Bin Liu | Computer Science | Research Excellence Award

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Prof. Bin Liu | Computer Science | Research Excellence Award

Professor | Northwest A&F University | China

Prof. Bin Liu is a researcher at Northwest A&F University, Yangling, China, with expertise in artificial intelligence, computer vision, agricultural informatics, and large-scale model training. He has published 69 Scopus-indexed documents, receiving approximately 2,949 citations and achieving an h-index of 18, reflecting sustained academic impact. His recent work focuses on multi-source data fusion, multimodal learning, remote sensing change detection, and efficient parallel training pipelines for large models, with publications in reputable venues such as IEEE Transactions on Computers, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, and Applied Sciences. Liu has collaborated with over 140 co-authors, demonstrating strong interdisciplinary and international research engagement. His research contributes to societal needs by advancing intelligent agricultural disease diagnosis, improving crop monitoring, and enhancing the efficiency of large-scale AI systems, supporting sustainable agriculture and data-driven environmental management.

Citation Metrics (Scopus)

2949
2200
1500
700
0

Citations

2,949

Documents

69

h-index

18

Citations

Documents

h-index

View Scopus Profile
 View Scopus Profile

Featured Publications


MDS-Net: An image-text enhanced multimodal dual-branch Siamese network for remote sensing change detection


– IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025

PRT: An efficient pipeline reuse technology for large models training


– IEEE International Conference on Cluster Computing (CLUSTER), 2025

VMF-SSD: A novel V-space based multi-scale feature fusion SSD for apple leaf disease detection


– IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023

Aleeza Adeel | Computer Science | Research Excellence Award

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Mrs. Aleeza Adeel | Computer Science | Research Excellence Award

The University of Waikato | New Zealand

Mrs. Aleeza Adeel is a Ph.D. student at the School of Computing and Mathematical Sciences, University of Waikato, New Zealand, specializing in digital twin frameworks, sustainable energy systems, and user-centered computing solutions. Her research focuses on developing interoperable and scalable digital twin technologies to optimize energy system management, enhance operational efficiency, and support sustainable resource utilization. She has contributed to peer-reviewed publications, including a recent article in Energies on an interoperable user-centered digital twin framework, demonstrating her commitment to integrating advanced computational models with real-world energy systems. Aleeza collaborates with interdisciplinary researchers, including experts in energy management and computational modeling, to ensure her work addresses both technical rigor and societal relevance. Her research contributes to sustainable energy transitions by providing data-driven, user-centric solutions that improve system performance, reduce environmental impact, and support informed decision-making in complex energy infrastructures.

Profile: View ORCID Profile 

Featured Publication


An Interoperable User‑Centred Digital Twin Framework for Sustainable Energy System Management

– Adeel, A., Apperley, M., & Walmsley, T. G., Energies, 2026, 19(2), Article 333

Miroslaw Kozielski | Computer Science | Best Researcher Award

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Mr. Miroslaw Kozielski | Computer Science | Best Researcher Award

Kazimierz Wielki University | Poland

Mr. Mirosław Kozielski is a researcher at Kazimierz Wielki University in Bydgoszcz, Poland, specializing in computer science, with a strong focus on natural language processing (NLP), industrial informatics, and Industry 4.0/5.0 technologies. His research addresses the use of intelligent language-based systems for automated industrial documentation, knowledge representation, and digital transformation in modern manufacturing environments. He has authored 7 peer-reviewed publications, which have accumulated 35 citations, and holds an h-index of 3, reflecting a focused and emerging academic impact. Dr. Kozielski collaborates with interdisciplinary teams, contributing to the integration of artificial intelligence with industrial and organizational processes. His work supports the development of efficient, human-centric, and sustainable industrial systems, with societal impact through improved documentation quality, enhanced knowledge accessibility, and the practical adoption of advanced AI-driven solutions in contemporary industrial ecosystems.

