Zuheng Ming | Artificial intelligence | Best Researcher Award

Published on by Global Academic Awards

Dr. Zuheng Ming | Artificial intelligence | Best Researcher Award

Associate professor at Sorbonne Paris North University, France

🧑‍🏫 Dr. Zuheng Ming is an Assistant Professor at L2TI, Sorbonne Paris North University, France. He earned his PhD in 2013 from Grenoble Alpes University 🇫🇷, specializing in speech parameter mapping. His expertise spans multimodal learning, computer vision, and deep learning 🤖. Dr. Ming has 30+ publications 📝 in top-tier journals (JCR Q1/Q2) and conferences (ICIP, ICPR, ICDAR). He has supervised doctoral and master’s theses and collaborated internationally with CVC, RIKEN AIP, and Oulu University 🌍. He has led funded research projects on face anti-spoofing and document analysis 📄. Additionally, he serves as a guest editor and reviewer for prestigious journals. ✨

Publication Profile

Google Scholar

🏅 Professional Experience

Dr. Zuheng Ming is an accomplished researcher and educator in computer vision and deep learning 🤖. Since September 2022, he has been serving as an Assistant Professor at L2TI, Sorbonne Paris North University, France 🇫🇷. Prior to this, he was a Lecture-Researcher at L3i, La Rochelle University (2021-2022) 📚. From 2016 to 2021, he worked as a Postdoctoral Fellow and Assistant Lecturer at L3i, La Rochelle University. Earlier, from 2014 to 2015, he pursued a postdoctoral fellowship at Bordeaux University 🏛️, contributing significantly to cutting-edge research in multimodal learning and artificial intelligence. ✨

🎓 Educational Background

Dr. Zuheng Ming holds a PhD in Computer Science from Grenoble Alpes University, France (2013) 🇫🇷, where he specialized in spectral parameters mapping for cued speech using multi-linear and GMM approaches 🔬. He earned his Master’s degree in Pattern Recognition and Artificial Intelligence from Beijing Institute of Technology (2008) 🎭🤖. His academic journey began with a Bachelor’s degree in Electronic and Automatic Systems Engineering from Hunan University, China (2003) ⚡. His strong educational foundation has driven his research contributions in computer vision, deep learning, and multimodal learning 📚✨.

🔬 Research Activities

Dr. Zuheng Ming has been actively involved in research supervision, mentoring 1 PhD thesis, 2 Master’s theses, and 6 internships 🎓📖. He has established six international collaborations with prestigious institutions, including CVC (Spain) 🇪🇸, RIKEN AIP (Japan) 🇯🇵, Oulu University (Finland) 🇫🇮, Northwestern Polytechnical University (China) 🇨🇳, and Xidian University (China) 🇨🇳. His global academic engagement also includes an academic visit to Kyoto University, Japan, in 2015 🌍🏫. Through his extensive research network, Dr. Ming continues to make significant contributions to computer vision, deep learning, and multimodal learning 📊🤖.

🎓 Teaching Experience

Dr. Zuheng Ming has extensive teaching experience in cutting-edge technologies related to artificial intelligence and computer vision 🧠📸. He has taught courses on Deep Learning, Advanced Image Processing, and Intelligent Systems in Computer Vision 🤖🖼️, equipping students with the latest advancements in AI. Additionally, he has imparted knowledge in Database Management and Object-Oriented Programming 💾💻, fostering strong software development skills. His expertise in both theoretical foundations and practical applications makes him a valuable mentor in the field of AI and computer vision, guiding students toward innovative research and industry-ready solutions 🚀📚.

🔍 Research Focus

Dr. Zuheng Ming’s research primarily focuses on computer vision, deep learning, and document security 🧠📸🔏. His contributions span facial recognition, anti-spoofing techniques, and face liveness detection 🤖😃, enhancing biometric security. He has also worked extensively on document image classification and authentication 📄🔍, improving identity verification systems. His expertise in multi-modal learning, pattern recognition, and deep feature fusion enables advancements in AI-driven document forensics and secure authentication 🚀🔐. Collaborating internationally, he applies machine learning and self-attention networks to solve real-world challenges in face recognition, fraud detection, and intelligent systems 🌍🔬.

Publication Top Notes

📸 A survey on anti-spoofing methods for facial recognition with RGB cameras of generic consumer devices – Z Ming, M Visani, MM Luqman, JC Burie | Journal of Imaging | 88 citations | 2020

📄 Visual and textual deep feature fusion for document image classification – S Bakkali, Z Ming, M Coustaty, M Rusiñol | IEEE/CVF Conference on Computer Vision | 63 citations | 2020

🔍 Simple triplet loss based on intra/inter-class metric learning for face verification – Z Ming, J Chazalon, MM Luqman, M Visani, JC Burie | IEEE/CVF International Conference on Computer Vision | 57 citations | 2017

😊 Facial action units intensity estimation by fusion of features with multi-kernel SVM – Z Ming, A Bugeau, JL Rouas, T Shochi | IEEE International Conference on Automatic Face and Gesture Recognition | 54 citations | 2015

🆔 MIDV-2020: A comprehensive benchmark dataset for identity document analysis – BK Bulatovich, EE Vladimirovna, TD Vyacheslavovich, SN Sergeevna, … | Computer Optics | 51 citations | 2022

🙂 Dynamic Multi-Task Learning for Face Recognition with Facial Expression – Z Ming, J Xia, MM Luqman, JC Burie, K Zhao | IEEE/CVF International Conference on Computer Vision Workshop | 40 citations | 2019

📜 VLCDoC: Vision-language contrastive pre-training model for cross-modal document classification – S Bakkali, Z Ming, M Coustaty, M Rusiñol, OR Terrades | Pattern Recognition | 33 citations | 2023

