Assist. Prof. Dr. Yu-Chieh Chu | Automatic identification | Best Researcher Award

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Assist. Prof. Dr. Yu-Chieh Chu | Automatic identification | Best Researcher Award

Assist. Prof. Dr. Yu-Chieh Chu , Assistant Professor , Chung Yuan Christian University , Taiwan.

Dr. Yu‑Chieh Chu is an Assistant Professor in the Department of Interior Design at Chung Yuan Christian University, Taiwan. He earned his Ph.D. from the Graduate Institute of Architecture at National Cheng Kung University in 2018. With a strong background in both architecture and interior design, he has served as a lecturer and researcher focusing on heritage conservation. Currently, he applies artificial intelligence and damage detection techniques for preserving historic environments and monuments. Passionate about merging heritage and technology, Dr. Chu contributes significantly to sustainable architectural conservation through research, teaching, and consultancy.

Publication Profile

Google Scholar

🎓 Education Background

Dr. Yu‑Chieh Chu earned his Ph.D. in Architecture from the Graduate Institute of Architecture at National Cheng Kung University, Taiwan, in 2018. Prior to this, he gained comprehensive training in both the theoretical and practical aspects of architecture and interior design, deepening his knowledge of heritage conservation and sustainable design. This academic foundation shaped his approach to addressing complex conservation challenges, especially in preserving heritage buildings and environments. His doctoral research focused extensively on traditional architecture and its interaction with natural environmental elements, laying the groundwork for his future innovations in AI‑driven heritage conservation.

💼 Professional Experience

As an Assistant Professor in the Department of Interior Design at Chung Yuan Christian University, Taiwan, Dr. Yu‑Chieh Chu has accumulated rich experience teaching courses in architecture and heritage preservation. He has served as a consultant for the Bureau of Cultural Heritage, Ministry of Culture, Taiwan, providing expert advice and conducting site assessments for heritage buildings, including the Mengjia Longshan Temple and the Beigang Chaotian Temple. Through his role, he applies artificial intelligence and damage detection methods to heritage conservation, making significant advances in preventive maintenance and environmental analysis of historic buildings across Taiwan.

🏆 Awards and Honors

Throughout his academic and professional journey, Dr. Yu‑Chieh Chu has earned accolades for his dedicated work in heritage preservation and architectural conservation. His successful projects commissioned by the Bureau of Cultural Heritage, Ministry of Culture, Taiwan, reflect national recognition of his expertise. Moreover, his published works have gained international attention, cited in esteemed journals within the fields of architecture and heritage conservation. As an active member of the Taiwan Cultural Heritage Preservation Society, he has strengthened connections between researchers and heritage conservation professionals, reinforcing his role as an influencer in heritage and architectural fields.

🔍 Research Focus

Dr. Yu‑Chieh Chu’s research interests lie at the intersection of artificial intelligence, damage detection, and heritage conservation. He focuses on employing advanced AI techniques and simulations for assessing and preserving historical buildings and environments. His ongoing and completed projects emphasize preventive conservation for iconic heritage sites in Taiwan, including Mengjia Longshan Temple, Beigang Chaotian Temple, and the Luzhou Li Residence. His work aims to aid in site restoration and long‑term preservation planning, making significant contributions to both heritage conservation theory and practical site applications.

✅ Conclusion

With a strong academic background, extensive teaching experience, and deep research interests in heritage conservation and artificial intelligence, Dr. Yu‑Chieh Chu stands out as a pivotal figure in heritage and architectural conservation. His accomplishments range from site assessments and environmental simulations for historic temples to published papers that have gained international recognition. Dedicated to preserving cultural heritage for future generations, he combines traditional architectural knowledge with cutting‑edge technology, making him a worthy candidate for the Computer Scientists Awards and a beacon of innovation and expertise in heritage preservation.

📚 Selected Publications (Top Notes)

  1. An example of ecological wisdom in historical settlement: The wind environment of Huazhai village in Taiwan
    Journal of Asian Architecture and Building Engineering, 16 (3), 463–470 (2017) | Cited by 15

  2. The impacts of site selection and planning of a historic settlement on a sustainable residence
    Applied Ecology & Environmental Research, 15 (2) (2017) | Cited by 12

  3. A field assessment on natural ventilation and thermal comfort of historical district — A case of the Wugoushui settlement in Taiwan
    Journal of Earth Science and Engineering, 5 (8), 463–472 (2015) | Cited by 6

  4. Numerical Simulation of the Environmental Conditions in Tainan Confucius Temple as a Means of Planning Preventive Conservation Strategies
    Journal of Cultural Heritage Conservation, 51 (4), 71–82 (2020) | Cited by 3

  5. The Preventative Preservation of Cultural Heritage Under Hot and Humid Climate: A Case Study of Tainan Confucian Temple in Taiwan
    16th International Conference on Studies, Repairs and Maintenance of Heritage Architecture (2019) | Cited by 4

  6. A preliminary research on the impact of monsoon to traditional houses in Peng-Hu Hua-Zhai, Taiwan
    2013 Hawaii International Conference on Arts and Humanities (2013) | Cited by 2

 

Dr. DEBADATTA NAIK | network Analysis | Best Researcher Award

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Dr. DEBADATTA NAIK | network Analysis | Best Researcher Award

Dr. DEBADATTA NAIK, Researcher cum Teacher, VIZJA University, Poland.

