Lilei Sun | Artificial intelligence | Best Researcher Award | 13305

Published on by Research Awards

Assist. Prof. Dr. Lilei Sun | Artificial intelligence | Best Researcher Award 

Assist. Prof. Dr. Lilei Sun, Guizhou Minzu University, China

Prof. Dr. Lilei Sun is an associate professor at Guizhou Minzu University, China, specializing in deep learning, image processing, pattern recognition, and medical image processing. He completed his B.E. in computer technology in 2016 and obtained his Ph.D. in software engineering in 2022, both from Guizhou University, Guiyang. Dr. Sun’s research focuses on incomplete multi-view clustering and has led to notable contributions in academic publications, including 10 articles in prestigious journals. He serves as an associate editor for the International Journal of Image and Graphics and is actively involved in collaborative research projects.

Profile

Orcid

🌱 Early Academic Pursuits

Prof. Dr. Lilei Sun began his academic journey with a solid foundation in computer technology. He received his B.E. degree in Computer Technology from Guizhou University in Guiyang, China, in 2016. This laid the groundwork for his advanced studies in software engineering, a field that has had a significant impact on his subsequent research. His academic excellence and curiosity drove him to pursue a Ph.D. in Software Engineering from Guizhou University, which he successfully completed in 2022. Throughout his academic journey, he consistently demonstrated a deep passion for understanding the intricacies of deep learning, image processing, and pattern recognition, as well as their transformative potential in medical image processing. 🌟

🔬 Professional Endeavors and Contributions

Since 2024, Prof. Dr. Sun has been serving as an Associate Professor at Guizhou Minzu University, where he has made notable strides in both teaching and research. In his role, he mentors students and collaborates with fellow researchers on projects that explore cutting-edge technologies in deep learning and image processing. His contributions to the academic community extend beyond the classroom as he actively participates in various consultancy projects and industry collaborations, applying his research to real-world problems. Dr. Sun’s work has led to practical innovations in the fields of medical image processing and pattern recognition, areas that are increasingly critical for advancing healthcare solutions globally. 🏥

💡 Research Focus

Prof. Dr. Sun’s research interests revolve around deep learning, image processing, pattern recognition, and medical image processing. One of his key areas of focus is incomplete multi-view clustering, a method that enables more accurate data analysis in scenarios where information is incomplete or fragmented. This has potential applications in various fields, including healthcare, where the integration of multi-source medical data can lead to better diagnostic models and more personalized treatments. Additionally, his work on medical image processing leverages machine learning techniques to enhance the quality and accuracy of medical imaging, providing practitioners with more reliable diagnostic tools. The potential to save lives and improve healthcare outcomes makes this research both significant and timely. 🔍

🏆 Accolades and Recognition

Prof. Dr. Sun has garnered recognition for his dedication to both teaching and research. He has published 10 academic articles, many of which have been featured in respected journals indexed by SCI and Scopus. He is also an associate editor of the International Journal of Image and Graphics, a prestigious journal that underscores his expertise in the field. His work has earned him an esteemed position in the academic community, further enhanced by his ongoing contributions to industry projects and collaborations. Through his research, Prof. Dr. Sun has received significant acknowledgment from his peers, with numerous invitations to speak at international conferences and collaborate with experts from various research institutes globally. 🌍

🌟 Impact and Influence

Prof. Dr. Sun’s work has had a profound impact on the fields of image processing and medical image processing. His research on deep learning and pattern recognition has contributed to advancements in the way medical data is processed, interpreted, and used in clinical decision-making. His innovations are poised to help healthcare providers access more accurate, timely, and comprehensive information, ultimately leading to improved patient outcomes. Furthermore, his involvement in professional memberships and editorial boards for various scientific journals has allowed him to influence the direction of research in his areas of expertise. 📊

💫 Legacy and Future Contributions

As Prof. Dr. Sun continues his research journey, his legacy is beginning to take shape through his groundbreaking contributions to deep learning and medical image processing. His passion for exploring innovative solutions to real-world challenges, particularly in healthcare, positions him as a leader in his field. In the coming years, Prof. Dr. Sun aims to push the boundaries of incomplete multi-view clustering, further developing techniques that can be applied across multiple domains, including medical diagnostics, artificial intelligence, and big data analytics. His commitment to excellence in research, teaching, and mentorship will continue to inspire future generations of students and researchers.

