Dr. Zhiwei Zhang | Deep Learning Awards | Best Researcher Award

Dr. Zhiwei Zhang | Deep Learning Awards | Best Researcher AwardΒ 

Dr. Zhiwei Zhang, AVIC Manufacturing Technology Institute, China

Zhiwei Zhang, is a research engineer specializing in aviation manufacturing technology in China. He holds a bachelor’s and master’s degree in Automation from Shenyang Ligong University and earned his Ph.D. in Instrument Science and Technology from Yanshan University. His research focuses on digital radiographic and industrial CT nondestructive testing, computer vision, and ensemble learning algorithms for additive manufacturing. He has published seven SCI-indexed research papers and holds two authorized patents. Zhiwei Zhang also serves as a reviewer for the Journal of Computational Methods in Sciences and Engineering, reflecting his active contribution to the academic and industrial research community.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award: Zhiwei Zhang

Zhiwei Zhang, a highly skilled research engineer in aviation manufacturing technology, has demonstrated outstanding contributions in the fields of nondestructive testing, computer vision, and ensemble learning for additive manufacturing. His innovative research integrates cutting-edge technologies like digital radiography, industrial CT, and machine learning, addressing critical challenges in the aerospace industry.

πŸŽ“ Education

  • 🏫 Bachelor’s Degree in Automation – Shenyang Ligong University

  • πŸŽ“ Master’s Degree in Automation – Shenyang Ligong University

  • πŸ§ͺ Ph.D. in Instrument Science and Technology – Yanshan University

πŸ’Ό Work Experience

  • πŸ‘¨β€πŸ”§ Research Engineer – Specializing in aviation manufacturing technology in China

  • πŸ”¬ Focus areas include:

    • Digital radiographic and industrial CT nondestructive testing

    • Computer vision

    • Ensemble learning algorithms for additive manufacturing

πŸ† Achievements

  • πŸ“„ Published 7 SCI-indexed research papers in high-impact journals

  • 🧾 Granted 2 authorized patents

  • πŸ§‘β€βš–οΈ Reviewer for the Journal of Computational Methods in Sciences and Engineering

πŸŽ–οΈ Awards & Honors

  • πŸ… Recognized for contributions in nondestructive testing and AI applications in manufacturing
    (Note: Specific award titles not mentioned; can be added if provided.)

PublicationΒ Top Notes:

A Hybrid Framework for Metal Artifact Suppression in CT Imaging of Metal Lattice Structures via Radon Transform and Attention-Based Super-Resolution Reconstruction

Complex Defects Detection of 3-D-Printed Lattice Structures: Accuracy and Scale Improvement in YOLO V7

A Prediction Model for Maximum Stress of Additive Manufacturing Lattice Structures Based on Voting-Cascading

Deep convolution IT2 fuzzy system with adaptive variable selection method for ultra-short-term wind speed prediction

An improved meta heuristic IT2 fuzzy model for nondestructive failure evaluation of metal additive manufacturing lattice structure

An improved stacking ensemble learning model for predicting the effect of lattice structure defects on yield stress

Data-driven XGBoost model for maximum stress prediction of additive manufactured lattice structures

Adaptive Defect Detection for 3-D Printed Lattice Structures Based on Improved Faster R-CNN

A Hybrid Model Based on Jensen’s Inequality Theory for 3D Printed Lattice Structures Maximum Stress Prediction

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

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

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.

πŸŽ“ Education

  • Ph.D. in Electrical Engineering
    National Cheng Kung University, Taiwan πŸ‡ΉπŸ‡Ό
    Completed in 1996

πŸ’Ό Work Experience

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

  • πŸ›οΈ Founding Director, Department of Electrical Engineering, National Chiayi University
    2007 – 2011

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

πŸ§ͺ Research Interests

  • πŸ” Computer Vision

  • 🎯 Semantic Object Detection

  • 🎞️ Video/Audio Coding

  • πŸ€– AI-based Pattern Recognition

  • πŸ₯½ Stereoscopic 3D

  • 🧠 Deep Learning Neural Networks

πŸ… 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.