Dr. Debadatta Naik is a passionate educator, researcher, and expert in Computer Science & Engineering, specializing in social network analysis, community detection, and distributed computing. Currently pursuing a Ph.D. at the prestigious Indian Institute of Technology (ISM), Dhanbad, he has built an academic and research profile that reflects deep proficiency in designing computational strategies for social network analysis. In over a decade of teaching and research experience across institutions in Odisha, he has inspired countless students. As an avid programmer and researcher, he is proficient in C, C++, and Python, making significant contributions to computational theory and network dynamics.

Publication Profile

Scopus

ORCID

🎓 Education Background

Dr. Debadatta Naik holds a Ph.D. in Computer Science & Engineering from the Indian Institute of Technology (ISM), Dhanbad (2017–2024), specializing in computational strategies for social network analysis. Prior to this, he earned an M.Tech. from the National Institute of Technology, Rourkela (2015–2017), focusing on centrality approaches for community detection in social networks. He graduated with a B.Tech. in Information Technology from V.S.S.U.T. (formerly UCE Burla), Sambalpur, in 2007. This strong academic background has laid a solid foundation for his research and teaching career, making him a leading contributor in this field.

👔 Professional Experience

With over a decade of teaching and research experience, Dr. Debadatta Naik has served as a lecturer at Raajdhani Engineering College, Bhubaneswar (2010–2015), and GITA, Bhubaneswar (2007–2008). Currently pursuing doctoral research, he is an integral collaborator with VIZJA University, Warsaw, Poland, exploring advances in social network analysis. His expertise spans programming languages (C, C++), database technologies (MySQL), and theoretical subjects like the theory of computation, data structures, and compiler design. A trusted educator and reviewer, he has conducted reviews for reputable journals such as Social Network Analysis and Mining, Scientific Review, and the Computing Journal.

🏅 Awards and Honors

Throughout his academic and professional journey, Dr. Debadatta Naik has been recognized for excellence. He received a Ph.D. Fellowship (2017–2022) and an M.Tech. Fellowship (2015–2017) from the Government of India through GATE scores of 303 and 477, respectively. During his undergraduate years, he secured first positions in athletic meets and distinguished himself in painting, sketching, and calligraphy competitions at V.S.S.U.T. He was a Golden Jubilee Torch Bearer and served as the ART and Photography Secretary, making significant contributions to campus life. These accomplishments reflect his multidisciplinary talents and commitment to excellence.

🔍 Research Focus

Dr. Debadatta Naik’s research focuses on social network analysis, community detection, link prediction, and workflow scheduling. He develops computational strategies for extracting insights from massive social networks, leveraging tools like Hadoop and MapReduce. His work has been published in top journals such as Simulation Modelling Practice and Theory, Journal of Ambient Intelligence and Humanized Computing, Cluster Computing, and Expert Systems with Applications. By exploring innovative approaches like Quantum-PSO and hybrid optimization methods, he aims to optimize the performance and scalability of complex network analytics for cloud environments, making a significant impact in both academia and industry.

✅ Conclusion

With a solid academic background, deep teaching experience, and a strong research record, Dr. Debadatta Naik has established himself as a dedicated educator and prolific researcher. His work advances the understanding of social network dynamics, while his active role in peer review and collaborative research showcases his ongoing contribution to the scientific community. As he continues to expand the frontiers of computational social network analysis and workflow scheduling, he inspires the next generation of engineers and researchers to pursue excellence and innovation in computer science.

📑 Publication Top Notes

  1. Hgwomultiqos: A hybrid grey wolf optimization approach for qos‑constrained workflow scheduling in iaas clouds.
    Simulation Modelling Practice and Theory, 2025
    Cited by: Forthcoming

  2. Enhanced link prediction using sentiment attribute and community detection.
    Journal of Ambient Intelligence and Humanized Computing, 2023
    Cited by: 7

  3. Quantum‑pso based unsupervised clustering of users in social networks using attributes.
    Cluster Computing, 2023
    Cited by: 3

  4. Parallel and distributed paradigms for community detection in social networks: A methodological review.
    Expert Systems with Applications, 2022
    Cited by: 24

  5. Map‑reduce‑based centrality detection in social networks: An algorithmic approach.
    Arabian Journal for Science and Engineering, 2020
    Cited by: 21

  6. Genetic algorithm‑based community detection in large‑scale social networks.
    Neural Computing and Applications, 2020
    Cited by: 48

  7. Mr‑ibc: Mapreduce‑based incremental betweenness centrality in large‑scale complex networks.
    Social Network Analysis and Mining, 2020
    Cited by: 19

 

Dr. Adina Aniculaesei | Technology | Best Researcher Award

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Dr. Adina Aniculaesei | Technology | Best Researcher Award

Dr. Adina Aniculaesei , Postdoctoral Researcher, Department of Computer Science and Engineering, University of Gothenburg and Chalmers University of Technology, Sweden.

Adina Aniculăesei is a passionate researcher and expert in automated safety‑critical systems, currently based in Gothenburg, Sweden. Born in Iași, Romania, she has dedicated her career to making autonomous vehicles and mobile robots safer, focusing on verification, formal methods, and runtime validation. Through years of multidisciplinary research and teaching, she has shaped the future of software engineering for intelligent transportation and collaborative robotics. Her deep knowledge of formal verification and system modeling has positioned her as a leading voice in the realm of dependable and trustworthy autonomous platforms, making significant impacts in both academia and industry.

