Xiaopeng Han | Computer Science | Best Industrial Research Award

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Dr. Xiaopeng Han | Computer Science | Best Industrial Research Award

Researcher at Purple Mountain Laboratories, China

Dr. Xiaopeng Han is a dedicated researcher currently serving as an Assistant Research Fellow at the Endogenous Security Research Center, Purple Mountain Laboratories. With a strong foundation in photogrammetry, remote sensing, and cyber-physical systems security, Dr. Han bridges geospatial technology and security innovation. His career has been marked by a blend of academic rigor and real-world application, particularly in the fields of high-resolution remote sensing image interpretation and network security. Over the past few years, he has contributed to numerous national and provincial research projects, including high-value initiatives like the National Key R&D Program and the Jiangsu Province Doctoral Innovation Program. Dr. Han has also played pivotal roles in multi-disciplinary collaborative research, publishing extensively in leading international journals. Notably, his work integrates machine learning, deep learning, and sensor network control with applications in smart cities and industrial cybersecurity. Through his academic endeavors and contributions to national strategy documents and patents, he has established himself as a well-rounded scientist pushing the boundaries of both remote sensing and cybersecurity. His robust profile and consistent academic engagement reflect a passion for scientific innovation, talent cultivation, and technological transformation.

Profile

ORCID

Education

Dr. Xiaopeng Han began his academic journey at Central South University, where he pursued a Bachelor of Engineering in Surveying and Mapping Engineering from September 2010 to June 2014. This program provided him with a solid grounding in geospatial science, data acquisition, and engineering applications. Motivated by a desire to further specialize, he continued his education at Wuhan University—one of China’s leading institutions in the field of photogrammetry and remote sensing—where he earned a Ph.D. between September 2014 and June 2019. His doctoral studies involved deep analytical work in remote sensing technologies, image classification, and environmental modeling. During this time, he developed a strong foundation in high-resolution image analysis and multi-source data fusion, skills that have been integral to his subsequent research. The academic rigor and innovative environment at Wuhan University equipped Dr. Han with the tools to thrive in cross-disciplinary research areas, paving the way for his transition into more security-focused technological research. Though he has not pursued postdoctoral studies, his educational background has enabled him to take on high-impact research roles in both academic and industry-aligned settings, bridging theory with practice.

Professional Experience

Dr. Xiaopeng Han’s professional journey reflects a well-rounded progression from industry roles to academic research positions. From July 2019 to July 2022, he worked as an Engineer in the System Research Department at the 14th Research Institute of China Electronics Technology Group Corporation (CETC). Here, he engaged in research and development activities focused on system integration, high-tech innovations, and security frameworks. This experience grounded his technical knowledge in practical, large-scale applications, particularly in cybersecurity systems and smart infrastructure. Since July 2022, Dr. Han has been serving as an Assistant Research Fellow at the Endogenous Security Research Center of Purple Mountain Laboratories. In this role, he has continued his work on network security, remote sensing, and data-driven system optimization. His professional portfolio includes collaborations on significant national projects, involving cutting-edge topics such as semi-supervised learning for remote sensing and cloud-edge industrial security technologies. He has also led and participated in provincial-level and talent development programs. These experiences have allowed him to blend the rigor of academic research with the urgency of real-world problem-solving. Dr. Han’s current position enables him to mentor junior researchers, drive innovative studies, and contribute to China’s evolving cybersecurity and geospatial technology landscapes.

Research Interest

Dr. Xiaopeng Han’s research interests span across multiple interdisciplinary domains, with a strong emphasis on high-resolution remote sensing, intelligent image interpretation, urban spatial analysis, and cybersecurity systems. His early academic work focused on photogrammetry and remote sensing, particularly in developing frameworks for image classification and environmental modeling using machine learning. Over time, his research evolved to address more complex challenges in smart city planning, environmental monitoring, and urban morphology analysis. Recently, Dr. Han has concentrated on cybersecurity, especially in relation to cloud-edge industrial systems and the development of endogenous security strategies. He is particularly interested in semi-supervised learning approaches for pixel-to-scene image interpretation, which allows for greater precision in automated data processing. Additionally, he investigates the application of artificial intelligence and deep learning in both remote sensing and network threat detection systems. His integrative research perspective allows him to develop solutions that link earth observation data with national defense and network security concerns. This convergence of disciplines places him at the forefront of innovation, where data science meets geospatial intelligence and cyber-physical security.

