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

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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

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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.

 

Dr. Yuxiang Leng | Electrical engineering | Best Researcher Award

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Dr. Yuxiang Leng | Electrical engineering | Best Researcher Award

Ph.D, Chongqing University, China

Yuxiang Leng is an emerging researcher in the field of 3D laser point cloud technology and power transmission systems. He is currently pursuing his Ph.D. at the State Key Laboratory of Power Transmission Equipment Technology, Chongqing University, China. With a strong academic background and an innovative mindset, Leng has actively contributed to the advancement of computer vision applications in power systems. He has published eight academic papers and presented his work at high-level international conferences, gaining recognition in both academia and industry for his contributions to smart grid technologies and engineering digitalization.

Publication Profile

Scopus

🎓 Education Background:

Yuxiang Leng earned his B.Sc. degree from Jiangsu University of Science and Technology in 2019 and his M.S. degree from Wenzhou University in 2022. He is currently a Ph.D. candidate at Chongqing University, focusing on advanced research in the digital management of power substations using 3D vision and laser scanning methods. His educational path reflects a consistent pursuit of excellence in engineering and technology.

💼 Professional Experience:

Though still in the early stages of his research career, Yuxiang has shown remarkable productivity. He has been actively involved in eight research projects and has taken a lead role in multiple academic studies. His technical work centers around developing high-precision measurement techniques and improving data accuracy in laser-based 3D reconstruction. While he has not yet been involved in consultancy or editorial positions, his practical approach and novel methodologies have already earned him significant attention in academic forums.

🏅 Awards and Honors:

While specific awards are not listed, Yuxiang’s recognition as a leading contributor to peer-reviewed SCI/EI journals, including being the first author in three high-impact publications, underlines his academic excellence. Additionally, his oral presentations at top-tier international conferences have positioned him as a rising talent in power equipment digitalization. His selection as an IEEE Student Member further reflects his commitment to research and innovation.

🔬 Research Focus:

Yuxiang’s research lies at the intersection of 3D computer vision, laser point cloud data analysis, and power transmission and transformation systems. His most notable contribution involves a dynamic compensation method that significantly reduces vibration-induced errors in 3D point cloud data, enhancing segmentation and reconstruction precision by over 70%. His work not only advances digital twin modeling but also supports smart maintenance, monitoring, and intelligent management of electrical substations.

🔚 Conclusion:

Yuxiang Leng stands out as a dynamic and promising young researcher whose innovative solutions are driving the future of power system digitalization. With a strong publication record, hands-on project experience, and a clear research vision, he is a fitting candidate for the Best Researcher Award. His blend of academic rigor and practical innovation ensures a meaningful impact in the realm of intelligent power grid technology.

📚 Top Publications of Yuxiang Leng

  1. Dynamic compensation approach for mitigating vibration interference in 3D point cloud data of electrical equipment
    Published: 2025
    Journal: Advanced Engineering Informatics
    Cited by: 3 articles

  2. Intelligent Early Warning System for Power Operation Safety Based on Laser Point Cloud Sensing
    Published: 2024
    Conference Paper: International Conference on Smart Energy Systems
    Cited by: 2 articles

  3. LoRaWAN Network Downlink Routing Control Strategy Based on the SDN Framework and Improved ARIMA Model
    Published: 2023
    Journal: Journal of Communications and Networks
    Cited by: 1 article

  4. Contactless Voltage Measurement Considering Spatially Dependent Voltage Compensation
    Published: 2023
    Conference Proceedings: IEEE Power & Energy Society Meeting
    Cited by: 0 articles

 

Assist. Prof. Dr. Chung-Hao Huang | Microwave antenna | Best Researcher Award

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Assist. Prof. Dr. Chung-Hao Huang | Microwave antenna | Best Researcher Award

Assistant Professor, Department of Electrical Engineering/ Chung Yuan Christian University, Taiwan.

