Chengyuan Zhang | Computer Science | Best Research Article Award

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Chengyuan Zhang | Computer Science | Best Research Article Award

Chengyuan Zhang, Hunan University, China

Dr. Chengyuan Zhang, born in October 1985 in Suining County, Hunan, is an Associate Professor and Ph.D. Supervisor at the College of Computer Science and Electronic Engineering, Hunan University. He also serves as a Guest Professor at the College of Information and Intelligence, Hunan Agricultural University. Dr. Zhang earned his Ph.D. in Computer Science from the University of New South Wales, where he also completed his master’s studies under the guidance of Professors Xuemin Lin and Wenjie Zhang. His professional experience includes academic roles in both China and Australia, notably as a postdoctoral researcher. With nearly 40 SCI-indexed publications and over 1,300 citations, he is widely recognized in the domains of multimedia computing, spatio-temporal data analysis, and machine learning. Dr. Zhang is a frequent reviewer for top-tier journals and has contributed to numerous national and provincial-level research projects. He holds editorial and committee roles in several internationally recognized journals and conferences.

Publication Profile

scopus

Education

Dr. Chengyuan Zhang began his academic journey in Software Engineering at Sun Yat-sen University, earning his bachelor’s degree in 2008. He then advanced to the University of New South Wales (UNSW), one of Australia’s leading research institutions, where he obtained a master’s degree in Computer Science in 2011. His academic excellence led him to pursue a Ph.D. in Computer Science at UNSW from July 2011 to December 2015. During his doctoral studies, he worked under the mentorship of esteemed professors Xuemin Lin and Wenjie Zhang. His research during this period laid the groundwork for his future academic contributions in data mining, multimedia computing, and spatio-temporal data processing. The international education experience at UNSW not only honed his technical expertise but also equipped him with a global research perspective and collaborative mindset, helping him transition smoothly into high-impact academic roles upon returning to China.

Experience

Dr. Chengyuan Zhang currently holds the position of Associate Professor and Deputy Director in the Department of Computer Science at Hunan University. He joined the university in December 2019 and assumed his deputy directorship in November 2023. Previously, he served as a Lecturer at the College of Information Science and Engineering at Central South University from 2016 to 2019. His international experience includes a one-year postdoctoral research position at the University of New South Wales from 2015 to 2016, where he continued his research on large-scale data processing. Over the years, Dr. Zhang has participated in and led various nationally funded projects, especially in multimedia, graph data analysis, and AI-driven spatio-temporal applications. He also contributes significantly to the academic community as an editor and reviewer for top journals such as IEEE TKDE, ACM TOIS, and IEEE TNNLS. His career reflects a balanced combination of research innovation, teaching, and academic leadership.

Awards and Honors

Dr. Chengyuan Zhang has received several recognitions for his scholarly contributions, including the Outstanding Reviewer Award from Pattern Recognition Letters, which highlights his dedication to academic quality and peer review. He serves as Academic Editor for Advances in Multimedia and as a Guest Editor for prestigious journals such as Multimedia Tools and Applications and Mathematics. Dr. Zhang has also contributed as a Reviewer for top-tier academic journals including IEEE TPAMI, IEEE TNNLS, IEEE TKDE, ACM TOIS, and ACM TOMM. In addition, he has served as a Program Committee Member for leading international conferences such as ACM Multimedia and IJCAI-PRICAI. These roles are a testament to his academic credibility and recognition within the global research community. His grant-winning research and participation in national foundations reflect his active role in shaping future advancements in multimedia, data mining, and artificial intelligence.

Research Focus

Dr. Chengyuan Zhang’s research centers on multimedia computing, spatio-temporal multi-modal data analysis, image processing, graph data analysis, and machine learning. His work aims to address complex challenges related to information retrieval, representation learning, and knowledge discovery from large-scale, heterogeneous datasets. Specifically, he focuses on designing efficient algorithms for spatio-temporal queries, cross-modal hashing retrieval, and dynamic image enhancement techniques. His research often integrates deep learning, graph theory, and semantic correlation mining, contributing to both theoretical advancements and real-world applications—especially in areas like intelligent agriculture, social recommendation systems, and wireless sensor networks. With support from multiple National Natural Science Foundation of China (NSFC) grants and Hunan provincial research programs, his work is recognized as both innovative and impactful. He has published nearly 40 papers in top journals and conferences such as IEEE TKDE, ACM TOIS, and ACM TOMM, earning over 1,300 citations and an H-index of 18.