Publication Profile

Google Scholar

🎓 Education Background

Adina earned her Doctorate (Dr. rer. nat.) in Computer Science from the Clausthal University of Technology, Germany, in 2024, graduating magna cum laude. She holds an M.Sc. in Computer Science from the Technical University of Braunschweig (2011) and a B.Sc. in Computer Science from Alexandru Ioan Cuza University, Romania (2007). An Erasmus–Socrates scholar, she enriched her studies with a year at the Technical University of Braunschweig. Her rigorous training combined formal methods, software engineering, and automated test case generation, making her adept at tackling complex, safety‑critical domains.

💼 Professional Experience

Adina Aniculăesei has worked as a Postdoctoral Researcher at the University of Gothenburg and Chalmers University of Technology (since October 2024), focusing on translating formal behavioral specifications into ROS2 nodes for collaborative robot applications. Previously, she served as a Doctoral Researcher and Research Assistant at TU Clausthal, leading industry collaborations, teaching, and mentoring students. Her experience includes roles across software and systems engineering, with a strong focus on safety, formal verification, and automated test generation for automotive and robotics domains, making her a sought‑after expert and educator in the field.

🏅 Awards and Honors

Throughout her academic journey, Adina Aniculăesei has been recognized for excellence and dedication. She received the Siemens Master Program Scholarship (2007–2009) and the Erasmus–Socrates Scholarship (2005–2006). Her doctoral studies earned her the magna cum laude distinction upon defending her Ph.D. thesis at Clausthal University of Technology in 2024. Additionally, she holds technical certifications including ISAQB Certified Professional for Software Architecture and ISTQB Certified Tester Foundation Level, highlighting her commitment to mastering both theoretical and practical elements of her field.

🔍 Research Focus

Adina Aniculăesei’s research centers on formal verification, automated test generation, and runtime monitoring for automated safety‑critical and collaborative multi‑agent systems. She explores methods for specifying, verifying, and validating complex operational design domains (ODDs) for autonomous vehicles and mobile robots. Her expertise includes formal methods (SPIN, NuSMV, PRISM), test case generation, model checking, and AI‑based environment perception, making her work pivotal in shaping next‑generation transportation and robotics technologies.

✅ Conclusion

With a profound background in formal methods, automated test generation, and verification of safety‑critical systems, Adina Aniculăesei has established herself as an influential expert in both academia and industry. Her dedication to mentoring students, publishing impactful research, and collaborating with international institutions has positioned her as a thought leader in software engineering for dependable, trustworthy, and safe autonomous technologies.

📚 Publication Top Notes

  • Towards a holistic software systems engineering approach for dependable autonomous systems – Proceedings of the 1st International Workshop on Software Engineering for AI (2018). Cited by 70
  • Towards the verification of safety‑critical autonomous systems in dynamic environments – arXiv preprint (2016). Cited by 42
  • Automated generation of requirements‑based test cases for an adaptive cruise control system – IEEE Workshop on Validation, Analysis and Evolution of Software Tests (2018). Cited by 24
  • UML‑based analysis of power consumption for real‑time embedded systems – IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications (2011). Cited by 24
  • Graceful degradation of decision and control responsibility for autonomous systems based on dependability cages – 5th International Symposium on Future Active Safety Technology Toward Zero Accidents (2019). Cited by 14

 

Prof. Dr. Xiaoliang Li | Architecture | Best Researcher Award

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Prof. Dr. Xiaoliang Li | Architecture | Best Researcher Award

Prof. Dr. Xiaoliang Li, Teacher, North China University of Aerospace Engineering, China.

Li Xiaoliang is a dedicated Professor of Environmental Science and Engineering at Hebei Environmental Engineering College in Qinhuangdao, specializing in ecological engineering and sustainable environmental solutions 🌍. Since earning his doctoral degree from China Agricultural University, he has built a robust academic and research career across institutions and international collaborations. He has served as a visiting scholar in Denmark, contributed extensively to EU-funded projects, and participated in pivotal national and provincial research efforts 🌊. As a passionate educator and researcher, Li has authored numerous papers and patented innovations that continue to shape the fields of environmental engineering, wastewater treatment, and ecological restoration 🌱.

Publication Profile

Scopus

ORCID

🎓 Education Background

Li Xiaoliang earned his Doctorate in Environmental Science and Engineering (Ecology) from the prestigious China Agricultural University 🎓. He progressed from a Master’s and Doctoral program in the Department of Soil and Water Sciences between 2004 and 2010, gaining a strong foundation in environmental engineering and sustainable agriculture. As part of the EU Framework SAFIR Project, he conducted collaborative research in Denmark, focusing on low-quality water utilization and improved irrigation management 🌊🌳. His academic journey laid the groundwork for a distinguished career that blends teaching, research, and environmental stewardship across international platforms 🌍.

👔 Professional Experience

Li Xiaoliang has dedicated over two decades to teaching and research in Environmental Science and Engineering 🌱. From 2010–2012, he served in the Environmental Engineering Department of the China Environmental Management Cadre College, and from 2012 to the present, he has taught in the Environmental Science department. In 2014, he was a visiting scholar at Zhejiang University, further enriching his expertise in ecological and environmental engineering 🌊. Since 2018, he has contributed to talent introduction and academic innovation at Hebei Environmental Engineering College. Currently a Professor, he guides students and researchers in exploring sustainable technologies and addressing critical environmental challenges 🌍.

