Prof. Din-Yuen Chan | Deep Learning | Best Scholar Award

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Prof. Din-Yuen Chan | Deep Learning | Best Scholar Award 

Prof. Din-Yuen Chan, National Chiayi University, Taiwan

Din-Yuen Chan is a prominent scholar in electrical engineering with extensive experience in visual signal processing and computer vision. He earned his Ph.D. in Electrical Engineering from National Cheng Kung University, Taiwan, in 1996. A member of the Visual Signal Processing and Communication Technical Committee (VSPC TC) since 2010, he served as the founding director of the Department of Electrical Engineering (2007–2011) and as Dean of the College of Science and Engineering at National Chiayi University (2017–2020). His research spans semantic object detection, video/audio coding, stereoscopic 3D, AI-based pattern recognition, and deep learning neural networks. In the past five years, he has published multiple SCI-indexed journal papers on topics such as stereo matching, instance segmentation, speaker diarization, depth estimation, and autonomous robotics. As a frequent corresponding author, he continues to lead innovations in applied AI and multimedia processing.

Professional Profile:

SCOPUS

Summary of Suitability for the Best Scholar Award

Dr. Din-Yuen Chan has maintained an outstanding academic career for over two decades, contributing significantly to the fields of electrical engineering and computer vision. His long-standing commitment to advancing knowledge is reflected in his leadership roles and consistent research output in areas such as semantic object detection, AI-based pattern recognition, video/audio coding, and stereoscopic 3D.

🎓 Education

  • Ph.D. in Electrical Engineering
    National Cheng Kung University, Taiwan 🇹🇼
    Completed in 1996

💼 Work Experience

  • 🧠 Member, Visual Signal Processing and Communication Technical Committee (VSPC TC)
    Since 2010

  • 🏛️ Founding Director, Department of Electrical Engineering, National Chiayi University
    2007 – 2011

  • 🎓 Dean, College of Science and Engineering, National Chiayi University
    2017 – 2020

🧪 Research Interests

  • 🔍 Computer Vision

  • 🎯 Semantic Object Detection

  • 🎞️ Video/Audio Coding

  • 🤖 AI-based Pattern Recognition

  • 🥽 Stereoscopic 3D

  • 🧠 Deep Learning Neural Networks

🏅 Achievements & Honors

  • ✍️ Published multiple SCI-indexed journal papers in high-impact venues, including:

    • EURASIP Journal on Image and Video Processing

    • IET Computer Vision

    • Multimedia Tools and Applications

    • Applied Sciences

  • ⭐ First or corresponding author in many significant papers on stereo matching, depth estimation, 3D object placement, and speaker diarization.

  • 🤖 Developed a low-cost autonomous outdoor robot with end-to-end deep learning navigation.

  • 🧏 Invented a new speaker-diarization technology using spectral-LSTM.

  • 🎓 Recognized leader in academia for establishing and leading research and administrative departments.

Publication Top Notes:

A new speaker-diarization technology with denoising spectral-LSTM for online automatic multi-dialogue recording

Natural-Prosodic Cross-Lingual Personalized TTS

New Efficient Depth Estimation and Real-Time Object 3D Recognition Models for Humanoid Robotic Environment Understanding

Rational 3D object placement based on deep learning based plane detection

INTEGRATED LIGHT-RESNET AND POOLFORMER NETWORKS FOR SHAPE-PRESERVING LANE DETECTION

Dr. Minh-Khang Le | Artificial Intelligence Awards | Best Researcher Award

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Dr. Minh-Khang Le | Artificial Intelligence Awards | Best Researcher Award 

Dr. Minh-Khang Le, Cedars-Sinai Medical Center, United States

Minh-Khang Le, M.D., Ph.D., is a Postdoctoral Research Scientist in the Department of Pathology and Computational Biomedicine at Cedars-Sinai Medical Center in Los Angeles, California. He obtained his Doctor of Medicine degree from the University of Medicine and Pharmacy at Ho Chi Minh City, graduating in the top 10% of his class, and completed his Ph.D. in Pathology at the University of Yamanashi in Japan. His research focuses on integrating histopathology, molecular profiles, and clinicopathological features to characterize human cancers, particularly lymphoid and hematopoietic neoplasms. Dr. Le has contributed to several projects involving histopathology, molecular analyses, and the development of clinicopathological machine-learning models. As a strong advocate for the transformative potential of artificial intelligence in pathology, he aims to enhance the understanding and treatment of cancer. In addition to his postdoctoral position, he has held research roles at various institutions, including the University of Iowa Hospitals and Clinics and the University of Oklahoma Health Sciences Center. Dr. Le’s work has led to impactful advancements in digital pathology and cancer research.

Professional Profile:

SCOPUS

Researcher Suitability Summary for Best Researcher Award: 

Minh-Khang Le is an exemplary candidate for the Best Researcher Award, showcasing a profound commitment to advancing the field of digital pathology and computational biomedicine. His research is particularly focused on integrating histopathological and molecular profiles to enhance the understanding and characterization of human cancers, especially lymphoid and hematopoietic neoplasms. This multidisciplinary approach not only reflects his extensive knowledge but also his dedication to translating complex data into meaningful clinical insights.

Education 🎓

  • Postdoctoral Research Scientist
    Cedars-Sinai Medical Center, Department of Computational Biomedicine and Pathology
    July 2024 – Present
    8700 Beverly Blvd, Los Angeles, CA, USA
  • Ph.D. Student
    University of Yamanashi, Department of Pathology
    April 2020 – March 2024
    GPA: 3.5/4.0
    1110 Shimokato, Chuo, Yamanashi, Japan
  • Doctor of Medicine
    University of Medicine and Pharmacy at Ho Chi Minh City
    October 2013 – September 2019
    Degree Classification: Good (Top 10% of the Course)
    Ho Chi Minh City, Vietnam

Work Experience 💼

  • Postdoctoral Research Scientist
    Cedars-Sinai Medical Center, Department of Computational Biomedicine and Pathology
    July 2024 – Present
  • Part-time Researcher
    New Energy and Industrial Technology Development Organization (NEDO)
    April 2022 – Present
  • Part-time Researcher
    Department of Pathology, The University of Iowa Hospitals and Clinics, Iowa, USA
    April 2022 – Present
  • Research Assistant
    Department of Pathology, University of Yamanashi
    April 2020 – Present
  • Teaching Assistant
    Department of Pathology, University of Yamanashi
    April 2020 – Present
  • Part-time Researcher
    Department of Neurosurgery, The University of Oklahoma Health Sciences Center, Oklahoma, USA
    April 2021 – March 2022

Achievements, Awards, and Honors 🏆

  • Top 10% of the Course in Doctor of Medicine program at the University of Medicine and Pharmacy at Ho Chi Minh City
  • GPA of 3.5/4.0 in Ph.D. studies at the University of Yamanashi

Publication Top Notes:

Clinical implication of PRAME immunohistochemistry in differentiating melanoma in situ and dysplastic nevus in non-acral nevus-associated melanoma in situ: An institutional experience and meta-analysis

A Novel Artificial Intelligence-Based Parameterization Approach of the Stromal Landscape in Merkel Cell Carcinoma: A Multi-Institutional Study

Comprehensive analysis of distinct circadian clock subtypes of adult diffuse glioma and their associations with clinicopathological, genetic, and epigenetic profiles

CXCL5 expression is associated with active signals of macrophages in the microenvironment of papillary thyroid carcinoma

Severe asthmatic airways have distinct circadian clock gene expression pattern associated with WNT signaling

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