Citation Metrics (Scopus)

35
25
15
5
0

Citations

35

Documents

7

h-index

3

Citations

Documents

h-index

View Scopus Profile
 View ORCID Profile

Featured Publications

Christian Schachtner | Computer Science | Research Excellence Award

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Prof. Dr. Christian Schachtner | Computer Science | Research Excellence Award

Professor of Business Informatics | RheinMain University of Applied Sciences | Germany

Dr. Christian Schachtner is a researcher at Fachhochschule Wiesbaden, Germany, specializing in safety culture, social impact assessment, and sustainable development in technical and organizational systems. His work bridges corporate social responsibility, environmental management, and smart district development, emphasizing practical solutions to complex societal challenges. According to Scopus, he has authored 23 scholarly publications, received 9 citations, and holds an h-index of 2. His recent research includes open-access work on the determinants of social impact through safety culture in technical organizations and scholarly contributions to book chapters on smart regional and district development initiatives. Dr. Schachtner actively collaborates with international researchers, supporting interdisciplinary perspectives and knowledge exchange. His research contributes to improving organizational governance, enhancing safety performance, and promoting socially responsible and sustainable practices across technical and socio-economic domains.

Citation Metrics (Scopus)

23
15
10
5
0

Citations

9

Documents

23

h-index

2

Citations

Documents

h-index

View Google Scholar Profile
 View Scopus Profile
 View ORCID Profile

Featured Publications

Zhaozhen Jiang | Computer Science | Best Research Article Award

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Dr. Zhaozhen Jiang | Computer Science | Best Research Article Award

Assistant Researcher | Naval Submarine Academy | China

Dr. Zhaozhen Jiang is a distinguished researcher at the Navy Submarine Academy in Qingdao, China, specializing in intelligent systems, maritime navigation, and dynamic target search. His research focuses on the development of advanced path-planning algorithms and neural network–based optimization techniques for complex maritime environments. He has published extensively and collaborated widely with researchers across multiple disciplines, reflecting a strong commitment to interdisciplinary innovation. His recent work on GBNN-based maritime dynamic target search demonstrates a focus on enhancing operational decision-making and situational awareness in challenging naval contexts. Through his research, he aims to advance autonomous maritime systems and contribute to safer, more efficient naval operations, while fostering technological progress with meaningful societal impact.

Citation Metrics (Scopus)

40
30
20
10
0

Citations

37

Documents

15

h-index

4

Citations

Documents

h-index

View Scopus Profile

Featured Publications

Sarbajit Paul Bappy | Computer Science | Research Excellence Award

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Mr. Sarbajit Paul Bappy | Computer Science | Research Excellence Award

Teaching Assistant | Daffodil International University | Bangladesh

Sarbajit Paul Bappy is an emerging researcher in computer science with a growing focus on applied machine learning, medical image analysis, and agricultural informatics. He is currently serving as a Teaching Assistant in the Department of Computer Science and Engineering at Daffodil International University, Bangladesh, where he has been contributing to academic instruction and research support since 2025. Alongside his professional role, he is pursuing his undergraduate degree in Computer Science and Engineering at the same institution, demonstrating a strong integration of academic excellence and early-career research productivity. His scholarly work includes peer-reviewed publications and openly accessible datasets that address critical challenges in healthcare diagnostics and smart agriculture. Notably, he co-authored SkinVisualNet: A Hybrid Deep Learning Approach Leveraging Explainable Models for Identifying Lyme Disease from Skin Rash Images (MAKE, 2025), which combines deep learning with explainable AI techniques to enhance early disease detection. He also contributed significantly to the dataset Jackfruit AgroVision, a comprehensive benchmark for disease detection in jackfruit and its leaves, supporting advancements in precision agriculture and food-security research. His collaborations span multidisciplinary teams involving experts such as Amir Sohel, Rittik Chandra Das Turjy, Md Assaduzzaman, Ahmed Al Marouf, Jon George Rokne, and Reda Alhajj, illustrating his ability to contribute within diverse international research groups. Through his ongoing work in AI-driven health diagnostics, dataset development, and sustainable agricultural technology, Bappy aims to advance research that supports societal well-being, improves disease detection accuracy, and contributes to innovation within global machine learning communities.

