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

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

 

 

Dr. Jiangning Zhang | Computer Vision | Best Researcher Award

Dr. Jiangning Zhang | Computer Vision | Best Researcher Award

Dr. Jiangning Zhang, Zhejiang University, China

Dr. Jiangning Zhang, a Principal Researcher at YouTu Lab, Tencent in Shanghai, holds a Ph.D. in Control Science and Engineering and an M.D. from Zhejiang University, as well as a B.S. in Electronic Information from Wuhan University. He leads the Industry Perception and AIGC teams, focusing on neural architecture design, particularly transformer-based and lightweight vision models. Dr. Zhang’s research spans multi-modal AIGC, including image and video generation, human-centric editing, and virtual digital human technologies, and extends to 3D scene segmentation with foundation models for visual anomaly classification. His work drives advancements in cutting-edge technologies and applications in artificial intelligence and computer vision.

Professional Profile:

Google Scholar

Suitability for the Award

Dr. Jiangning Zhang is highly suitable for the Best Researcher Award for the following reasons:

  1. Innovative Research Contributions:
    • Dr. Zhang’s work in neural architecture design and multi-modal generative models has advanced the field of computer vision and AI. His research on transformer-based architectures and lightweight vision models contributes to the efficiency and effectiveness of AI systems.
    • His involvement in developing multi-modal GANs, VAEs, and diffusion models for various applications, including 2D/3D digital human generation and motion generation, demonstrates significant innovation and impact in the field.
  2. High-Impact Publications:
    • Dr. Zhang has published influential papers in top-tier conferences such as ICCV and TIP, showcasing his contributions to cutting-edge research. His work on efficient attention-based models and anomaly detection reflects his expertise and impact on the academic community.
  3. Leadership and Influence:
    • As a Principal Researcher at Tencent’s YouTu Lab, Dr. Zhang leads teams working on industry perception and advanced AI-generated content, indicating his role in shaping future technologies and influencing both academic and industrial research.
  4. Relevance and Application:
    • Dr. Zhang’s research addresses practical and emerging challenges in AI, such as image/video generation, digital human reconstruction, and scene segmentation. His work has practical applications in various industries, enhancing its relevance and impact.

Educational Background 

Dr. Zhang earned his Ph.D. in Control Science and Engineering from Zhejiang University, Hangzhou, China, under the guidance of Prof. Yong Liu. He pursued his M.D. at the same institution and obtained his B.S. in Electronic Information from Wuhan University.

Current Position

Dr. Jiangning Zhang is a Principal Researcher leading the Industry Perception and AIGC teams at YouTu Lab, Tencent, Shanghai.

Research Interests 

  • Neural Architecture Design: Specializing in transformer-based architectures and lightweight vision models.
  • Multi-modal AIGC Research: Investigating image and video generation, human-centric editing, and 2D/3D virtual digital human technologies, including reconstruction and animation.
  • 3D Scene Segmentation: Utilizing foundation models for visual anomaly classification and segmentation.

Publication Top Notes:

  • Title: Omni-Frequency Channel-Selection Representations for Unsupervised Anomaly Detection
    • Year: 2023
    • Cited by: 96
  • Title: Rethinking Mobile Block for Efficient Attention-Based Models
    • Year: 2023
    • Cited by: 78
  • Title: Towards Open Vocabulary Learning: A Survey
    • Year: 2024
    • Cited by: 71
  • Title: Multimodal Industrial Anomaly Detection via Hybrid Fusion
    • Year: 2023
    • Cited by: 64
  • Title: Region-Aware Face Swapping
    • Year: 2022
    • Cited by: 56