🏅 Awards and Honors

Throughout his esteemed academic and research journey, Li Xiaoliang has achieved numerous accolades 🏆. He earned the title of Professor in 2019 and serves as a CPPCC Member for Haigang District, Qinhuangdao, recognizing his service to academia and society 🌍. He has been an integral part of national and provincial research projects, including a significant role in EU SAFIR research, and has secured four invention patents and three utility model patents 🛠️. His work has been published extensively in core journals and has been cited across disciplines, cementing his reputation as a leading environmental engineering expert 🌱.

🔍 Research Focus

Li Xiaoliang’s research focuses on sustainable environmental engineering solutions for wastewater treatment, soil remediation, and ecological restoration 🌊🌱. He has conducted pivotal studies on soil microbial activity in the Bohai Bay estuary, low-carbon economic modeling for Qinhuangdao, and precision treatments for heavy metal contamination 🌳. His innovations in mobile internet teaching platforms have reshaped environmental education, making it more accessible and impactful 💻. Li’s efforts in applying diatomaceous earth and nano-TiO₂ materials for wastewater purification have inspired advances in ecological engineering, making him a significant contributor to the global environmental engineering discourse 🌍.

🌍 Conclusion

Li Xiaoliang is a highly accomplished Professor and Environmental Science and Engineering expert dedicated to addressing critical ecological challenges 🌱. Through his teaching, research, and innovations, he has shaped the future of sustainable engineering, impacting both national and global efforts in environmental conservation 🌊. An educator, researcher, and thought leader, Li’s work reflects a deep commitment to a cleaner, greener planet for future generations 🌳. His legacy shines through his impactful projects, patents, and published research, making him a beacon of excellence in the environmental engineering community 🏅🌍.

📚 Selected Top Publications with Citation Details

  1. Soil Microbial Response, Water and Nitrogen Use by Tomato under Different Irrigation Regimes. Agricultural Water Management, 98(3): 414–418. (Cited by 102)

  2. An Efficient Visual Servo Tracker for Herd Monitoring by UAV. Scientific Reports, 14(1): 10463.(Cited by 43)

  3. High-Accuracy and Low-Latency Tracker for UAVs Monitoring Tibetan Antelopes. Remote Sensing, 15(2): 417. (Cited by 39)

Mr. Idrus Jamalulel | Human Resource | Best Researcher Award

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Mr. Idrus Jamalulel | Human Resource | Best Researcher Award

PhD Student, Research Enthusiast, Chaoyang University of Technology, Indonesia.

Idrus Jamalulel is a dynamic and passionate doctoral student with a strong inclination toward human resources, technology, business, tourism, and leadership 🌐📊. His academic and professional journey is marked by a consistent commitment to organizational development, education, and digital innovation. With a vision to foster meaningful change, he aspires to build a future where education thrives alongside purpose-driven leadership 💡🎓.

Publication Profile

Scopus

Google Scholar

📘 Education Background

Idrus earned his Bachelor of Social Science degree from Universitas 17 Agustus 1945 Cirebon with an impressive GPA of 3.92/4.00 🎓🇮🇩. He further pursued a Master of Business Administration at Chaoyang University of Technology in Taiwan, graduating with a stellar GPA of 4.24/4.30 🇹🇼📚. Currently, he is undertaking his doctoral studies with a research-driven approach focused on strategic leadership and technology.

💼 Professional Experience

Idrus gained valuable experience as a Government Planning Administration Staff intern at BP4D Cirebon City in 2020, contributing to administrative tasks and regulatory compliance 🏛️📄. He also worked as a Marketing & Administration Staff for the “Desa Informasi” project, where he demonstrated excellent organizational and communication skills. In academia, he served as a Teaching Assistant for the Human Resource Management course under the EMI Program in 2024 🧑‍🏫💼. Since 2023, he has been working part-time at Hi-lai Foods Company in Taiwan as a helper and production staff 👨‍🍳📦.

🏅 Awards and Honors

His dedication has earned him several prestigious awards including the Best Paper Conference Award at the 4th International Conference on Social Sciences and Intelligence Management (SSIM) Asia in 2024 🏆📘. He was the 3rd Winner of the Indramayu District Youth PIK Video Competition in 2020 and was a semifinalist in the Top 30 of the National Outstanding Student Ambassadors in 2019 🎥🎤. His consistent achievements also include winning top positions in video, writing, and quiz competitions, and being recognized as Best Environment Mister Teen West Java in 2018 🌿🏅.

🔬 Research Focus

Idrus’s research is centered on the integration of digital leadership and technology in enhancing productivity and decision-making, particularly in sectors like hospitality and government policy 🧠💼. His recent works explore how AI and sustainable development goals (SDGs) can contribute to economic and human capital growth, with a focus on Indonesia and Taiwan.

📝 Conclusion

Driven by a passion for knowledge and innovation, Idrus Jamalulel continues to bridge the gap between theory and practice through impactful research, effective leadership, and social commitment 📈🌍. His journey exemplifies a purposeful academic and professional life, inspiring others to pursue change with vision and values.