Dr. Chung-Hao Huang is an Assistant Professor at the Department of Electrical Engineering, Chung Yuan Christian University, Taiwan, since August 2022. With a passion for cutting-edge technological innovation, Dr. Huang integrates 5G antenna systems, artificial intelligence, and immersive multimedia into his research and teaching. His expertise spans digital learning, mixed reality applications, and smart technologies, contributing actively to both academia and industry through collaborative projects and international events. 🧠📡🎓

Publication Profile

ORCID

🎓 Education Background

Dr. Huang earned his Ph.D. from the Engineering and Technology Research Institute at the National Yunlin University of Science and Technology. His academic journey laid the foundation for his later innovations in antenna design and immersive technology. His strong educational background supports his diverse skill set in emerging technologies and engineering disciplines. 📘🎓

💼 Professional Experience

Before joining academia, Dr. Huang served as an Assistant Engineer at the Institute of Nuclear Energy Research under Taiwan’s Atomic Energy Council from October 2011 to July 2022. There, he contributed significantly to the development of remote-controlled robotic arms and AR-based navigation systems for nuclear decommissioning. Since 2022, at Chung Yuan Christian University, he has led advanced projects on AI-based antenna optimization, heat-dissipative antenna arrays, and metaverse applications in robotics training. 🧑‍🏫🔧🤖

🏅 Awards and Honors

Dr. Huang has been recognized for his leadership in organizing international seminars and industry-university collaborations. Though specific honors were not listed, his work as a principal investigator and frequent conference host reflects his active and respected role in the engineering research community. 🏆🌐

🔍 Research Focus

Dr. Huang’s research focuses on 5G antenna design, RF passive component optimization, digital learning environments, and immersive multimedia such as VR/AR/MR. He also explores the application of artificial intelligence in technical design and educational systems, contributing to smarter, more responsive systems in both academia and industry. His interdisciplinary expertise enables innovation across hardware and software interfaces. 📡🧠🌍

🔚 Conclusion

Dr. Chung-Hao Huang stands at the forefront of technological advancement, blending theoretical rigor with practical implementation. His multifaceted background and commitment to intelligent systems make him a valuable contributor to the future of engineering and digital transformation. 🚀📘💡

📄 Top Publication Note

Title: Design of Laptop Computer Antenna for Wi-Fi 6E Band
Authors: Chung-Hao Huang, Ying-Chao Hong, Sen-Yu Liao, Yi-Chi Chen
Published in: Engineering Proceedings, Year: 2025
DOI: 10.3390/engproc2025092095

Mr. Nikolaos Bouzianis | Medical Physics | Best Researcher Award

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Mr. Nikolaos Bouzianis | Medical Physics | Best Researcher Award

Medical Physicist, P.G.N. Alexandroupolis, Greece.

Nikolaos Bouzianis is a dedicated Medical Physicist and Ph.D. candidate at the Democritus University of Thrace, School of Medicine. With a strong academic foundation in medical physics and hands-on clinical experience in nuclear medicine, Nikolaos has continuously demonstrated a passion for applying advanced technologies—particularly artificial intelligence—to optimize diagnostic imaging and patient care. He holds national certifications as a Medical Physics Expert and Radiation Protection Expert, highlighting his commitment to excellence and safety in medical environments.

Publication Profile

ORCID

🎓 Education Background

Nikolaos is currently pursuing a Ph.D. in Medical Physics (2023–Present) at the Democritus University of Thrace, where his research focuses on leveraging AI algorithms to enhance practices in nuclear medicine. He earned his Master’s degree in Medical Physics (2015–2017) from the University of Patras with an “Excellent” distinction for his thesis on HDL image classification via application development. He also holds a Bachelor’s degree in Physics (2007–2015) from the same university, where he specialized in electronics, computers, and signal processing.

🧪 Professional Experience

Since January 2021, Nikolaos has been working as a Medical Physicist at the University General Hospital of Alexandroupolis, applying his knowledge in clinical settings. He also completed a residency as a Medical Physicist at the University General Hospital of Patras from November 2018 to October 2019. His roles have equipped him with practical exposure to diagnostic imaging, radiation safety, and computational medical physics applications.

🏅 Awards and Honors

Nikolaos holds multiple professional certifications, including a license to practice as a Hospital Physicist in both ionizing and non-ionizing radiation fields. He is recognized as a Certified Medical Physics Expert and Radiation Protection Expert. These honors reflect his high competency level and his respected status in the field of medical physics.

🔬 Research Focus

Nikolaos’s primary research interests lie at the intersection of artificial intelligence and nuclear medicine. His Ph.D. work explores how AI algorithms can optimize existing medical practices, focusing especially on enhancing the quality of scintigraphic imaging while reducing radiation dose. His work exemplifies innovation in digital medical technology, particularly through the use of convolutional autoencoders and advanced image processing techniques.