Profiles: Google Scholar | ORCID | LinkedIn

Featured Publications

1. Sohel, A., Turjy, R. C. D., Bappy, S. P., Assaduzzaman, M., Marouf, A. A., Rokne, J. G., & Alhajj, R. (2025). SkinVisualNet: A Hybrid Deep Learning Approach Leveraging Explainable Models for Identifying Lyme Disease from Skin Rash Images. Machine Learning and Knowledge Extraction, 7(4), 157. https://doi.org/10.3390/make7040157  MDPI+1

2. Sohel, A., Bijoy, M. H. I., Turjy, R. C. D., & Bappy, S. P. (2025). Jackfruit AgroVision: A Extensive Dataset for Jackfruit Disease and Leaf Disease Detection using Machine Learning. Mendeley Data. https://doi.org/10.17632/pt647jfn52.1

Jia Jinlong | Engineering | Research Excellence Award

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Assoc. Prof. Dr. Jia Jinlong | Engineering | Research Excellence Award

Head of the Mining Department | Wuhan Institute of Technology | China

Dr. Jinlong Jia is a researcher at the Lanzhou Institute of Technology, China, specializing in coal engineering, gas extraction technologies, and energy-related geomechanics with a focus on improving safety, efficiency, and sustainability in coal mining operations. With 24 scientific publications, 434 citations, and an h-index of 12, he has established a strong research profile in the fields of coal pore structure evolution, borehole optimization, and fluid–rock interactions under complex geological conditions. His recent work includes developing numerical simulation models to quantitatively evaluate effect factors in multi-branch pinnate borehole gas extraction in high-gas thick coal seams, and investigating the influence of CO₂–H₂O interaction time on coal pore morphology and water migration, published in Energy and already earning citations for its contributions to clean energy and mine safety. Dr. Jia’s research integrates computational modeling, experimental coal chemistry, and engineering applications to address critical challenges in methane extraction, gas-solid coupling mechanisms, and geological hazard prevention. Over his career, he has collaborated with more than 67 co-authors, demonstrating extensive engagement in multidisciplinary and multi-institutional research teams working across geology, mining engineering, and energy science. His findings contribute to national and global efforts toward safer mining environments, enhanced gas utilization, reduced greenhouse gas emissions, and improved resource recovery efficiency. Through advancing both theoretical understanding and practical solutions in coalbed methane extraction and pore-scale mechanisms, Dr. Jia continues to play a significant role in supporting sustainable energy development and improving engineering practices within the mining and geoscience sectors.

Profile: Scopus 

Featured Publications

Zhu, X., Jia, J., Zhang, L., Ma, Z., Qin, Z., Zhang, H., & Liu, Z. (2025). Study on the numerical simulation model for quantitative evaluation on effect factors of multi‑branch pinnate borehole gas extraction in high‑gas thick coal seams. Himalayan Geology, 46(2), 125–135.

Xu, H., Hu, J., Liu, H., Ding, H., Zhang, K., Jia, J., Fang, H., & Gou, B. (2024). Effect of the interaction time of CO₂–H₂O on the alterations of coal pore morphologies and water migration during wetting. Energy, 294, Article 130944. https://doi.org/10.1016/j.energy.2024.130944

Wenguang Song | Software Development | Best Researcher Award

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Prof. Dr. Wenguang Song | Software Development | Best Researcher Award

Educator at Guangdong Ocean University, China

Professor Song Wenguang is a highly accomplished researcher and academic in the fields of software engineering, petroleum software technology, and big data analysis. With a strong background in computer science, he has built an impressive career that bridges theory, applied research, and industrial innovation. His work has been pivotal in developing software systems and interpretation methods for production logging, which are essential for petroleum exploration and resource management. Beyond petroleum-focused research, he has also contributed to interdisciplinary domains such as artificial intelligence for medical prediction and digital watermarking-based plagiarism detection. His professional journey reflects an ability to integrate computing technologies into critical industrial and societal applications, underscoring his reputation as a versatile and impactful scholar. Through his participation in national and provincial projects and his extensive publication record in Scopus-indexed journals and IEEE conferences, he has established a strong academic and industrial presence, contributing meaningfully to both research and society.

