Jingcheng Ke | Diffusion Models | Excellence in Research

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Jingcheng Ke | Diffusion Models | Excellence in Research

Dr. Jingcheng Ke, Osaka university, Japan.

Jingcheng Ke, Ph.D. 🎓, is a researcher at the Institute for Datability Science, Osaka University 🇯🇵. With a Ph.D. from National Tsing Hua University (NTHU) 🇹🇼, his research focuses on vision-language matching and diffusion models for image and video analysis 🖼️📹. He has worked as an AI researcher at vivo AI Lab and as an exchange student at Shenzhen Key Laboratory of Visual Object Detection and Recognition. Proficient in multiple languages 🌏 and programming 🖥️, Dr. Ke’s work bridges cutting-edge AI technologies and innovative computational methods.

Publication Profile

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Education & Experience:

Education

  • 🎓 Ph.D. in Communications Engineering (2019–2024)
    • National Tsing Hua University, Taiwan
    • Thesis: Referring Expression Comprehension in a Graph-based Perspective and Its Generalizations
  • 🎓 M.Sc. in Computer Application (2015–2018)
    • Shaanxi Normal University, China
    • Thesis: Face recognition based on virtual faces and sparse representations
  • 🎓 B.Sc. in Network Engineering (2010–2014)
    • Southwest Minzu University, China
    • Thesis: An improved encryption algorithm based on Data Encryption Standard

Experience

  • 🧑‍🔬 Researcher (2024–Present)
    • Institute for Datability Science, Osaka University
  • 🤖 AI Researcher (2018–2019)
    • vivo AI Lab
  • 🔬 Exchange Student (2016–2018)
    • Shenzhen Key Laboratory of Visual Object Detection and Recognition

Suitability for the Award

Dr. Jingcheng Ke is an exceptional candidate for the Excellence in Research Award, demonstrating a profound impact on AI and computational sciences. His Ph.D. research at National Tsing Hua University, focused on graph-based referring expression comprehension, has advanced the fields of vision-language matching and diffusion models for image and video analysis. With professional experience at Osaka University and vivo AI Lab, Dr. Ke has effectively bridged theoretical innovation and practical application. His technical expertise in Python, PyTorch, and C++, coupled with knowledge in matrix theory, stochastic processes, and topology, underscores his interdisciplinary strength. Dr. Ke’s groundbreaking contributions position him as a leader in AI research.

Professional Development

Dr. Jingcheng Ke’s professional journey spans academia and industry, specializing in artificial intelligence 🤖 and computer vision 👁️. His Ph.D. research at NTHU explored graph-based perspectives for referring expression comprehension, advancing the intersection of vision and language technologies 🌐. With hands-on experience in AI innovation at vivo AI Lab and collaboration with top-tier research labs, he has honed his expertise in diffusion models and image/video analysis 📊. Proficient in coding languages like Python and PyTorch 🖥️, he leverages advanced mathematical concepts like matrix theory and stochastic processes to push AI boundaries 🚀.

Research Focus

Dr. Ke’s research is centered on the intersection of vision and language 🤝, with a keen focus on diffusion models for image and video analysis 🎥. His work addresses challenges in vision-language matching, exploring graph-based approaches to enhance comprehension and generalization capabilities 🔍. Passionate about advancing AI technologies, he delves into areas like sparse representation and encryption algorithms 🔒. By integrating robust coding skills in Python and PyTorch with theoretical foundations, his research contributes to groundbreaking advancements in artificial intelligence and computational methodologies 🚀.

Awards and Honors

  • 🏆 Best Paper Award – Recognized for excellence in vision-language research.
  • 🥇 Graduate Fellowship – National Tsing Hua University, Taiwan.
  • 🥉 Outstanding Thesis Award – Shaanxi Normal University, China.
  • 🎖️ Research Excellence Recognition – vivo AI Lab, 2019.
  • 🌟 Academic Merit Scholarship – Southwest Minzu University, China.

Publication Highlights

  • 📄 An improvement to linear regression classification for face recognition – 26 citations, published in International Journal of Machine Learning and Cybernetics, 2019.
  • 📘 Referring Expression Comprehension via Enhanced Cross-modal Graph Attention Networks – 12 citations, published in ACM TOMM, 2022.
  • 🖼️ Face recognition based on symmetrical virtual image and original training image – 12 citations, published in Journal of Modern Optics, 2018.
  • 📊 Sample partition and grouped sparse representation – 8 citations, published in Journal of Modern Optics, 2017.
  • 🤖 A novel grouped sparse representation for face recognition – 7 citations, published in Multimedia Tools and Applications, 2019.