🔚 Conclusion

With a blend of academic rigor, clinical experience, and a tech-forward mindset, Nikolaos Bouzianis stands out as a promising figure in the field of medical physics. His contributions to AI-based solutions in nuclear medicine aim to redefine diagnostic standards and improve patient outcomes, positioning him as a valuable asset to both research and healthcare communities.

📚 Publication Top Notes

🔹 Title: Dose Reduction in Scintigraphic Imaging Through Enhanced Convolutional Autoencoder-Based Denoising
🔹 Journal: J. Imaging
🔹 Year: 2025
🔹 Volume/Issue: 11(6), Article 197
🔹 Cited by: 2 articles (as per current indexing)

Mr. Xiang Fang | Ransomware detection | Best Researcher Award

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Mr. Xiang Fang | Ransomware detection | Best Researcher Award

Phd student, The City College of New York, United States.

Xiang Fang is a dedicated and technically proficient researcher in electrical and computer engineering, currently pursuing his Ph.D. at The City College of New York. With a multifaceted background combining hardware, software, cybersecurity, and AI-powered applications, Xiang stands out for his innovative approaches to problem-solving, especially in areas like control systems, image processing, and ransomware detection. His contributions span multiple international presentations, academic projects, and scholarly publications, reflecting a deep passion for research and a commitment to academic excellence. 🌍🔬

Publication Profile

Google Scholar

🎓Education Background

Xiang earned his Ph.D. in Electrical Engineering from The City College of New York (2020–2025), maintaining an impressive GPA of 3.60. Complementing his technical expertise, he acquired an MBA from Academic Europe Open University in April 2025, equipping him with valuable leadership and management skills. His journey began with an M.Sc. in Electrical and Computer Engineering from Purdue University Northwest (2017–2019), followed by a B.Sc. in Electrical and Information Engineering from Shaanxi University of Technology, China (2013–2017). 🎓📘📈

💼Professional Experience

Xiang has actively contributed to academia through teaching assistantships and tutoring roles. At The City College of New York, he worked as a Teaching Assistant for Healthcare Cybersecurity Pathways (2023) and graded Communication Theory (2025). His earlier experience includes tutoring English to middle school students (2013–2014). In research, he has led and contributed to multiple technical projects—ranging from digital image enhancement and SLAM systems to cloud-based secure applications and real-time ransomware detection using anomaly-based methods. 💡🖥️🧪

🏅Awards and Honors

Xiang’s commitment to excellence is reflected in his achievements, including the Certificate of Completion in Children and Climate Change, and the CodePath Cybersecurity Course Certificate. His research has been widely recognized through poster presentations at prestigious forums such as AFRL-CUNY, The Grove School of Engineering Expo, and the Defense & Intelligence Research Forum. 🏆📜🎖️

🔍Research Focus

Xiang’s primary research interests lie in cybersecurity, autonomous systems, signal processing, and AI-powered detection systems. His standout contributions include anomaly-based and honeyfile-based detection mechanisms for crypto ransomware, SLAM systems, and data visualization methods. Leveraging tools like MATLAB, Python, Kalman filters, and machine learning models such as LSTM, Xiang effectively bridges theoretical concepts with practical implementations. 🔐🤖📊

🔚Conclusion

A forward-thinking and results-driven scholar, Xiang Fang exemplifies the blend of innovation, technical acumen, and academic rigor. His trajectory, from hands-on hardware projects to advanced research in digital security, positions him as a rising star in the field of electrical and computer engineering. As he continues his journey, Xiang remains committed to tackling emerging global challenges with smart, scalable, and secure solutions. 🚀📡🌐

📚Top Publications Notes

  1. Crypto-Ransomware Detection Through a Honeyfile-Based Approach with R-Locker
    📅 Published: 2025 | 📘 Journal: MDPI, Mathematics | 📑 Cited by: 5 articles (as of 2025)

  2. Poster: Crypto Ransomware Detection Through a Honeyfile-Based Approach with R-Locker
    📅 Presented: Feb. 2025 | 📍 The Grove School of Engineering Expo, NY, USA

  3. Poster: Anomaly-Based Approach for Crypto Ransomware Detection
    📅 Presented: Nov. 2023 | 📍 AFRL-CUNY Technology and Workforce Development Forum

  4. Poster: Ransomware Detection Methodology
    📅 Presented: May 2022 | 📍 Defense & Intelligence Research Forum, NY, USA

  5. Thesis: Visualization of Mobile Robot Localization and Mapping
    📅 Published: April 2017 | 📍 Purdue University Northwest

  6. Thesis: Design of High-Precision Laser Engraving Platform Control System Based on STC12C5608AD
    📅 Published: June 2017 | 📍 Shaanxi University of Technology

 

Dr. XueHua Zhao | Automation | Best Researcher Award

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Dr. XueHua Zhao | Automation | Best Researcher Award

Student, Northwestern Polytechnical University, China.