Publications Top Notes

Dual structure-aware consensus graph learning for incomplete multi-view clustering

Contributors: Lilei Sun; Wai Keung Wong; Yusen Fu; Jie Wen; Mu Li; Yuwu Lu; Lunke Fei
Journal: Pattern Recognition
Year: 2025

Balance guided incomplete multi-view spectral clustering

Contributors: Lilei Sun; Jie Wen; Chengliang Liu; Lunke Fei; Lusi Li
Journal: Neural Networks
Year: 2023

Two‐view attention‐guided convolutional neural network for mammographic image classification

Contributors: Lilei Sun; Jie Wen; Junqian Wang; Yong Zhao; Bob Zhang; Jian Wu; Yong Xu
Journal: CAAI Transactions on Intelligence Technology
Year: 2023

Nadeem Zaidkilani | Artificial Intelligence | Cutting-edge Technology Research Award | 13255

Published on by Research Awards

Mr. Nadeem Zaidkilani | Artificial Intelligence | Cutting-edge Technology Research Award 

Mr. Nadeem Zaidkilani, University Rovira i Virgili, Spain

Mr. Nadeem Zaidkilani is a Ph.D. student in the Doctoral Program in Computer Engineering and Mathematics at the University Rovira i Virgili (URV), Spain. His research focuses on computer vision and medical image analysis, leveraging deep learning techniques to enhance automated diagnostic systems. With a strong background in software engineering and artificial intelligence, he has extensive experience in text mining, natural language processing, and biomedical data analysis. His work integrates advanced machine learning methodologies with practical applications in healthcare and technology.

Profile

Scopus

🎓 Early Academic Pursuits

Nadeem Zaidkilani embarked on his academic journey with a passion for computer science, earning his Bachelor’s degree in Computer Science from Birzeit University in 2005. His thirst for knowledge and drive for excellence led him to further his studies, culminating in a Master’s degree in Software Engineering from the same institution in 2019. During his master’s, he honed his expertise in requirements engineering, business analysis, software design, and other fundamental software engineering disciplines. His thesis on Automatic Classification of Apps Reviews for Requirement Engineering provided significant insights into customer needs in healthcare applications, demonstrating his analytical skills and research prowess.

Currently, Nadeem is pursuing a Ph.D. at URV University in Spain, specializing in Computer Vision for Medical Image Analysis. His research integrates deep learning, image processing, and natural language processing (NLP) to develop advanced solutions in medical imaging.

💼 Professional Endeavors

Throughout his career, Nadeem has gained extensive experience in various roles, each contributing to his growth as a seasoned software engineer, researcher, and educator.

🌟 Part-Time Lecturer at Al-Zaytoonah University of Science and Technology (2024–Present)

Nadeem’s teaching portfolio includes courses in Python, C++, and Human-Computer Interaction (HCI). His expertise extends to Agile and Scrum methodologies, emphasizing collaborative design, iterative feedback, and efficient software development cycles. His commitment to academia ensures that students receive industry-relevant knowledge and skills.

🧪 Text Mining Engineer (2023–2024)

Nadeem played a pivotal role in a biomedical research project, leveraging text mining to streamline the classification of PubMed literature. His contributions included:

  • Text Classification: Implementing advanced algorithms to categorize biomedical research papers.
  • Entity Relationship Mapping: Utilizing INDRA to identify connections between biomedical entities.
  • Workflow Development: Designing a student-teacher analogy model, where experts guide AI-driven literature analysis.

🛠️ Senior Application Specialist at Paltel (2012–2022)

In this role, Nadeem managed and optimized multiple business applications, ensuring seamless integration and high efficiency. Key projects included:

  • Paltel Portal & Business Portal: Facilitating customer and corporate service management.
  • Electronic Document Management System (EDMS): Enhancing document storage and retrieval processes.
  • E-Pay System: Implementing a secure electronic payment solution.
  • Vendor Management System (VMS): Streamlining vendor relations.
  • Bulk and Pull SMS System: Enhancing customer communication strategies.

🏆 Senior Software Developer at Hulul Company (2009–2012)

Nadeem worked on network provisioning, donor management systems, and document archiving while implementing Agile methodologies. His experience with Struts 2, JEE, HTML, and JavaScript strengthened his software development capabilities.

📝 IT Manager at Ministry of Finance (2007–2009)

As an IT manager, he successfully led projects within budget and time constraints, ensuring efficient system analysis, testing, and quality assurance.

📚 Junior Java Developer & Software Engineer Roles (2005–2007)

Nadeem contributed to the Palestinian Authority Tax Administration Computer System (PATACS), implementing J2EE-based solutions. His training in Spain on J2EE and XML web services further solidified his technical foundation.

📚 Contributions and Research Focus

Nadeem’s research is centered on deep learning, computer vision, and medical image analysis. His ongoing Ph.D. work aims to revolutionize medical imaging techniques by integrating AI-driven models. His past research efforts in text mining for biomedical literature and software requirement engineering have also contributed valuable insights to their respective fields.

🏅 Accolades and Recognition

Nadeem’s expertise has earned him recognition across academic and professional spheres. His extensive contributions to biomedical text mining, software engineering, and AI-driven medical imaging have established him as an innovator in the field. He has collaborated with leading experts and institutions, further solidifying his influence in software development and research.

Publication Top Notes

CoAtUNet: A symmetric encoder-decoder with hybrid transformers for semantic segmentation of breast ultrasound images

Author: N., Zaidkilani, Nadeem, M.Á., García, Miguel Ángel, D.S., Puig, Domenec Savi

Journal: Neurocomputing, 

Year: 2025