Research Skills

Dr. Xiaopeng Han possesses a diverse and advanced skill set, positioning him as a key contributor in both geospatial and cybersecurity research. His core competencies include high-resolution remote sensing image processing, data fusion techniques, and machine learning-based image classification methods. He is proficient in implementing multi-classifier learning frameworks that preserve edge features in complex remote sensing data. Beyond remote sensing, Dr. Han is also skilled in designing resilient control strategies for mobile sensor networks under adversarial conditions, including input delay and Sybil attacks. His work often involves semi-supervised and sparse representation learning, reflecting his deep understanding of AI model optimization for real-world scenarios. Furthermore, he has experience developing system-level threat detection and risk assessment methodologies, which are crucial for next-generation industrial and smart grid environments. His skills extend into software programming and system modeling, making him capable of conducting end-to-end experimentation and algorithm development. With the ability to cross traditional disciplinary boundaries, Dr. Han brings computational, analytical, and theoretical expertise to the table, supported by practical engagement in multi-million-yuan national and provincial projects. His research capabilities are complemented by his familiarity with cutting-edge platforms and security protocols in cloud-edge computing environments.

Awards and Honors

Dr. Xiaopeng Han has received several prestigious recognitions that underscore his academic excellence and innovative contributions. One of his most notable honors is the inclusion in the Jiangsu Province Dual-Innovation Doctoral Talent Program, administered by the Jiangsu Provincial Organization Department in 2020. This competitive award recognizes outstanding researchers with strong potential for innovation and industrial transformation. In addition to this award, Dr. Han has contributed to a wide range of patent filings, showcasing his applied research impact. These include patented methods for system security assessment, network threat detection, and 3D object reconstruction, among others. Many of these inventions are co-authored with leading experts in cybersecurity and have been registered both domestically in China and internationally through WIPO. He has also participated in high-profile conferences such as the IEEE ICTC 2024, interacting with global scholars and presenting breakthrough ideas. Dr. Han’s involvement in major strategy white papers, such as the “Cybersecurity Strategy and Technology Trends” released at the 2024 China Endogenous Security Conference, further cements his role as a thought leader. Collectively, these accolades reflect his dedication to blending theoretical research with practical solutions that address critical societal challenges.

Publications

Dr. Xiaopeng Han has a strong portfolio of publications in internationally renowned journals, reflecting his diverse research interests and collaborative capabilities. His most cited work includes “The edge-preservation multi-classifier relearning framework for the classification of high-resolution remotely sensed imagery” published in ISPRS Journal of Photogrammetry and Remote Sensing, which highlights novel classification methods for remote sensing images. He has also co-authored a pivotal study in Environmental Pollution analyzing the relationship between urban noise and city morphology, showcasing his engagement with real-world urban analytics. In the journal Land Degradation & Development, his contribution to monitoring ecosystem services in Shenzhen using deep learning and satellite imagery stands out as a key interdisciplinary application. More recently, Dr. Han has contributed to work on resilient control in sensor networks published in the International Journal of Applied Mathematics and Computer Science, reflecting his shift toward cybersecurity topics. Alongside journal articles, he has presented at major conferences like ICTC 2024 and authored multiple patents related to network threat detection and smart system security. His publication record demonstrates a continuous trajectory of innovation across different yet interlinked domains, with a focus on impactful research that bridges environmental science and cyber defense.

Conclusion

Dr. Xiaopeng Han is an accomplished researcher whose expertise lies at the intersection of geospatial science and cybersecurity. With an academic background rooted in photogrammetry and remote sensing, he has expanded his research to cover pressing issues in smart urban systems and industrial network security. His career trajectory—from an engineer in a national research institute to an Assistant Research Fellow at a premier lab—illustrates both his technical depth and upward professional mobility. Dr. Han has been entrusted with critical roles in high-value R&D projects, and his contributions are recognized through prestigious awards, patents, and scholarly publications. He actively contributes to scientific advancement not only through innovative research but also by participating in national policy formulation and knowledge dissemination. His ability to bridge disciplines and integrate theoretical and applied science makes him a unique asset in both academic and industrial settings. As he continues to explore new frontiers in semi-supervised learning, cyber-physical systems, and intelligent remote sensing, Dr. Han remains a driving force in shaping the future of integrated technology solutions. His work stands as a testament to rigorous scholarship aligned with real-world impact.

Fatih Kalemkuş | Artificial Intelligence | Best Researcher Award

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Assist. Prof. Dr. Fatih Kalemkuş | Artificial Intelligence | Best Researcher Award

Assistant Professor at Kafkas University, Turkey

Dr. Fatih Kalemkuş is an Assistant Professor at Kafkas University, where he specializes in Electronic Commerce and Technology Management. With a rich academic and professional background, Dr. Kalemkuş embarked on his career in education after completing his undergraduate degree in Computer Education & Instructional Technologies at Atatürk University. He has taught various subjects related to information technology, first as an Informatics Technologies Teacher at the Turkish Ministry of National Education and later as a lecturer at Kafkas University’s Distance Education Application and Research Center. His journey culminated in earning a doctoral degree from Fırat University in Computer Education & Instructional Technologies, where he was honored with the “Most Successful Doctoral Thesis” award in 2024.