Professional Profile 

Scopus Profile | ORCID Profile 

Education

Professor Song Wenguang pursued his academic training with a focus on computer science and engineering, steadily building his expertise through undergraduate, postgraduate, and doctoral studies. He completed his Bachelor of Engineering in Computer Science and Technology at Jianghan Petroleum University, establishing a strong foundation in computing and its applications to industrial technologies. He continued his studies with a Master’s degree in Computer Application Technology at Yangtze University, where he deepened his technical skills in applied software systems and information processing. His academic journey culminated with a Doctor of Engineering in Geodetection and Information Technology, also at Yangtze University, equipping him with specialized knowledge in computational methods for petroleum software technologies and logging interpretation. This educational progression highlights his commitment to advancing both the theoretical and applied aspects of computer science. His formal education has prepared him to contribute to complex, interdisciplinary challenges and foster innovation in both academic and industrial domains.

Experience

Professor Song Wenguang has accumulated extensive professional and research experience that blends academic teaching, research leadership, and industrial collaboration. As a professor at the School of Computer Science and Engineering, Guangdong Ocean University, he has contributed significantly to higher education, mentoring students and leading research initiatives in computer science and petroleum technologies. His experience includes active involvement in numerous large-scale projects funded by national and provincial agencies, as well as collaborations with major corporations such as the China National Petroleum Corporation, China National Offshore Oil Corporation, and China Oilfield Services Limited. In these roles, he has driven advancements in oilfield data interpretation, multiphase flow simulation, and logging technologies, showcasing his ability to translate academic knowledge into real-world industrial solutions. His career also reflects active participation in cross-disciplinary initiatives, including medical prediction systems and AI-based solutions, demonstrating his versatility as a researcher. Collectively, his experience underscores his leadership and innovative capacity in both academia and industry.

Research Interest

Professor Song Wenguang’s research interests encompass a broad spectrum of computer science applications, with a primary focus on software engineering, petroleum software technology, and big data analysis. He has made substantial contributions to the development of methodologies and software tools for production logging interpretation, which are vital for optimizing petroleum engineering processes and resource management. His work extends into artificial intelligence, particularly the use of neural networks for medical data prediction, which demonstrates the adaptability of computational approaches to healthcare challenges. Additionally, he has explored digital watermarking and neural networks for anti-plagiarism detection, reflecting his engagement with issues of academic integrity in the digital era. His interdisciplinary approach highlights his commitment to applying computer science not only to traditional industrial fields but also to emerging domains. By integrating big data techniques with engineering applications, he continues to push the boundaries of research, offering innovative solutions to both scientific and societal needs.

Awards and Honors

Throughout his academic and professional journey, Professor Song Wenguang has earned recognition for his significant contributions to research, education, and industry collaborations. His leadership in multiple government-funded and industry-supported projects has positioned him as a key contributor to advancements in petroleum logging software and computational technologies. While specific award details are not provided, his extensive list of successfully completed projects with leading organizations such as CNPC, CNOOC, and China Oilfield Services Limited reflects the high level of trust and acknowledgment he has received within the energy sector. His publication record in prestigious international journals and conferences, including Scopus and IEEE, further demonstrates his recognition in the global academic community. As a professor, his role in advancing student research and building academic-industry collaborations can also be considered a form of academic honor, showcasing his influence in shaping future researchers. His career achievements reflect ongoing professional acknowledgment and respect within his fields of expertise.

Research Skills

Professor Song Wenguang possesses a diverse set of research skills that span both theoretical and applied domains in computer science and engineering. He is skilled in software design and development for petroleum applications, including production logging interpretation and multiphase flow analysis, which require advanced computational modeling and algorithmic thinking. His expertise in big data analysis allows him to process and interpret complex datasets, contributing to solutions for resource optimization and predictive modeling. In addition, he is proficient in artificial intelligence and machine learning techniques, applying neural networks to areas such as medical prediction and intelligent decision systems. His work on digital watermarking and plagiarism detection further showcases his technical innovation in data security and academic integrity. Professor Song’s ability to collaborate across large-scale industrial projects demonstrates his strong project management and problem-solving capabilities. These skills collectively highlight his capacity to deliver impactful research outcomes that benefit both academia and industry.