📚 Publication Top Notes

  1. AI and Digital Leadership: Perspectives of Leaders in the Taiwan Restaurant Industry
    Authors: I. Jamalulel, A. Sihombing, P. Pahrudin
    Published in: 2024 International Conference on Computer, Control, Informatics and its Applications (IC3INA)
    Cited by: 1
    Year: 2024
    Journal/Conference: IEEE

  2. Enhancing Labor Productivity through SDG-Based Policies in Indonesia: The Role of the Manpower Office in Indramayu Regency
    Author: I. Jamalulel
    Published in: International Journal of Research and Innovation in Social Science (IJRISS), Volume 9, Issue 4
    Cited by: —
    Year: 2025
    Journal: IJRISS

 

Prof. Erping Zhao | Neural Networks | Best Researcher Award

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Prof. Erping Zhao | Neural Networks | Best Researcher Award

Master, Xizang Minzu University, China.

Erping Zhao, originally from Binxian County in Shaanxi Province, is a highly respected professor at Xizang Minzu University, where he also mentors master’s students. With a career rooted in academia and research, Dr. Zhao has emerged as a distinguished figure in the field of computer science. After earning his master’s degree in software engineering from Xidian University in 2006, he embarked on a teaching journey that has spanned nearly two decades. His academic pursuits have taken him to China Renmin University as a visiting scholar in Big Data and Knowledge Graphs. Currently, he holds several influential positions, including outstanding member of the China Computer Association, executive member of the Information System Committee, and expert evaluator in the national graduate education monitoring database.

Publication Profile

ORCID

🎓 Education Background

Dr. Zhao completed his B.S. in Computer Application from Xidian University in 1999. He later returned to the same university and earned his M.S. in Software Engineering in April 2006. His passion for continuous learning led him to further expand his research capabilities as a visiting scholar in 2016 at China Renmin University, focusing on Big Data and Knowledge Graphs.

💼 Professional Experience

Beginning his career in the industry, Erping Zhao worked at Dang Tang Telecom Co., Ltd. from 1999 to 2003. Transitioning into academia, he joined the College of Information Engineering at Xizang Minzu University in June 2006. Over the years, he has risen through the ranks to become a professor, having led multiple research projects funded by both provincial and national bodies. His leadership has been instrumental in the successful completion of Natural Science Foundation projects and key technology initiatives for Tibet.

🏆 Awards and Honors

Throughout his distinguished career, Dr. Zhao has received numerous accolades. These include the Third Prize in the Tibet Sub-Competition of the 2024 “Data Elements ×” Competition, the Xizang Autonomous Region Teaching Achievement Award, and the Xianyang Excellent Academic Paper Award. These honors reflect his commitment to both academic excellence and innovation in applied research.

🔬 Research Focus

Dr. Zhao’s research interests lie in the rapidly advancing domains of Natural Language Processing, Knowledge Graphs, Deep Learning, Intelligent Q&A and Recommendation Systems, and Large Language Models. He has made significant contributions in integrating big data analysis with knowledge representation, and his publications reflect a blend of theory and real-world applications.

🔚 Conclusion

In summary, Professor Erping Zhao stands out as a dedicated academician and accomplished researcher with profound contributions to artificial intelligence and computer science. His blend of academic insight, industrial experience, and scholarly recognition positions him as a thought leader in his field.

📚 Top Publications 

  1. A multi-head attention-based bidirectional gated recurrent unit and multilayer perceptron for relation extraction model
     2025 — Engineering Applications of Artificial Intelligence
     Cited by: 7 articles

  2. Aspect-Level Sentiment Analysis Based on Vector Projection and Adversarial Contrastive Learning
     2025 — Expert Systems with Applications
     Cited by: 4 articles

  3. A knowledge graph completion model based on weighted fusion description information and transform of the dimension and the scale
     2025 — Applied Intelligence
     Cited by: 3 articles

  4. Multi-Level Attention Based Coreference Resolution With Gated Recurrent Unit and Convolutional Neural Networks
     2023 — IEEE Access
     Cited by: 11 articles

  5. A Knowledge Graph Completion Method Based on Fusing Association Information
     2022 — IEEE Access
     Cited by: 18 articles

 

Dr. vincebt majanga | Artificial intelligence | Best Researcher Award

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Dr. vincebt majanga | Artificial intelligence | Best Researcher Award

Post doctoral research fellow, university of south africa, South Africa.

Dr. Vincent Idah Majanga  is a dynamic and passionate researcher in Artificial Intelligence (AI), with over a decade of impactful experience in developing cutting-edge algorithms to solve complex real-world problems. His primary expertise lies in machine learning, deep learning, neural network optimization, and computer vision—especially for medical imaging and diagnostic tasks. Dr. Majanga is proficient in Python and Java, and his interdisciplinary skills extend to computer-aided diagnostics, simulation and modeling, computer forensics, and networking. A devoted academician and mentor, he has served in teaching and research capacities across renowned institutions in Kenya and South Africa. His current role as a Postdoctoral Researcher at the University of South Africa (UNISA) underlines his continued contributions to AI-driven healthcare solutions and intelligent systems.

Publication Profile

ORCID

📘 Education Background

Dr. Majanga completed his Ph.D. in Computer Science from the University of KwaZulu-Natal  (2018–2022), focusing on dental image segmentation and AI-based diagnostic systems. He holds an MSc in Computer Science from the University of Nairobi (2012–2014), and a BSc in Computer Science (Upper Second Class) from Kabarak University  (2009–2011). He also studied Computer Engineering at Moi University (2005–2008, credit transferred), and attended Nairobi School for his secondary education (2001–2004). His academic foundation forms the bedrock of his AI-driven research innovations.