🔐 FaceLiveNet: End-to-end networks combining face verification with interactive facial expression-based liveness detection – Z Ming, J Chazalon, MM Luqman, M Visani, JC Burie | International Conference on Pattern Recognition | 30 citations | 2018

📑 Cross-modal deep networks for document image classification – S Bakkali, Z Ming, M Coustaty, M Rusiñol | IEEE International Conference on Image Processing | 23 citations | 2020

📃 Document liveness challenge dataset (DLC-2021) – DV Polevoy, IV Sigareva, DM Ershova, VV Arlazarov, DP Nikolaev, Z Ming, … | Journal of Imaging | 21 citations | 2022

📹 ViTransPAD: Video Transformer using convolution and self-attention for Face Presentation Attack Detection – Z Ming, Z Yu, M Al-Ghadi, M Visani, M Muzzamil Luqman, JC Burie | IEEE International Conference on Image Processing | 21 citations | 2022

🌲 Multiple sources data fusion via deep forest – J Xia, Z Ming, A Iwasaki | IGARSS IEEE International Geoscience and Remote Sensing Symposium | 15 citations | 2018

🆔 Face detection in camera captured images of identity documents under challenging conditions – S Bakkali, MM Luqman, Z Ming, JC Burie | International Conference on Document Analysis and Recognition Workshops | 11 citations | 2019

📑 EAML: Ensemble self-attention-based mutual learning network for document image classification – S Bakkali, Z Ming, M Coustaty, M Rusiñol | International Journal on Document Analysis and Recognition | 10 citations | 2021

🧠 Synthetic evidential study as augmented collective thought process – Preliminary report – T Nishida, M Abe, T Ookaki, D Lala, S Thovuttikul, H Song, Y Mohammad, … | ACIIDS Asian Conference | 10 citations | 2015

🆔 Identity documents authentication based on forgery detection of guilloche pattern – M Al-Ghadi, Z Ming, P Gomez-Krämer, JC Burie | arXiv preprint | 8 citations | 2022

 

ShengHsun Hsu | AI | Best Researcher Award

Published on by Global Academic Awards

Prof. ShengHsun Hsu | AI | Best Researcher Award

Prof. ShengHsun, Chung Hua University, Taiwan

📚 Prof. Sheng-Hsun Hsu is a full-time professor in the Department of Management at Chu Hua University, Taiwan. He holds a Ph.D. in Business Administration from Taiwan University (2004), a Master’s in Computer Science, and a Bachelor’s in Mathematics from Hsing Hua University.💼 With extensive experience, Prof. Hsu has served as an Assistant Professor, Associate Professor, and Chairman at Chu Hua University. His research focuses on organizational behavior, customer satisfaction indices, brand equity, and psychological capital. His work has been published in top journals like Total Quality Management & Business Excellence and Service Industries Journal (SSCI).🌟 In addition to his academic contributions, Prof. Hsu actively supports curriculum planning, faculty evaluations, and student recruitment efforts. His expertise bridges business management and research, with a commitment to fostering excellence.

Publication Profile

Scopus

📘 Academic Journey

Prof. Sheng-Hsun Hsu boasts an impressive academic background spanning business administration, computer science, and mathematics. He earned his Ph.D. in Business Administration from Taiwan University (1999–2004) 🎓. Before that, he completed his Master’s degree in Computer Science at Hsing Hua University (1993–1995) 💻. His academic journey began with a Bachelor’s degree in Mathematics from the same institution (1990–1993) ➗. This diverse educational foundation reflects his interdisciplinary expertise and commitment to excellence in both theoretical and practical domains of knowledge. 🌟

 

💼 Professional Experience

Prof. Sheng-Hsun Hsu has had an illustrious career at Chu Hua University, contributing as a scholar and leader. He began as an Assistant Professor (1993–1996) 🧑‍🏫, advancing to Associate Professor (1996–1999) 📚. His dedication and expertise led to his promotion as a Professor, a position he has held since May 2014 🌟. Beyond teaching and research, he served as Chairman of the university from August 2013 to August 2014 🏢. Prof. Hsu’s professional journey reflects his commitment to academia and leadership in higher education. 🎓

 

📊 Research Focus

Prof. Sheng-Hsun Hsu’s research primarily revolves around Total Quality Management (TQM) and Business Excellence, particularly focusing on improving organizational performance and strategic alignment in various industries. His studies explore the integration of information technology (IT) and business strategies, emphasizing IT competence and the roles of CIOs in business success. Additionally, Prof. Hsu has contributed to the development of models for customer satisfaction, alumni satisfaction, and psychological capital in organizational contexts. His work bridges behavioral economics, higher education, and business management, aiming to enhance both quality management and consumer experience. 🔍📈

 

Publication Top Notes  

  • A GPT-Aided literature review process for total quality management and business excellence (2024) – Cited by 1
  • The effects of IT chargeback on strategic alignment and performance: the contingent roles of business executives’ IT competence and CIOs’ business competence (2023) – Cited by 3
  • Topic analysis of studies on total quality management and business excellence: an update on research from 2010 to 2019 (2022) – Cited by 11
  • Constructing a consumption model of fine dining from the perspective of behavioral economics (2018) – Cited by 8
  • Developing a decomposed alumni satisfaction model for higher education institutions (2016) – Cited by 23
  • Building business excellence through psychological capital (2014) – Cited by 15
  • Developing a decomposed customer satisfaction index: An example of the boutique motel industry (2013) – Cited by 4
  • Constructing an index for brand equity: A hospital example (2011) – Cited by 31
  • A dyadic perspective on knowledge exchange (2010) – Cited by 6
  • A two-stage architecture for stock price forecasting by integrating self-organizing map and support vector regression (2009) – Cited by 108