Publication Top Notes

Title: Optimization of steel plate quality inspection driven by PscSE and SPPFELAN
Journal: Microwave and Optical Technology Letters
Year: 2024

Title: Pumping machine fault diagnosis based on fused RDC-RBF
Journal: PLOS ONE
Year: 2023
Citations: 2

Conclusion

Professor Song Wenguang is a highly deserving candidate for the Best Researcher Award. His significant contributions to software engineering, petroleum software technology, and big data applications have advanced both academic research and industrial practice. His leadership in multiple large-scale projects, strong record of publications, and interdisciplinary expertise showcase his capacity to impact society through innovation and knowledge transfer. With continued international collaborations and visibility in global scientific communities, Professor Song is well-positioned to further elevate his contributions and inspire future generations of researchers.

Andrzej Augustynowicz | Engineering | Best Researcher Award

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Mr. Andrzej Augustynowicz | Engineering | Best Researcher Award

Professor at Opole University of Technology, Poland

Dr. Andrzej Augustynowicz is a highly accomplished University Professor at the Opole University of Technology, specializing in automotive engineering and vehicle mechatronics. His academic and professional career is marked by a strong focus on energy systems in vehicles, hybrid propulsion, driver behavior modeling, and advanced vehicle diagnostics. He has contributed extensively to both theoretical research and practical applications through experimental studies, computational simulations, and diagnostic analyses that address challenges in energy efficiency, traffic safety, and sustainable mobility. His research is published in internationally indexed journals and presented at reputed conferences, strengthening the global understanding of modern automotive systems. Alongside his research, he is an active mentor, doctoral supervisor, and reviewer of scientific works, playing a key role in developing the next generation of researchers. His contributions extend beyond academia through his involvement in professional societies and initiatives in electromobility and continuing engineering education.

Professional Profile 

Scopus Profile | ORCID Profile 

Education

Dr. Andrzej Augustynowicz has pursued a distinguished academic path culminating in a habilitation degree in engineering, positioning him as a recognized authority in the field of automotive research. His educational background combines a rigorous foundation in mechanical and automotive engineering with advanced specialization in mechatronics of vehicles and machines. Over the course of his academic development, he has gained deep expertise in energy systems, mathematical modeling, vehicle dynamics, and hybrid technologies. His education has enabled him to bridge theoretical and applied perspectives, equipping him to conduct impactful experimental research and computational studies that contribute to both academia and industry. Through his advanced qualifications, he is not only able to lead complex research projects but also to mentor doctoral candidates, design innovative curricula, and serve as a reviewer of scientific dissertations. His education reflects both depth and breadth, supporting a career dedicated to advancing sustainable and intelligent mobility solutions.

Experience

Professor Augustynowicz holds an esteemed academic position at the Department of Vehicle and Machine Mechatronics, where he combines research, teaching, and academic leadership. His experience includes supervising doctoral and postgraduate theses in the fields of energy systems, vehicle diagnostics, and hybrid drive technologies. He has contributed to numerous collaborative research initiatives and co-authored impactful studies with national and international partners, underscoring his active engagement in global academic networks. Beyond supervision, he has served as a reviewer of doctoral dissertations and scientific works in automotive engineering and internal combustion systems, thereby ensuring the quality and rigor of scholarly contributions in his domain. His experience also spans leadership in continuing education programs, where he develops and promotes courses in electromobility and sustainable transportation technologies. With a career blending research, teaching, and academic service, he has established himself as a versatile expert committed to innovation, mentorship, and advancing the engineering profession.

Research Interest

Dr. Augustynowicz’s research interests cover a wide spectrum of topics within automotive and mechanical engineering, with a particular emphasis on sustainable energy systems and driver–vehicle interactions. His studies focus on automotive engines as energy systems, hybrid drive mechanisms, and mathematical modeling of driver behavior in regulating vehicle systems. He has conducted both experimental investigations—such as bench and road analysis of spark-ignition engines—and computational simulations to optimize vehicle performance and safety. His work also extends to traffic safety, accident reconstruction, and diagnostic systems for vehicles, all of which contribute to reducing environmental impacts and improving reliability. A strong interdisciplinary focus characterizes his approach, integrating mechanical design, human factors, energy efficiency, and advanced diagnostics. His interest in emerging areas such as electromobility and intelligent energy assistance systems highlights his vision for future-oriented automotive engineering. Collectively, his research interests reflect a dedication to innovation, sustainability, and road safety in transportation systems.