💼 Professional Experience

Dr. Majanga is currently a Postdoctoral Researcher at UNISA  (Dec 2023–Present), where he works on deep learning, neural networks, transfer learning, and model optimization in image processing. He is also a part-time lecturer at Masinde Muliro University of Science and Technology  since 2022. Previously, he served as an Assistant Lecturer at Laikipia University  (2015–2023), contributing to curriculum development and student supervision. He has also lectured part-time at JKUAT Nakuru Campus, Dedan Kimathi University, and Kabarak University. Across these roles, he has consistently contributed to high-impact teaching, curriculum development, and academic mentorship.

🏆 Awards and Honors

Dr. Majanga has earned recognition through certifications in Research Ethics from the Clinical Trials Centre at The University of Hong Kong 🏅, completing three modules between March and April 2024—Introduction to Research Ethics, Research Ethics Evaluation, and Informed Consent. These certifications affirm his commitment to ethical research standards and responsible conduct in AI healthcare studies.

🔬 Research Focus

Dr. Majanga’s research focuses on Artificial Intelligence applications in medical imaging and diagnostics, with a specialization in deep learning, computer vision, and unsupervised segmentation. His significant contributions include blob detection and component analysis techniques for identifying cancerous lesions and dental caries in radiographs. His Ph.D. research and publications highlight strong applications of active contour models, connected component analysis, and dropout regularization in healthcare AI systems.

📝 Conclusion

Dr. Vincent Idah Majanga is a dedicated AI researcher and academician with a rich educational and professional background that aligns with transformative applications of artificial intelligence in medical diagnostics. His teaching, ethical research approach, and cross-continental academic presence have made him a valuable contributor to the global AI and computer science communities.

📚 Top Publications Highlights

  1. Automatic Blob Detection Method for Cancerous Lesions in Unsupervised Breast Histology Images
    📅 2025 | 📰 Bioengineering, 12(4), p.364
    🔎 Cited by: 8 articles

  2. Active Contours Connected Component Analysis Segmentation Method of Cancerous Lesions in Unsupervised Breast Histology Images
    📅 2025 | 📰 Bioengineering, 12(6), p.642
    🔎 Cited by: 5 articles

  3. A Survey of Dental Caries Segmentation and Detection Techniques
    📅 2022 | 📰 The Scientific World Journal, 2022
    🔎 Cited by: 21 articles

  4. Automatic Blob Detection for Dental Caries
    📅 2021 | 📰 Applied Sciences, 11(19), p.9232
    🔎 Cited by: 17 articles

  5. Dental Images’ Segmentation Using Threshold Connected Component Analysis
    📅 2021 | 📰 Computational Intelligence and Neuroscience, 2021
    🔎 Cited by: 12 articles

  6. Dropout Regularization for Automatic Segmented Dental Images
    📅 2021 | 📰 Asian Conference on Intelligent Information and Database Systems, Springer
    🔎 Cited by: 6 articles

  7. A Deep Learning Approach for Automatic Segmentation of Dental Images
    📅 2019 | 📰 MIKE 2019, Springer
    🔎 Cited by: 18 articles

  8. Component Analysis
    📅 2025 | 📰 WIDECOM 2024, Vol. 237, p.139, Springer Nature
    🔎 Cited by: 2 articles

 

Dr. Jiaming Zhang | Engineering | Best Researcher Award

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Dr. Jiaming Zhang | Engineering | Best Researcher Award

Associate Professor, Northeast Normal University, School of Environment, China.

Dr. Jiaming Zhang is a distinguished environmental scientist known for his impactful research in advanced oxidation technologies and water treatment solutions. With a strong publication record in top-tier journals, Dr. Zhang leads a dynamic research group that focuses on innovative and practical approaches to environmental remediation. His expertise spans membrane technologies, functional material synthesis, and the control of disinfection byproducts, making him a prominent figure in environmental engineering and sustainable chemistry.

Publication Profile

Scopus

ORCID

Education Background 🎓

Dr. Zhang earned his doctoral degree in Environmental Engineering, where he specialized in chemical oxidation technologies and membrane science. His academic journey laid a robust foundation in material chemistry, catalysis, and process engineering, fueling his interdisciplinary contributions to water purification.

Professional Experience 🏢

Dr. Zhang currently leads an active research group that investigates advanced oxidation processes, including catalytic membrane cleaning and disinfection byproduct control. His team has made considerable strides in modifying membrane structures and improving contaminant removal, publishing frequently in leading journals such as Water Research, Chemical Engineering Journal, Journal of Hazardous Materials, and Journal of Membrane Science.

Awards and Honors 🏆

Over the years, Dr. Zhang’s work has earned accolades and recognitions in the form of research grants, high citation counts, and collaborative invitations from leading institutions and journals. His publications have become widely referenced in the fields of environmental and chemical engineering.

Research Focus 🔬

Dr. Zhang’s current research centers around the synthesis of environmental functional materials, membrane modification for enhanced filtration performance, and catalytic systems that effectively degrade organic contaminants. He is especially noted for his work on Co₃O₄, CuFe₂O₄-based systems, and graphene-based composite membranes, with a focus on sustainability, stability, and scale-up potential.

Conclusion 📘

With an outstanding portfolio of scholarly work and practical innovations, Dr. Jiaming Zhang continues to contribute significantly to global environmental sustainability through scientific advancements in water treatment technologies and functional material applications.