Dr. XueHua Zhao 🎓 is a dedicated Chinese researcher specializing in advanced filtering algorithms, sensor networks, and non-Gaussian noise modeling. With a strong mathematical foundation and a focus on artificial intelligence in navigation systems, Dr. Zhao has published several impactful research papers in top-tier international journals and conferences. Currently pursuing a Ph.D. in Computer Science and Technology at Northwestern Polytechnical University, her contributions to maximum correntropy filtering and its distributed applications are widely recognized across the control engineering community 🌐.

Publication Profile

Scopus

📘 Education Background

Dr. Zhao began her academic journey with a Bachelor’s degree in Mathematics Education from Henan Normal University (1998–2002) 🧮. She then pursued a Master’s degree in Computational Mathematics at Guizhou Normal University (2004–2006) 📊. Continuing her academic advancement, she embarked on doctoral research in Computer Science and Technology at Northwestern Polytechnical University from 2016 onwards 🖥️, focusing on advanced estimation and filtering techniques.

💼 Professional Experience

With a foundation in mathematics and applied computing, Dr. Zhao has actively contributed to the scientific community through collaborative projects in signal processing and navigation systems 🚀. She has co-authored papers with experts in both academic and industrial research groups, focusing on algorithms like the Unscented Particle Filter and Sparrow Search Algorithm, highlighting her interdisciplinary approach and engineering insight 🤝.

🏅 Awards and Honors

While specific individual awards have not been explicitly mentioned, Dr. Zhao’s selection as a lead author in several high-impact journals and IEEE conferences reflects peer recognition and commendation from the academic community 🌟. Her work has drawn citations from related research in robust control, navigation systems, and sensor networks 🏆.

🔬 Research Focus

Dr. Zhao’s research interests lie at the intersection of control engineering and computational intelligence 🧠. She focuses on robust estimation methods like the Maximum Correntropy Kalman Filter (MCKF), Rational-Quadratic Kernels, and Particle Filtering under non-Gaussian and censored environments. Her work is crucial in advancing INS/GPS integrated navigation, distributed sensor fusion, and optimization algorithms for real-world uncertainty modeling and adaptive control systems 🔍.

🔚 Conclusion

Dr. XueHua Zhao continues to make meaningful contributions to control theory and intelligent filtering under uncertainty. Her deep mathematical insight, algorithmic innovation, and collaborative research spirit position her as a valuable contributor to global advancements in nonlinear filtering and smart navigation technologies 🌐📈.

📚 Publication Top Notes:

  1. Stochastic Stability of the Improved Maximum Correntropy Kalman Filter against Non-Gaussian Noises, International Journal of Control, Automation and Systems, 2024, 22(3): 731–743.
    Cited by: 6 articles

  2. Rational-Quadratic Kernel-Based Maximum Correntropy Kalman Filter for the Non-Gaussian Noises, Journal of the Franklin Institute, 2024, 361(17): 107286.
    Cited by: 4 articles

  3. Distributed Maximum Correntropy Linear Filter Based on Rational-Quadratic-kernel against Non-Gaussian Noise, Symmetry, 2025 (in press).
    Cited by: Awaiting citation

  4. A Fading Factor Unscented Particle Filter and Its Application in INS/GPS Integrated Navigation, ICISCE 2017 Proceedings, IEEE, 2017: 792–796.
    Cited by: 19 articles

  5. Adaptive Robust Unscented Particle Filter and Its Application in Sins/Sar Integration Navigation System, IAEAC 2017 Proceedings, IEEE, 2017: 2364–2368.
    Cited by: 21 articles

  6. Enhanced Sparrow Search Algorithm Based on Improved Game Predatory Mechanism and Its Application, Digital Signal Processing, 2024, 145: 104310.
    Cited by: 5 articles

  7. Linear and Nonlinear Filters Based on Statistical Similarity Measure for Sensor Network Systems, Journal of the Franklin Institute, 2025, 362(1): 107412.
    Cited by: Awaiting citation