Publication Top Notes

  1. 📖 MvHAAN: Multi-view hierarchical attention adversarial network for person re-identification – World Wide Web, 2024

  2. 📖 Bi-Direction Label-Guided Semantic Enhancement for Cross-Modal Hashing – IEEE TCSVT, 2024

  3. 🖼 Using CNN with Multi-Level Information Fusion for Image Denoising – Electronics, 2023

  4. 🖼 Adaptive Dynamic Shuffle Convolutional Parallel Network for Image Super-Resolution – Electronics, 2024

  5. 📷 Efficient Feature Redundancy Reduction for Image Denoising – World Wide Web, 2024

  6. 🔍 Efficient Maximal Biclique Enumeration on Large Uncertain Bipartite Graphs – IEEE TKDE, 2023

  7. 🔍 Efficient Maximum Edge-Weighted Biclique Search on Large Bipartite Graphs – IEEE TKDE, 2022

  8. 🤖 Robust Sparse Weighted Classification for Crowdsourcing – IEEE TKDE, 2022

  9. 🌐 Multi-Graph Heterogeneous Interaction Fusion for Social Recommendation – ACM TOIS, 2022

  10. 🌐 Scaling High-Quality Pairwise Link-Based Similarity Retrieval on Billion-Edge Graphs – ACM TOIS, 2022

 

Ahmad Yahya Dawod | Computer Science | Academic Excellence Citation Award

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Assist. Prof. Dr. Ahmad Yahya Dawod | Computer Science | Academic Excellence Citation Award

Assist. Prof. Dr. Ahmad Yahya Dawod, Chiang mai University, Thailand

Assist. Prof. Dr. Ahmad Yahya Dawod is a lecturer at the International College of Digital Innovation (ICDI) at Chiang Mai University (CMU), Thailand. He holds a bachelor’s degree in Computer Science from Al-Mustansiriya University, Iraq (2006), a master’s degree in Computing and Informatics from Multimedia University (MMU), Malaysia (2012), and a Ph.D. from the Faculty of Information Science and Technology at the National University of Malaysia (UKM) (2018). His research focuses on Artificial Intelligence, Machine Learning, Pattern Recognition, Computer Vision, Medical Image Analysis, Image Processing, Robotics, Sign Language Recognition, and Natural

Education

Assistant Professor Dr. Ahmad Yahya Dawod has a rich academic background with a strong focus on computer science and technology. He earned his Doctor of Philosophy (Ph.D.) degree from the National University of Malaysia (UKM), Faculty of Information Science and Technology, in May 2018. His doctoral research, titled “Hand Gesture Recognition Based on Isolated and Continuous Sign Language,” was supervised by Assoc. Prof. Dr. Md. Jan Nordin. Prior to this, he completed his Master’s degree (M.Sc.) at Multimedia University (MMU) in Malaysia in May 2013. His thesis, “Hand and Fingertip Detection Based on Free-Form Color Model,” was supervised by Dr. Junaidi Abdullah at the Faculty of Computing and Informatics. Dr. Dawod began his academic journey by obtaining a Bachelor’s degree (B.Sc.) in Computer Science from The University of Mustansirya in Iraq in July 2006, graduating with a commendable GPA of 3.18.

Professional Profiles

ORCID Profile

Google Scholar

Scopus Profile

Teaching Experience

Assistant Professor Dr. Ahmad Yahya Dawod is a distinguished academic and lecturer at Chiang Mai University International College of Digital Innovation in Thailand, where he has been teaching since February 15, 2019. With extensive experience in higher education, Dr. Dawod has taught a variety of courses to both undergraduate and master’s students. For master’s students, he delivers advanced courses such as Artificial Intelligence and Machine Learning for Digital Business and Research Methodology, teaching 6 hours weekly for each course to groups of 20–25 students. At the undergraduate level, he engages in teaching a wide range of subjects, including Communication, Digital Platforms, Networking in Online Society, Internet of Things (IoT), Internet Databases Systems, Internet Programming Language, Big Data, and Information Management Systems, often handling class sizes ranging from 50 to 150 students and dedicating 8–12 hours weekly per course.