📚 Top Publications of Dr. Jiaming Zhang

  1. Catalytic degradation of bisphenol A (BPA) in water by immobilizing silver-loaded graphene oxide (GO-Ag) in ultrafiltration membrane with finger-like structure
    Journal: Chemical Engineering Journal, 2023
    Cited by: 35+ articles (Google Scholar)

  2. Insights into Co₃O₄ nano-rod/peroxymonosulfate catalytic oxidation system for chemical cleaning ultrafiltration membrane: Performance, mechanisms, and effects on the membrane stability
    Journal: Separation and Purification Technology, 2024
    Cited by: Awaiting citations – New article

  3. Treatment of shale gas produced water by magnetic CuFe₂O₄/TNTs hybrid heterogeneous catalyzed ozone: Efficiency and mechanisms
    Journal: Journal of Hazardous Materials, 2022
    Cited by: 110+ articles

  4. Enhancing the long-term separation stability of TFC membrane by the covalent bond between synthetic amino-substituted polyethersulfone substrate and polyamide layer
    Journal: Journal of Membrane Science, 2021
    Cited by: 90+ articles

  5. Organic contaminants degradation from the S(IV) autoxidation process catalyzed by ferrous-manganous ions: A noticeable Mn(III) oxidation process
    Journal: Water Research, 2018
    Cited by: 210+ articles

  6. CuO with (001)-plane exposure efficiently induces peroxymonosulfate to form ≡Cu-OOSO₃⁻ intermediates directly oxidizing organic contaminants in water
    Journal: Chemical Engineering Journal, 2022
    Cited by: 75+ articles

 

Dr. JOONSOO KIM | Digital Transformation | Best Researcher Award

Published on by Computer Scientists Awards

Dr. JOONSOO KIM | Digital Transformation | Best Researcher Award

Postdoctoral Researcher, Korea Institute of Construction Technology (KICT), South Korea.

Dr. Joon-Soo Kim is an innovative and skilled researcher in Construction Management, with a strong command of advanced data analytics, machine learning, and environmental sustainability. His academic and research work uniquely integrates engineering with cutting-edge technologies such as text mining and big data to enhance construction safety and efficiency. Currently serving as a Postdoctoral Researcher at the Korea Institute of Civil Engineering and Building Technology (KICT), Dr. Kim is highly regarded for developing reliable decision-making models tailored to complex engineering challenges. His expertise spans from eco-friendly engineering solutions to smart waste management systems, making him a vital contributor to sustainable civil engineering research. 🏗️📊🌿

Publication Profile

Scopus

🎓 Education Background

Dr. Kim earned his Ph.D. in Construction Environment and Energy Engineering from Kyungpook National University, where his dissertation explored road construction environmental load and cost estimation using machine learning. He also holds a Master’s in Construction Systems Engineering with a specialization in Geotechnical and Road Engineering, and a Bachelor’s degree in Civil Engineering—all from the same university. His academic path reflects a strong commitment to applying data-driven insights to real-world infrastructure problems. 🎓📚

💼 Professional Experience

Dr. Kim is currently a Postdoctoral Researcher at KICT, contributing to advancements in civil infrastructure and environmental solutions. Prior to this, he worked at the Intelligent Construction Automation Research Center, Kyungpook National University, for over three years. He also shared his expertise as a lecturer at Daegu University, teaching courses such as Basic Statistics and Construction Management. His combined academic and field experience empowers him to lead high-impact research in civil engineering. 🏢👨‍🏫

🏅 Awards and Honors

Dr. Kim holds registered intellectual property rights, including a software-based Construction Waste Information Management (CWIM) system using QR codes (2023), and a patented Eco-Friendly Value Engineering Decision Analysis System (Patent No. 10-1745567, registered in 2017). These innovations underscore his commitment to enhancing efficiency and sustainability in construction engineering through smart technologies. 🏆📜💡

🔍 Research Focus

Dr. Kim’s primary research areas include construction safety, environmental load management, and project efficiency, with a strong focus on big data, machine learning, and geospatial analysis. He specializes in Value Engineering (VE), Life Cycle Assessment (LCA), and advanced image processing techniques like YOLO for object detection. His multidisciplinary approach supports disaster prevention and promotes green building practices. 🔎🌱📈

📘 Conclusion

Combining strong academic foundations with hands-on innovation, Dr. Joon-Soo Kim continues to make significant strides in the civil and construction engineering fields. His work not only enhances safety and environmental responsibility but also sets a benchmark in leveraging AI-driven methodologies for engineering problem-solving. 👏🌐🚧

📚 Top Publications with 

  1. Image Processing and QR Code Application Method for Construction Safety Management
    Kim, J.-S., Yi, C.-Y., & Park, Y.-J., 2021, Applied Sciences
    📑 Cited by: 18 articles (as per Google Scholar)

  2. Impact Evaluation of Water Footprint on Stages of Drainage Works
    Chen Di, Kim, J.-S., Batagalle V., & Kim, B.-S., 2020, Journal of the Korean Society of Civil Engineers
    📑 Cited by: 6 articles

  3. Characteristics Analysis of Seasonal Construction Site Fall Accident using Text Mining
    Kim, J.-S., & Kim, B.-S., 2019, Journal of the Korea Institute of Construction Engineering and Management
    📑 Cited by: 11 articles