Award and Honor

Throughout his career, Dr. Augustynowicz has received recognition for his academic and research contributions in automotive engineering. His publications in high-impact journals indexed in Scopus, MDPI, and other international platforms stand as a testament to the quality and originality of his research. He has collaborated with leading researchers in Europe and contributed to cross-border projects, earning respect in the international research community. His role as a doctoral supervisor and reviewer of theses has also been acknowledged as a valuable service to higher education and scientific advancement. Membership in esteemed professional societies such as the Polish Scientific Society of Combustion Engines reflects the recognition of his expertise by peers in the field. His involvement in continuing education initiatives in electromobility has further demonstrated his commitment to knowledge dissemination. These achievements underline his professional stature and reinforce his position as a deserving candidate for academic and research awards.

Research Skills

Dr. Andrzej Augustynowicz possesses a diverse set of advanced research skills that have shaped his academic and professional success. He is proficient in experimental techniques for analyzing automotive energy systems, including road and laboratory testing of powertrains, hybrid systems, and diagnostic applications. His computational expertise allows him to conduct mathematical modeling of driver behavior and vehicle dynamics, as well as simulations for energy management and speed control. These capabilities enable him to link theory with practical application, offering comprehensive solutions to complex engineering challenges. He is skilled in project leadership, having contributed to collaborative research initiatives and interdisciplinary investigations. In addition, he has strong academic supervision skills, guiding doctoral and postgraduate students through advanced research topics. His ability to critically review scholarly works, contribute to curriculum development, and support continuing education reflects his versatility. These combined skills highlight him as a research leader with significant impact on academia and industry alike.

Publication Top Notes

Title: Evaluation of the Quality of Welded Joints After Repair of Automotive Frame Rails
Authors: Andrzej Augustynowicz, Mariusz Prażmowski, Wiktoria Wilczyńska, Mariusz Graba
Year: 2025
Journal: Materials

Title: Analysis of Passenger Car Powertrain System Measurements in Road Conditions
Authors: Andrzej Bieniek, Mariusz Graba, Jarosław Mamala, Andrzej Augustynowicz, Michał Szczepanek
Year: 2023
Journal: Combustion Engines

Title: Assessment of Energy Demand for PHEVs in Year-Round Operating Conditions
Authors: Mariusz Graba, Jarosław Mamala, Andrzej Bieniek, Andrzej Augustynowicz, Krystian Czernek, Andżelika Krupińska, Sylwia Włodarczak, Marek Ochowiak
Year: 2023
Journal: Energies

Title: The Concept of Using an Expert System and Multi-Valued Logic Trees to Assess the Energy Consumption of an Electric Car in Selected Driving Cycles
Authors: Adam Deptuła, Andrzej Augustynowicz, Michał Stosiak, Krzysztof Towarnicki, Mykola Karpenko
Year: 2022
Journal: Energies

Title: Study of Energy Consumption of a Hybrid Vehicle in Real-World Conditions
Authors: Jarosław Mamala, Mariusz Graba, Andrzej Bieniek, Krzysztof Prażnowski, Andrzej Augustynowicz, Michal Smieja
Year: 2021
Journal: Eksploatacja i Niezawodnosc – Maintenance and Reliability

Title: Evaluation of Applicability of Dielectric Constant in Monitoring Aging Processes in Engine Oils
Authors: Leszek Gomółka, Andrzej Augustynowicz
Year: 2019
Journal: Eksploatacja i Niezawodnosc – Maintenance and Reliability

Title: Preliminary Evaluation Research of a Powertrain System with Electrically Controlled Planetary Gear
Authors: Andrzej Lechowicz, Andrzej Augustynowicz
Year: 2018
Journal: International Journal of Vehicle Design

Title: Identification of Static Unbalance Wheel of Passenger Car Carried Out on a Road
Authors: Krzysztof Prażnowski, Sebastian Brol, Andrzej Augustynowicz
Year: 2014
Journal: Solid State Phenomena (SSP)

Conclusion

In summary, Dr. Andrzej Augustynowicz’s extensive expertise in vehicle energy systems, hybrid technologies, and driver behavior modeling, combined with his strong record of research, publication, and academic mentorship, make him a highly deserving candidate for the Best Researcher Award. His scholarly contributions have advanced the fields of automotive diagnostics, hybrid drive systems, and road safety, while his leadership in education has nurtured future engineering innovators. With continued growth in international collaborations and high-impact publications, he has the potential to play an even greater role in shaping the future of sustainable mobility and research excellence.