Profile

Orcid

Education

Dr. Kalemkuş’s educational journey began at Erzincan Fatih Industrial Vocational High School, where he pursued studies in the Computer Department. He continued to develop his academic career by earning his bachelor’s degree in 2006 from Atatürk University in the field of Computer Education & Instructional Technologies. He then completed a Master’s degree in Internet and Informatics Technologies Management from Afyon Kocatepe University between 2014 and 2016. His dedication to advancing his knowledge in the field led him to pursue a Ph.D. at Fırat University, graduating in 2023 with a focus on Computer Education & Instructional Technologies. His research has been instrumental in advancing educational practices in the digital age, with a specific focus on artificial intelligence and emerging technologies.

Experience

Dr. Kalemkuş has had diverse professional experiences. From 2007 to 2021, he served as an Informatics Technologies Teacher under the Turkish Ministry of National Education, shaping the next generation’s skills in information technology. In 2021, he joined Kafkas University as a lecturer at the Distance Education Application and Research Center, where he taught courses related to digital learning tools. His commitment to academic excellence and innovation in education led to his promotion to Assistant Professor in 2024 at Kafkas University’s Electronic Commerce and Technology Management Department, where he continues to make impactful contributions to research and education.

Research Interests

Dr. Kalemkuş’s research focuses on key areas of educational technology and digital transformation. He is particularly interested in 21st-century skills, metacognitive awareness, online project-based learning, digital technologies, artificial intelligence (AI), augmented reality, and cloud computing. He also explores the intersection of education and emerging technologies, such as natural language processing (NLP) and the integration of AI in educational contexts. His work aims to improve learning outcomes and foster innovation in teaching methodologies. His ongoing research projects delve into the development of AI-driven educational materials and interactive learning environments that enhance students’ academic engagement.

Awards

Dr. Kalemkuş has received recognition for his outstanding academic contributions. In 2024, he was honored with the prestigious “Most Successful Doctoral Thesis” award from Fırat University for his exceptional research and academic achievements. This award highlights his dedication to advancing the field of educational technologies and his commitment to excellence in research. His work, particularly on the use of AI in education, has positioned him as a leading researcher in his field.

Publications

Dr. Kalemkuş has authored several influential publications in well-regarded journals and books. His research has been featured in leading SSCI and ESCI journals, including the European Journal of Education, Interactive Learning Environments, Science & Education, and Journal of Research in Special Educational Needs. His recent publications include:

Kalemkuş, F., & Kalemkuş, J. (2025). “Primary School Students’ Perceptions of Artificial Intelligence: Metaphor and Drawing Analysis”, European Journal of Education, 60(1), 1-23.

Kalemkuş, F., & Bulut-Özek, M. (2024). “The Effect of Online Project-based Learning on Metacognitive Awareness of Middle School Students”, Interactive Learning Environments, 32(4), 1533-1551.

Kalemkuş, F., & Kalemkuş, J. (2024). “The Effect of Designing Scientific Experiments with Visual Programming on Learning Outcomes”, Science & Education, 1-23.

Kalemkuş, F., & Bulut-Özek, M. (2023). “Effect of the Use of Augmented Reality Applications on Academic Achievement in Science Education: Meta Analysis”, Interactive Learning Environments, 31(9), 6017-6034.

Kalemkuş, F. (2024). “Trends in Instructional Technologies Used in Education for People with Special Needs Due to Intellectual Disabilities and Autism”, Journal of Research in Special Educational Needs, 1-25.

Kalemkuş, F., & Çelik, L. (2023). “Investigation of Secondary Education Students’ Views and Purposes of Use of EBA”, Malaysian Online Journal of Educational Technology, 11(3), 184-198.

Kalemkuş, F., & Bulut-Özek, M. (2021). “Research Trends in 21st Century Skills: 2000-2020”, MANAS Sosyal Araştırmalar Dergisi, 10(2), 878-900.

Conclusion

Dr. Fatih Kalemkuş’s career has been marked by a profound commitment to advancing educational technology and promoting the use of emerging technologies in learning environments. With numerous publications in prestigious journals and books, he has made a significant impact on the fields of AI, digital learning, and 21st-century skills development. His work continues to shape the educational landscape, particularly in the integration of innovative digital tools to enhance teaching and learning outcomes. Dr. Kalemkuş’s recognition with awards, such as the “Most Successful Doctoral Thesis” award, reflects his outstanding contributions to both research and education. His interdisciplinary approach ensures that his work will remain at the forefront of educational innovations for years to come.