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

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

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

PublicationΒ 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

Assoc. Prof. Dr. Waleed Mahmoud Elsayed | Machine learning Awards | Best Researcher Award

Assoc. Prof. Dr. Waleed Mahmoud Elsayed | Machine learning Awards | Best Researcher AwardΒ 

Assoc. Prof. Dr. Waleed Mahmoud Elsayed, Beni-suef university, Saudi Arabia

Dr. Waleed Mahmoud Ead is an accomplished Assistant Professor in the Faculty of Computing and Information at Al-Baha University, Saudi Arabia, with over 15 years of experience in digital business transformation, data science, and applied research. He holds a Ph.D. in Computers and Informatics from Menoufia University, Egypt, where he focused on privacy-preserving techniques in social networks. Throughout his career, Dr. Ead has developed expertise in business intelligence, data mining, machine learning, cloud computing, and big data analytics, and he is SAS-certified in multiple disciplines, including machine learning and visual analytics. His research interests span social network analysis, distributed databases, precision medicine, and cybersecurity. He has served in various academic roles across prominent Egyptian institutions and has co-supervised doctoral and master’s research in genetics, AI, and privacy in healthcare. A dedicated peer reviewer for renowned journals such as Springer Nature and Inderscience, Dr. Ead is also an active contributor to academic conferences and international workshops. Beyond academia, he is a technology enabler, STEM judge, and entrepreneur, with projects focused on sustainable agriculture and digital innovation.

Professional Profile:

GOOGLE SCHOLAR

ORCID

SCOPUS

βœ… Summary of Suitability for Best Researcher Award: Dr. Waleed Mahmoud Ead

Dr. Waleed Mahmoud Ead is highly suitable for the Best Researcher Award, given his exceptional combination of research depth, academic leadership, interdisciplinary engagement, and societal impact. His qualifications are supported by the following key strengths

πŸŽ“ Education

  • πŸ₯‡β€―2004: B.Sc. (Honor) in Information and Technology Systems – Zagazig University, Egypt

  • πŸ“šβ€―2012: M.Sc. in Computers and Informatics – Menoufia University, Egypt
    β€ƒβ€ƒπŸ“˜ Thesis: “Developing an Intelligent Technique in Web Mining”

  • πŸŽ“β€―2018: Ph.D. in Computers and Informatics – Menoufia University, Egypt
    β€ƒβ€ƒπŸ“— Thesis: “Privacy Preserving in Social Networks”

πŸ‘¨β€πŸ« Academic Work Experience

  • πŸ‡ΈπŸ‡¦β€―2024–Present: Assistant Professor, Faculty of Computing and Information – Al-Baha University, Saudi Arabia

  • πŸ‡ͺπŸ‡¬β€―2022–2023: Assistant Professor, CSIT – Egypt-Japan University of Science and Technology

  • πŸ‡ͺπŸ‡¬β€―2018–2022: Assistant Professor, Faculty of Computers & AI – Beni-Suef University

  • πŸ‡ͺπŸ‡¬β€―2015–2018: Lecturer Associate, Faculty of Information Technology – MUST University

  • πŸ‡ͺπŸ‡¬β€―2014: Lecturer Associate, Faculty of Computers & Information – Beni-Suef University

  • πŸ‡ͺπŸ‡¬β€―2012: Lecturer Associate, CSC – October 6 University

  • πŸ‡ͺπŸ‡¬β€―2006–2012: Teaching Assistant, CSC – October 6 University

πŸ† Achievements & Honors

  • 🧠 SAS Certified: Machine Learning, Visual Analytics, Business Planning

  • πŸ’‘ Developed systems for international conferences

  • 🌍 Peer Reviewer for top journals & publishers (Inderscience, Springer, EAI, etc.)

  • 🧬 Co-supervisor for Ph.D. and Master’s students in AI, bioinformatics, and precision medicine

  • πŸ₯‡ Honor degree in B.Sc.

  • πŸ‘©β€βš– STEM Judge: INTEL ISEF & Graduation Projects

  • πŸ’Ό Speaker and participant in events by DAAD, UNESCO, Microsoft, SAS, Oracle

  • 🌱 Founder of IGreen (Intelligent Adaptive Environmental Farm)

  • πŸš€ Participated in entrepreneurship programs (Start Egypt, Flat6Labs)

  • 🧭 Bridging analytics and IT knowledge for social development

PublicationΒ Top Notes:

An Optimized Hierarchal Cluster Formation Approach for Management of Smart Cities

ODCS: On-Demand Hierarchical Consistent Synchronization Approach for the IoT

A General Cyber Hygiene Approach for Financial Analytical Environment

Feedforward Deep Learning Optimizer-based RNA-Seq Women’s cancers Detection with a hybrid Classification Models for Biomarker Discovery

Semantic Sentiment Classification for COVID-19 Tweets Using Universal Sentence Encoder

Automated Prediction of Employee Attrition Using Ensemble Model Based on Machine Learning Algorithms