Before joining Chiang Mai University, Dr. Dawod taught at Al-Maaref University College from 2013 to 2015, covering subjects such as Artificial Intelligence, Digital Images, Video Processing, Human-Computer Interaction, and Image Processing for classes of 30–40 students. His teaching career began at the University of Mosul, where, as a tutor in the College of Computer Science and Mathematics (2006–2009), he specialized in image processing, computer graphics, and artificial intelligence programs, providing hands-on training in lab environments.

Professional Experience

Dr. Dawod’s expertise spans a broad range of subjects in computer science and programming. His professional background includes:

Programming and Software Training:

MATLAB Trainer (2010–2016):

Conducted courses on MATLAB basics, mathematics, and working with variables in the MATLAB environment.

C++ Trainer (2010–2014):

Delivered training on fundamental programming concepts and variable management.

C# Trainer (2012–2016):

Provided training on C# fundamentals, applications, and Visual Studio.NET.

Dr. Dawod’s extensive experience in teaching and professional training reflects his strong proficiency in computer science, digital innovation, and programming.

Research Interests

His research focuses on Image processing, Machine Learning, Machine vision, Artificial Intelligence, Robotic Control, Video Processing, Computer Graphical programming, Augmented Reality, Virtual Reality, Computer Vision, Human-computer interaction, Sign Language Recognition, and Sign Language Interpretation.

Achievements

Medical Image Processing Projects

Segmenting and classifying brain hemorrhage injuries using CT scan images.

Detecting and classifying lesions related to diabetic retinopathy (NPDR).

Studying skin cancer (melanoma) using advanced techniques.

Utilized Spyder (IDE) Python and deep learning algorithms for the projects, with research and datasets from Chiang Mai Hospital.

Mangrove Forest Study

Conducting research on mangrove forests and their various ecological features.

Security and Cybersecurity Projects

Developing a face recognition security system (data collection phase).

Identifying car plate numbers, models, and vehicle brands through cybersecurity measures.

Markerless Tracking Augmented Reality Project

Contributing to a project focused on treating insect phobias using augmented reality.

Funded by Multimedia University from 2010 to 2012.

Real-Time 3D Virtual Object Overlay

Overlaying 3D virtual objects onto real environments using optical tracking for accurate registration.

Insect Movement Simulation in Virtual Reality

Created and organized insect simulations using VRML, OpenGL, and Maya.

Ensured insects accurately track and follow hand movements on screen.

Virtual Reality for Surgical Training

Developed a VRML program to create high-quality virtual hearts for training students in surgery, aiming to help overcome fear of surgery.

Sign Language Recognition for Deaf Communication

Devised a new technique using American Sign Language to improve communication for deaf individuals.

Developed four classification approaches with a focus on accuracy in recognition.

Continuous Sign Language Gesture Recognition

Conducted research on detecting and recognizing hand gestures in continuous sign language.

Focused on static and dynamic gesture categories.

Kinect-Based Sign Language Recognition

Developed a novel approach to automatically recognize and interpret sign language using Kinect for Windows V2.

Algorithm capable of recognizing both continuous and isolated sign language.

Real-Time Recognition of Continuous Sign Language

Contributed to advancements in real-time recognition of continuous sign language using Kinect sensors.

Hand Gesture Recognition in Sign Language

Developed methods to recognize one-handed and two-handed signs in sign language.

Tested the method on standard and negative sentence datasets.

Top Notable Publications

“Hotspots and trends of environmental, social and governance (ESG) research: A bibliometric analysis”

Co-authors: G Wan, AY Dawod, S Chanaim, RS Shankar

Published in Data Science and Management, 6(2), 65-75

Citations: 68 (2023)

“An optimal deep learning framework for multi-type hemorrhagic lesions detection and quantification in head CT images for traumatic brain injury”

Co-authors: A Phaphuangwittayakul, Y Guo, F Ying, AY Dawod, S Angkurawaranon

Published in Applied Intelligence

Citations: 52 (2022)

“Adaptive skin color model for hand segmentation”

Co-authors: AY Dawod, J Abdullah, MJ Alam

Published in 2010 International Conference on Computer Applications and Industrial Engineering

Citations: 49 (2010)

“A new method for hand segmentation using free-form skin color model”

Co-authors: AY Dawod, J Abdullah, MJ Alam

Published in 2010 3rd International Conference on Advanced Computer Theory and Engineering