Prof Dr. Bernd Markert | Computational Intelligence | Best Researcher Award

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Prof Dr. Bernd Markert | Computational Intelligence | Best Researcher Award

Prof Dr. Bernd Markert, RWTH Aachen University, Germany

Prof. Dr. Bernd Markert is a distinguished academic leader and Full Professor at RWTH Aachen University, where he directs the Institute of General Mechanics. Renowned for his research in mechanics, structural health monitoring, and biomechanics, Prof. Markert has authored over 400 publications with an h-Index of 43 and has garnered international recognition, including an honorary doctorate from PSACEA and a Distinguished Visiting Professorship at Tsinghua University. His academic excellence is complemented by leadership roles such as Vice Dean at RWTH Aachen and significant contributions to international collaborations and digital teaching innovations.

Professional Profile:

Google Scholar

Suitability for the Award

Prof. Dr. Bernd Markert is exceptionally qualified for the Best Researcher Award for the following reasons:

  1. Outstanding Academic Contributions:
    • Prof. Markert has made significant advancements in various areas of mechanics, including damage and fracture mechanics, multiscale and multiphysics approaches, and biomechanics. His research on coupled problems, nano-materials, and structural health monitoring highlights his innovative approach to complex engineering problems.
  2. High Impact and Recognition:
    • With an impressive h-index of 43 and over 6,900 citations, his work has had a profound impact on the field. His publications in prestigious journals and his contributions to digital twins and artificial intelligence further emphasize his leading role in engineering research.
  3. Leadership and Influence:
    • His leadership roles, including Vice Dean, Scientific Director, and Distinguished Visiting Professor, showcase his ability to drive academic and research excellence. His involvement in international collaborations and his influence in shaping educational programs reflect his significant impact on the academic community.
  4. Awards and Fellowships:
    • Prof. Markert’s recognition through various prestigious awards and fellowships underscores his exceptional contributions to the field. His honorary doctorate and international accolades highlight his global influence and the high regard in which he is held.

Educational Background 📚

He holds a Habilitation in Mechanics from 2010 and a Ph.D. (Dr.-Ing.) with distinction (2005), following a Diploma degree in Civil Engineering from the University of Stuttgart (1998).

Distinguished Academic Leader 🎓

Prof. Dr. Bernd Markert is a distinguished academic leader and Full Professor at RWTH Aachen University, where he also serves as the Institute Director. He has made significant contributions to the fields of mechanics, structural health monitoring, and biomechanics.

Research Excellence 🔬

With an h-Index of 43 and an i10-Index of 163, Prof. Markert boasts over 400 publications and 6973 citations as of August 2024. His research focuses on coupled problems, multifield theories, damage and fracture mechanics, and multiscale approaches, contributing to advancements in nano-materials and predictive maintenance.

Leadership and Administration 🏛️

Prof. Markert has held numerous leadership roles, including Vice Dean in Charge of Studies at the Faculty of Mechanical Engineering (2016-2019) and Chairman of the proRWTH support association at RWTH Aachen University. He has also been a Rector’s Delegate for Alumni and Scientific Director of International Master Programmes.

International Recognition 🌏

He is a Distinguished Visiting Professor at Tsinghua University, Beijing, China (since February 2024) and has been recognized with an honorary doctorate from PSACEA (2022) and a Royal Token from Princess Sirindhorn for his contributions to the Thai-German Graduate School of Engineering (2015).

Awards and Fellowships 🏆

Prof. Markert’s accolades include a fellowship for innovations in digital teaching from the Stifterverband (2016) and being a finalist for the Europe-wide Best PhD Thesis Award by ECCOMAS (2005).

Publication Top Notes:

  • Title: A Systematic Review of Gait Analysis Methods Based on Inertial Sensors and Adaptive Algorithms
    • Year: 2017
    • Cited by: 338
  • Title: Effects of Porosity on the Mechanical Properties of Additively Manufactured Components: A Critical Review
    • Year: 2020
    • Cited by: 253
  • Title: A Phase-Field Modeling Approach of Hydraulic Fracture in Saturated Porous Media
    • Year: 2017
    • Cited by: 204
  • Title: Comparison of Monolithic and Splitting Solution Schemes for Dynamic Porous Media Problems
    • Year: 2010
    • Cited by: 162
  • Title: A Linear Viscoelastic Biphasic Model for Soft Tissues Based on the Theory of Porous Media
    • Year: 2001
    • Cited by: 162