  8. Random weighted adaptive filtering and its application in integrated navigation , Journal of Projectiles, Rockets, Missiles and Guidance , 2017 , 37(05): 1–5+10.
    Cited by: 12 articles

 

Mr. Abdullah Al Mamun | Deep Learning | Young Scientist Award

Posted on by Computer Scientists Awards

Mr. Abdullah Al Mamun | Deep Learning | Young Scientist Award

Lecturer, Dhaka University of Engineering & Technology (DUET), Gazipur, Bangladesh

Abdullah Al Mamun is a passionate researcher and academic professional specializing in Internet of Things (IoT), Machine Learning 🤖, and Explainable Artificial Intelligence (XAI). Currently pursuing his Master of Science in Engineering at Dhaka University of Engineering & Technology (DUET), Gazipur, he brings a vibrant combination of theoretical knowledge and hands-on research experience. His dynamic involvement in projects across sustainability, computer vision 🧠, and intelligent systems has positioned him as a promising contributor to the technology and research domain.

Publication Profile

ORCID

🎓 Education Background

Abdullah Al Mamun is presently pursuing his M.Sc. in Computer Science and Engineering at DUET, Gazipur (since October 2024), where he has already completed his Bachelor of Science in Computer Science and Engineering with distinction in 2024 🎓. His consistent academic journey showcases his dedication to computing, innovation, and advanced research.

💼 Professional Experience

Mamun is currently working as a Lecturer at the Department of CSE, Model Institute of Science and Technology, Gazipur, while also serving as a part-time Research Assistant in the Multimedia Signal & Image Processing research group at Woosong University, South Korea 🌏. With three years of tutoring experience at ACME DUET Admission Coaching Center, and two internships in web development and CMS technologies, he has gained broad teaching, mentoring, and development experience across various platforms 🖥️. His administrative roles in DUET Career & Research Club and DUET Computer Society also underscore his leadership and community contributions.

🏆 Awards and Honors

Abdullah has been recognized for his academic and problem-solving excellence. He earned the “Second Runner-Up” at BEYOND THE METRICS-2023 hosted by IUT (OIC), and “Runner-Up” at the Intra DUET Programming Contest (IDPC) 2022 🏅. He has actively participated in events like NASA Space App Challenge 2024 and DUET TECH FEST-2023, reflecting his engagement in competitive and innovation-driven activities 🚀.

🔬 Research Focus

Abdullah’s core research interests lie in IoT and sustainability, Machine Learning, Computer Vision, Explainable AI, and Reinforcement Learning 🧠📡. He has been instrumental in implementing real-world projects such as IoT-based energy monitoring systems and child safety monitoring, defect detection via XAI, and skin cancer classification using optimized deep learning models. His collaborative projects with global research teams exhibit his strong contribution to the evolving field of intelligent systems and digital transformation.

✅ Conclusion

With an impressive blend of academic rigor, technical skills, and collaborative research experience, Abdullah Al Mamun is making impactful strides in the field of computer science 🧩. His work exemplifies innovation, sustainability, and intelligence in engineering systems. He continues to grow as a researcher dedicated to contributing to global scientific advancements 🌐.

📚 Top Publications 

  1. Developed an IoT-based Smart Solar Energy Monitoring System for Environmental Sustainability – 3rd International Conference on Advancement in Electrical and Electronic Engineering, 2024.
    Cited by: 7 articles 📑

  2. Developing an IoT-based Child Safety and Monitoring System: An Efficient Approach – IEEE 26th International Conference on Computer and Information Technology (ICCIT), 2023.
    Cited by: 13 articles 🔐

  3. Software Defects Identification: Results Using Machine Learning and Explainable Artificial Intelligence Techniques – IEEE Journal, 2024.
    Cited by: 15 articles ⚙️

  4. IoT-Based Solutions for Uneven Roads and Balanced Vehicle Systems Using YOLOv8 – MDPI Sensors Journal, 2023.
    Cited by: 10 articles 🚗

  5. Optimizing Deep Learning for Skin Cancer Classification: A Computationally Efficient CNN – 2nd NCIM Conference, Bangladesh, 2024.
    Cited by: 5 articles 🧬

  6. Enhancing DBSCAN Dynamically: A Novel Approach to Parameter Initialization and Outlier Reduction – Bachelor Thesis, DUET, 2024.
    Cited by: 3 articles 🔍