CHENGZU DONG | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Prof . CHENGZU DONG | Computer Science | Best Researcher Award

Assistant Professor at Lingnan University , Hong Kong

Dr. Chengzu Dong is a highly accomplished early-career researcher specializing in cybersecurity, AI, blockchain, IoT, UAVs, and edge computing. Currently an Assistant Professor at Lingnan University, he has published over 30 peer-reviewed papers in prestigious Q1 journals and Core A/A* conferences, showcasing his strong research productivity and interdisciplinary expertise. His collaborations with CSIRO and industry partners reflect a robust blend of academic rigor and applied impact. Dr. Dong has received multiple accolades, including best paper awards, hackathon honors, and scholarships, highlighting his innovation and leadership potential. In addition to research, he has made significant contributions to teaching, mentoring, and curriculum development across several international institutions. While he could further enhance his profile through principal investigator roles and broader international visibility, his achievements and contributions make him a strong candidate for the Best Researcher Award, particularly in emerging areas of intelligent systems, secure computing, and next-generation network technologies.

Professional Profile 

Education🎓

Dr. Chengzu Dong has a strong and diverse educational background in computer science and information technology. He earned his Ph.D. from Deakin University, Australia, specializing in blockchain, AI, UAVs, edge computing, IoT, Web3, and the Metaverse. During his Ph.D. studies (2021–2024), he conducted extensive research in next-generation technologies, contributing significantly to academic and applied fields. Prior to that, he completed a Bachelor of Computer Science (Honours) at Swinburne University of Technology in 2020, where he deepened his expertise in software development and systems engineering. He also holds a Bachelor of Information Technology from Deakin University (2016–2019), which laid the foundation for his interests in cybersecurity and emerging technologies. His education reflects a consistent focus on interdisciplinary innovation and a strong grounding in both theoretical knowledge and practical applications. Dr. Dong’s academic journey across top Australian universities has prepared him well for a career in high-impact, technology-driven research and teaching.

Professional Experience📝

Dr. Chengzu Dong brings a rich and diverse professional background in academia, research, and industry. He is currently serving as an Assistant Professor at Lingnan University, Hong Kong, where he teaches and develops courses in blockchain, data mining, machine learning, and cybersecurity. Prior to this, he held multiple academic roles at Deakin University, including seminar lecturer, academic tutor, course developer, and capstone mentor, contributing significantly to curriculum innovation and student mentorship. His research experience includes collaborations with CSIRO, Australia’s leading scientific agency, where he worked on blockchain and AI projects. He also held positions as a research assistant at Swinburne University and Deakin University, and worked in software development roles at Artchain Global, Creative Geelong, and FPT Software. These roles highlight his strong technical skills and ability to bridge academia and industry. Dr. Dong’s professional journey reflects a well-rounded portfolio of teaching, research, and applied innovation in emerging technologies.

Research Interest🔎

Dr. Chengzu Dong’s research interests lie at the intersection of emerging technologies and intelligent systems, with a strong focus on cybersecurity, blockchain, artificial intelligence (AI), Internet of Things (IoT), unmanned aerial vehicles (UAVs), edge computing, Web3, and the Metaverse. His work aims to address critical challenges in data privacy, secure communication, and decentralized systems through the integration of blockchain and federated learning frameworks. He is particularly passionate about developing secure and efficient architectures for UAV delivery systems and smart edge networks, making his research highly relevant to real-world applications. Dr. Dong’s interdisciplinary approach combines theoretical advancements with practical implementations, as demonstrated by his collaborations with CSIRO and numerous industry partners. His contributions not only advance academic knowledge but also provide innovative solutions to pressing technological issues in digital security and autonomous systems. This diverse and forward-looking research portfolio positions him as a thought leader in next-generation computing and intelligent infrastructure.