  4. Analysis of the Environmental Load Impact Factors for IPC Girder Bridge Using PCA
    Kim, J.-S., Jeon, J.-G., & Kim, B.-S., 2018, Journal of the Korea Institute of Construction Engineering and Management
    📑 Cited by: 9 articles

  5. Analysis of Fire-Accident Factors Using Big-Data in Construction Areas
    Kim, J.-S., & Kim, B.-S., 2017, KSCE Journal of Civil Engineering
    📑 Cited by: 34 articles

  6. Eco-Friendly Design Evaluation Model Using PEI for Construction Facilities
    Kim, J.-S., & Kim, B.-S., 2017, Journal of the Korean Society of Civil Engineers
    📑 Cited by: 10 articles

  7. Definition of Environmental Cost and Eco-VE Model for Construction Facility
    Kim, M.-J., Kim, J.-S., & Kim, B.-S., 2016, Journal of the Korean Society of Civil Engineers
    📑 Cited by: 7 articles

  8. A Proposal of NIA Model for Eco VE Decision of Construction Facilities
    Kim, J.-S., & Kim, B.-S., 2015, Journal of the Korean Society of Civil Engineers
    📑 Cited by: 12 articles

 

Dr. Raihan ur Rasool | Resource management | Best Researcher Award

Published on by Computer Scientists Awards

Dr. Raihan ur Rasool | Resource management | Best Researcher Award

Senior Architect/ Quantum Ambassador, IBM Australia; Victoria University, Australia.

Raihan ur Rasool is a seasoned technology leader, currently serving as a Senior Solution Architect and Quantum Ambassador at IBM Australia, while also contributing academically as a Ph.D. supervisor and Advisory Board Member at Victoria University, Melbourne. With over 20 years of combined experience in academia and industry, he has established himself as a notable expert in hybrid cloud computing, distributed systems, and quantum technologies. His impactful innovations in cloud scheduling, big data analytics, and energy-efficient VM distribution have been widely acknowledged and cited across research communities. 🧠💻🌐

Publication Profile

ORCID
Scopus
Google Scholar

📘 Education Background

Raihan ur Rasool holds advanced degrees in Computer Science and Engineering, reflecting a strong academic foundation that supports his expertise in distributed computing and secure network systems. His academic training paved the way for his early involvement in both innovative research projects and cutting-edge industrial applications. 🎓📚

💼 Professional Experience

Professionally, Raihan has held several prominent positions in tech innovation. At IBM, he plays a critical role as a Quantum Ambassador, leading research and outreach in quantum computing technologies. His affiliation with Victoria University allows him to mentor Ph.D. students and contribute to strategic academic decisions. His collaborations with renowned scholars like Ian Foster and Andrew Chien from the University of Chicago, and Hua Wang from Victoria University, speak to his influential standing in the global research landscape. 🏢🔬🌍

🏆 Awards and Honors

His scholarly impact is underscored by an h-index of 21, and a publication record of over 80 papers, with around 50 published in reputed journals including IEEE, Elsevier, and Springer. His contributions have earned industry and academic recognition, and he is also a published author (ISBN: 1466697679). 📖🥇

🔬 Research Focus

Raihan’s research spans across distributed systems, network security, big data analytics, IoT, quantum computing, and software-defined networking. His work is known for its practical implications in disaster management, healthcare systems, and cloud infrastructure, often integrating AI and machine learning techniques for optimized system performance. 🔐📊☁️

✅ Conclusion

Raihan ur Rasool is a distinguished researcher and technology innovator whose work bridges the gap between academic theory and industrial application. His leadership in emerging areas like quantum computing and 6G-enabled healthcare analytics positions him as a top contender for recognition in international research awards. 🌟🚀🧬

📚 Top Publications with Notes

  1. Leveraging 6G, extended reality, and IoT big data analytics for healthcare: A review
    Cited by: 15+
    An in-depth review of futuristic healthcare systems combining 6G, XR, and IoT analytics.

  2. Quantum Computing for Healthcare: A Review
    Cited by: 20+
    Explores the potential of quantum technologies in transforming healthcare delivery and diagnostics.

  3. A multi-objective grey-wolf optimization based approach for scheduling on cloud platforms
    Cited by: 5+
    Proposes a novel cloud scheduler improving resource allocation using grey-wolf optimization.

  4. A Hybrid Machine Learning Model for Efficient XML Parsing
    Cited by: 3+
    Introduces a hybrid ML model for faster and more efficient XML parsing in data-heavy applications.

  5. CyberPulse++: A machine learning‐based security framework for detecting link flooding attacks in software defined networks
    Cited by: 30+
    Presents a robust cybersecurity framework for SDNs using ML-driven detection.

  6. Big data analytics enhanced healthcare systems: a review
    Cited by: 100+
    Highly cited work evaluating big data’s role in healthcare innovations.

  7. Complementing IoT Services through Software Defined Networking and Edge Computing: A Comprehensive Survey
    Cited by: 120+
    Recognized for detailing SDN and edge computing synergies for IoT applications.

  8. Feature Selection Optimization in Software Product Lines
    Cited by: 50+
    Improves product line configuration through optimization-based feature selection.

  9. A survey of link flooding attacks in software defined network ecosystems
    Cited by: 80+
    An authoritative survey of LFA threats and countermeasures in SDN environments.

  10. Cyberpulse: A Machine Learning Based Link Flooding Attack Mitigation System for Software Defined Networks
    Cited by: 60+
    ML-based real-time solution for detecting and mitigating LFA in SDN systems.