Jamal Raiyn | Deep Learning | Best Researcher Award

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Prof. Dr. Jamal Raiyn | Deep Learning | Best Researcher Award

Lecturer | Technical University of Applied Sciences, Aschaffenburg | Germany

Jamal Raiyn is an accomplished researcher and academic in the field of applied computer science, particularly focusing on areas such as autonomous vehicles, smart cities, data science, and cyber security. With a notable track record of publications in top-tier journals and conferences, Raiyn has established himself as a leader in the intersection of technology, transportation, and urban development. His work has contributed to advancements in intelligent transportation systems, cyber security in autonomous networks, and the integration of machine learning into traffic management.

Profile

Google Scholar

Education

Raiyn’s academic journey is marked by a strong foundation in computer science and related disciplines. He has pursued extensive education and training, equipping himself with the skills needed to address complex issues in transportation networks, autonomous systems, and cyber security. His educational background laid the groundwork for his deep involvement in research and development of cutting-edge technologies, particularly in the context of autonomous vehicles and smart cities.

Experience

Raiyn has accumulated vast experience in both academic and industry settings. Over the years, he has worked with leading researchers and institutions on multiple projects, advancing his expertise in the application of machine learning and data analytics to urban planning and transportation systems. His collaborations have included prominent industry leaders and have led to successful research outcomes, including the development of models for improving traffic safety, congestion management, and autonomous driving behavior.

Research Interests

Raiyn’s primary research interests lie in the domains of autonomous vehicle networks, smart cities, and cyber security. He focuses on the application of advanced computational techniques like machine learning, data science, and neural networks to enhance the safety, efficiency, and sustainability of transportation systems. Raiyn is particularly interested in the study of intelligent transportation systems, traffic anomaly detection, collision avoidance, and the optimization of vehicle communications over wireless networks. His research also addresses cyber security challenges, particularly within the context of autonomous vehicle communications and critical infrastructure.

Awards

Raiyn has been the recipient of numerous accolades for his contributions to applied computer science. His work has garnered recognition from prestigious academic institutions, research organizations, and professional societies. Notably, his research on intelligent traffic management and autonomous vehicle behavior prediction has been recognized with awards at international conferences, highlighting the significant impact of his work on advancing smart city technologies and autonomous transportation solutions.

Publications

Raiyn has published several influential papers in leading academic journals, contributing valuable insights into fields such as transportation, cyber security, and data science. Some of his notable publications include:

Raiyn, J., & Weidl, G. (2025). “Improvement of Collision Avoidance in Cut-In Maneuvers Using Time-to-Collision Metrics.” Smart Cities.

Raiyn, J., Chaar, M. M., & Weidl, G. (2025). “Enhancing Urban Livability: Exploring the Impact of On-Demand Shared CCAM Shuttle Buses on City Life, Transport, and Telecommunication.”

Raiyn, J., & Weidl, G. (2024). “Predicting Autonomous Driving Behavior through Human Factor Considerations in Safety-Critical Events.” Smart Cities, 7(1), 460-474.

Raiyn, J. (2024). “Maritime Cyber-Attacks Detection Based on a Convolutional Neural Network.” Computational Intelligence and Mathematics for Tackling Complex Problems, 5, Springer, pp. 115-122.

Raiyn, J., & Rayan, A. (2023). “Identifying Safety-Critical Events in Data from Naturalistic Driving Studies.” International Journal of Simulation Systems, Science & Technology, 24(1).

Raiyn, J. (2022). “Detection of Road Traffic Anomalies Based on Computational Data Science.” Discover Internet of Things, 2(6).

Raiyn, J. (2022). “Using Dynamic Market-Based Control for Real-Time Intelligent Speed Adaptation Road Networks.” Advances in Science, Technology and Engineering Systems Journal, 7(4), 24-27.

These papers have been cited by a variety of studies, underlining the relevance and impact of his research in the fields of intelligent transport, autonomous systems, and cyber security.

Conclusion

Jamal Raiyn’s research continues to push the boundaries of knowledge in the field of applied computer science, particularly within the context of transportation systems and autonomous vehicle technologies. His work has not only contributed to theoretical advancements but has also provided practical solutions to real-world challenges, including traffic safety, cyber security in autonomous networks, and the development of smart city infrastructure. Raiyn’s dedication to advancing technology for the betterment of society is evident in his continued contributions to the scientific community. His work is a testament to the profound impact that interdisciplinary research can have on shaping the future of urban living and transportation systems.