Award and Honor🏆

Dr. Chengzu Dong has received numerous awards and honors in recognition of his academic excellence, research impact, and innovative contributions to emerging technologies. He was the recipient of the prestigious Deakin University Postgraduate Research Scholarship and a CSIRO Top-up Scholarship, supporting his advanced research in blockchain and AI. His work has earned best paper awards at international conferences such as IEEE IAS GLOBCONHT 2023, and he has achieved first runner-up prizes in blockchain hackathons in both Thailand and Australia. Dr. Dong is a certified member of the Australian Computer Society and holds various professional certifications, including Cisco CCNET and Certificate IV in Training and Assessment. His academic excellence was further recognized with the Golden Key Top 15% Student Award. He has also received recognition as a journal and conference reviewer, including a free ACM membership. These accolades collectively highlight his leadership, innovation, and dedication to research excellence and professional development.

Research Skill🔬

Dr. Chengzu Dong possesses a comprehensive set of research skills that span theoretical development, applied experimentation, and interdisciplinary collaboration. He is highly proficient in blockchain technology, artificial intelligence, federated learning, and cybersecurity frameworks, with a particular focus on secure systems for UAVs and edge computing environments. Dr. Dong demonstrates strong technical expertise in programming languages such as Python, Node.js, and React, along with experience in data analytics, machine learning model development, and system architecture design. His ability to design privacy-preserving frameworks and implement decentralized solutions reflects his strength in combining research theory with practical outcomes. Additionally, his experience working with organizations like CSIRO showcases his capability to collaborate on large-scale, real-world projects. Dr. Dong is also skilled in academic writing and publishing, with over 30 high-quality publications in top-tier journals and conferences. His strong analytical mindset, problem-solving ability, and innovation make him a highly capable and impactful researcher in advanced computing domains.

Conclusion💡

Dr. Chengzu Dong exemplifies the qualities of an outstanding researcher and academic, making him a highly suitable candidate for the Best Researcher Award. His extensive contributions to cutting-edge areas such as blockchain, AI, cybersecurity, and UAV systems reflect both depth and breadth in research expertise. With over 30 high-impact publications, multiple international awards, and active collaborations with renowned institutions like CSIRO, Dr. Dong has demonstrated consistent research excellence and innovation. His ability to translate theoretical knowledge into practical solutions for real-world challenges, especially in emerging technologies, underscores his relevance and leadership in the field. Additionally, his dedication to teaching and mentoring at multiple universities enhances his influence in shaping future researchers and professionals. Dr. Dong’s interdisciplinary skills, academic achievements, and forward-thinking research agenda not only position him as a leader in his domain but also affirm his deserving candidacy for this prestigious recognition.

Publications Top Noted✍

  • Title: BBM: A Blockchain-Based Model for Open Banking via Self-Sovereign Identity
    Authors: C. Dong, Z. Wang, S. Chen, Y. Xiang
    Year: 2020
    Citations: 32

  • Title: A Novel Security Framework for Edge Computing Based UAV Delivery System
    Authors: A. Yao, F. Jiang, X. Li, C. Dong, Y.X. Jia, X.L. Gang Li
    Year: 2021
    Citations: 28

  • Title: Enhancing Quality of Service Through Federated Learning in Edge-Cloud Architecture
    Authors: J. Zhou, S. Pal, C. Dong, K. Wang
    Year: 2024
    Citations: 22

  • Title: A Blockchain-Aided Self-Sovereign Identity Framework for Edge-Based UAV Delivery System
    Authors: C. Dong, F. Jiang, X. Li, A. Yao, G. Li, X. Liu
    Year: 2021
    Citations: 20

  • Title: Optimizing Performance in Federated Person Re-Identification Through Benchmark Evaluation for Blockchain-Integrated Smart UAV Delivery Systems
    Authors: C. Dong, J. Zhou, Q. An, F. Jiang, S. Chen, L. Pan, X. Liu
    Year: 2023
    Citations: 15

  • Title: Continuous Authentication for UAV Delivery Systems Under Zero-Trust Security Framework
    Authors: C. Dong, F. Jiang, S. Chen, X. Liu
    Year: 2022
    Citations: 15

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