Director of the State Key Laboratory of Multiphase Flow in Power Engineering, is a leading expert in the field of multiphase flow and thermal engineering. His extensive educational background, including a Bachelor’s, Master’s, and Ph.D. from Xi’an Jiaotong University, has laid a solid foundation for his impressive research career.

Education

  • Ph.D. in Thermal Engineering
    Xi’an Jiaotong University, 1997 – 2002
  • Master of Cryogenic Engineering
    Xi’an Jiaotong University, 1993 – 1996
  • Bachelor of Power Engineering
    Xi’an Jiaotong University, 1989 – 1993

Work Experience

  • Professor
    State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University
    February 2008 – Present
  • Deputy Director
    State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University
    January 2009 – Present
  • Associate Professor
    State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University
    August 2003 – January 2008
  • Lecturer
    State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University
    May 2000 – July 2003
  • Lecturer
    Chemical Engineering School, Xi’an Jiaotong University
    July 1996 – April 2000
  • Postdoctoral Fellow
    Japan Society for the Promotion of Science
    March 2002 – March 2004

Publication Top Notes

The curvature-adaptive voxel Monte Carlo (CAVMC) method-based photothermal model for customized retinal laser surgery

Study on the mechanism of hydrogen production from bamboo gasification in supercritical water by ReaxFF molecular dynamics simulation

The high-concentration and pumpable pig manure slurry: Preparation, optimization, and evaluation for continuous supercritical water gasification

A novel coaxial air-R134a spray cooling for heat transfer enhancement of laser dermatology

Fe3O4/Au@SiO2 nanocomposites with recyclable and wide spectral photo-thermal conversion for a direct absorption solar collector

Noninvasive Detection of the Skin Structure and Inversed Retrieval of Chromophore Information Based on Diffuse Reflectance Spectroscopy

Assist Prof Dr. Yishu Zhang | Artificial Neuron Awards | Best Researcher Award

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Assist Prof Dr. Yishu Zhang | Artificial Neuron Awards | Best Researcher Award 

Assist Prof Dr. Yishu Zhang, Zhejiang University, China

Yishu Zhang is a 32-year-old researcher currently serving as a Hundred Talents Researcher at the School of Micro-nano Electronics, Zhejiang University. He holds a Ph.D. in Electronic Engineering from the Singapore University of Technology and Design, where he achieved a GPA of 4.4/5 under the supervision of Zhao Rong. Zhang also earned his B.Sc. in Microelectronics from Jilin University, China, with a GPA of 3.61/4. He has over five years of professional experience, including roles as the Director of the Reliability Department at the Zhejiang CMOS Innovation Platform and as an Assistant Professor at Zhejiang University. His research focuses on emerging memristive devices, neuromorphic computing, and the 55nm CMOS manufacturing process. Zhang has supervised several doctoral and master’s students, contributing to advancements in high-reliability RRAM devices and neuromorphic computing based on 2D materials. He has been recognized for his work with various awards and honors, including the Zhejiang Province Thousand Talents Project and a Silver Medal in the 2023 China Postdoctoral Innovation and Entrepreneurship Competition. Zhang has also contributed to the academic community as a guest editor and reviewer for several prestigious journals. His skills encompass micro-nanofabrication, electrical characterization, semiconductor processes, and data processing using Python.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award: Yishu Zhang

Research Expertise & Direction: Yishu Zhang is an exceptional candidate for the Best Researcher Award due to his extensive contributions to emerging technologies such as memristive devices (RRAM, CBRAM, and 2D ferroelectronics), neuromorphic computing, and in-memory computing. His specialization in cutting-edge technologies that directly impact fields like AI hardware and bio-medical applications demonstrates his forward-thinking approach and relevance in today’s research landscape.

Education:

  • Ph.D. in Electronic Engineering (2015.1 – 2019.10):
    Singapore University of Technology and Design (SUTD)
    GPA: 4.4/5
    Supervisor: Zhao Rong
  • B.Sc. in Microelectronics (2010.9 – 2014.7):
    Jilin University, China
    GPA: 3.61/4

Work Experience:

  • Director of Reliability Department (2022.3 – Present):
    Zhejiang CMOS Innovation Platform

    • Supervises 2 doctoral and 2 master’s students working on high-reliability RRAM devices compatible with 55nm standard logic back-end processes.
    • Responsible for R&D of 55nm device reliability and embedded eFlash.
  • Assistant Professor (2021.11 – Present):
    School of Micro-nano Electronics, Zhejiang University

    • Supervises 4 doctoral and 1 master’s student, focusing on neuromorphic computing devices based on 2D materials.
  • Research Fellow (2019.12 – 2021.10):
    National University of Singapore
    Supervisor: Loh Kian Ping

    • Investigated two-dimensional ferroelectric materials for neuromorphic devices and designed biocompatible neuromorphic devices for biomedical applications.
  • Intern, PhD Researcher (2018.10 – 2019.9):
    Institute for Infocomm Research (I2R), A*STAR
    Supervisor: Jiang Wenyu

    • Worked on Spiking Neural Networks (SNN) and their applications in image classification using emerging memory devices.
  • Intern, PhD Researcher (2018.5 – 2018.9):
    Sungkyunkwan University, N Center
    Supervisor: Yang Heejun

    • Explored 2D materials like hBN and Graphene for large-scale memory applications, designing a self-selective Van Der Waals Heterostructure.

Teaching Experience:

  • Artificial Intelligence Hardware Design (Graduate Course), Co-Lecturer at Zhejiang University (2022.10 – 2022.12)
  • Fabrication of Microelectromechanical Systems (Undergraduate Course), Teaching Assistant at SUTD (2017.1 – 2017.5)
  • Engineering in the Physical World and Design (Undergraduate Course), Teaching Assistant at SUTD (2016.1 – 2016.5)

Publication top Notes:

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