Citations: 29 (2010)

“ESG Rating and Northbound Capital Shareholding Preferences: Evidence from China”

Co-authors: G Wan, AY Dawod

Published in Sustainability Journal, 14(15), 19

Citations: 27 (2022)

“Twitter sentiment analysis and expert ratings of initial coin offering fundraising: evidence from Australia and Singapore markets”

Co-authors: A Chursook, AY Dawod, S Chanaim, N Naktnasukanjn, N Chakpitak

Published in TEM Journal, 11(1), 44

Citations: 26 (2022)

“Fingertips detection from color image with complex background”

Co-authors: AY Dawod, J Abdullah, MJ Alam

Published in The 3rd International Conference on Machine Vision (ICMV), 88-96

Citations: 12 (2010)

“Novel Technique for Isolated Sign Language Based on Fingerspelling Recognition”

Co-authors: AY Dawod, N Chakpitak

Published in 2019 13th International Conference on Software, Knowledge, Information, …

Citations: 11 (2019)

“A Bibliometric and Visual Analysis in the Field of Environment, Social and Governance (ESG) Between 2004 and 2021”

Co-authors: G Wan, AY Dawod, C Nopasit

Published in International Journal of Information Science and Management (IJISM), 21(2)

Citations: 10 (2023)

“Assessing mangrove deforestation using pixel-based image: a machine learning approach”

Co-authors: AY Dawod, MA Sharafuddin

Published in Bulletin of Electrical Engineering and Informatics, 10(6), 3178-3190

Citations: 8 (2021)

“Gesture Segmentation: Automatic Continuous Sign Language Technique Based on Adaptive Contrast Stretching Approach”

Co-authors: AY Dawod, M.J. Nordin, J. Abdullah

Published in Middle-East Journal of Scientific Research, 24, 347-352

Citations: 8 (2016)

“Legal Informatics of HS Code Automatic Compliance Translation Based on Cross-border Trade Digitization”

Co-authors: J Mao, AY Dawod

Published in International Electrical Engineering Congress (iEECON). IEEE, 1-4

Citations: 6 (2022)

“Static Hand Gestures: Fingertips Detection Based on Segmented Images”

Co-authors: AY Dawod, MJ Nordin, J Abdullah

Published in J. Comput. Sci., 11(12), 1090-1098

Citations: 6 (2015)

“Microseismic Monitoring Signal Waveform Recognition and Classification: Review of Contemporary Techniques”

Co-authors: H Shu, AY Dawod

Published in Applied Sciences, 13(23), 12739

Citations: 5 (2023)

“Post-covid teaching of physics experiments through flipped classroom & blended teaching practice at college”

Co-authors: X Wen, AY Dawod

Published in 2022 International Conference on Engineering and Emerging Technologies

Citations: 5 (2022)

“Adaptive Slices in Brain Haemorrhage Segmentation Based on the SLIC Algorithm”

Co-authors: AY Dawod, A Phaphuangwittayaku, F Ying, S Angkurawaranon

Published in Engineering Letters, 29(2)

Citations: 5 (2021)

“Correlation between capital markets and cryptocurrency: impact of the coronavirus”

Co-authors: K Ariya, S Chanaim, AY Dawod

Published in International Journal of Electrical & Computer Engineering, 13(6)

Citations: 4 (2023)

“Hand Feature Detection from Skin Color Model with Complex Background”

Co-authors: AY Dawod, J Abdullah, MJ Alam

Published in Annual International Conference on Advances in Distributed and Parallel Computing

Citations: 4 (2010)

“From traditional to digital: The impact of drones and virtual reality technologies on educational models in the post-epidemic era”

Co-authors: J Lu, AY Dawod, F Ying

Published in Sustainable Engineering and Innovation, 5(2), 261-280

Citations: 3 (2023)

Conclusion

Assist. Prof. Dr. Ahmad Yahya Dawod is highly deserving of the Research for Academic Excellence Citation Award based on his impressive body of work, significant citation impact, and the breadth of research topics he has addressed. His contributions to both academic and applied research, particularly in AI, image processing, and ESG, are commendable. While there are opportunities for enhancing the interdisciplinary nature of his work and boosting his international and public visibility, his current contributions reflect excellence in academic research. Dr. Dawod’s continuous pursuit of innovation and collaboration makes him a valuable candidate for this prestigious recognition.