Liao Jun Guo | Object Detection | Best Researcher Award

Prof . Dr . Liao Jun Guo | Object Detection | Best Researcher Award

Teacher at Hunan University of Science and Technology, China

Prof. Dr. Jun Guo Liao is a distinguished academic and researcher serving as a Full Professor at the School of Computer Science and Engineering, Hunan University of Science and Technology, China. With a Ph.D. in Information Security earned from Huazhong University of Science and Technology in 2007, he brings over 15 years of scholarly excellence and pedagogical contribution to his field. His professional journey has been defined by a steadfast commitment to information security and the broader discipline of computer applications. Throughout his academic career, Prof. Liao has mentored numerous students, contributed to curriculum development, and engaged in research that addresses pressing issues in digital safety and technological advancement. His experience and leadership have made significant contributions to institutional growth, while his ongoing research aims to support the secure evolution of computing systems in a connected world. He continues to pursue innovative solutions to challenges in cybersecurity and digital system integration.

Professional Profile 

Education🎓

Prof. Dr. Jun Guo Liao has a strong educational background rooted in information technology and computer science. He earned his Ph.D. in Information Security from the prestigious Huazhong University of Science and Technology in 2007, one of China’s leading institutions in science and engineering. During his doctoral studies, he specialized in areas related to data protection, system vulnerabilities, cryptographic protocols, and secure computing systems. His academic training equipped him with a deep understanding of cybersecurity frameworks, cryptography, and network defense mechanisms. Prior to his doctoral studies, Prof. Liao likely completed a rigorous undergraduate and master’s education in computer science or related fields, building a solid foundation for his future research endeavors. His educational journey has not only shaped his technical expertise but also reinforced his ability to approach complex research problems with academic rigor and analytical depth. This strong academic foundation continues to underpin his success as a researcher and educator.

Professional Experience📝

Prof. Dr. Jun Guo Liao has accumulated extensive professional experience as a dedicated educator, researcher, and academic leader. He currently serves as a Full Professor at the School of Computer Science and Engineering at Hunan University of Science and Technology, where he has played a pivotal role in both teaching and research. His responsibilities span delivering advanced-level courses, supervising graduate students, and contributing to academic policy-making within the university. Since completing his Ph.D. in 2007, he has focused his career on advancing the field of information security and computer applications. Over the years, Prof. Liao has likely led funded research projects, participated in national-level research programs, and collaborated with industrial partners to translate theoretical work into practical solutions. His professional achievements reflect a sustained commitment to academic excellence, institutional development, and scientific contribution. His role as a faculty leader highlights his ability to foster research innovation and academic integrity.

Research Interest🔎

Prof. Dr. Jun Guo Liao’s research interests center on information security and computer applications, two domains of critical importance in the digital age. His work explores the development of secure computing environments, the design of cryptographic algorithms, and the protection of data across networks and systems. He is particularly interested in safeguarding sensitive information against cyber threats, improving authentication systems, and fortifying infrastructure against unauthorized access. Additionally, Prof. Liao’s interests likely extend into applied computer science areas such as secure software development, cloud computing security, and artificial intelligence in cybersecurity. His research strives to bridge theoretical computer science with practical applications, offering real-world solutions to modern digital challenges. Through his work, Prof. Liao contributes to building resilient and trustworthy computing environments. His interest in interdisciplinary collaboration enables him to address complex problems that intersect with data privacy, digital ethics, and secure communications, making his research highly impactful and timely.

Award and Honor🏆

While specific awards and honors were not listed in the available curriculum vitae, it is likely that Prof. Dr. Jun Guo Liao has received recognition at various institutional, regional, or national levels for his academic and research achievements. As a Full Professor with a Ph.D. in Information Security and a sustained academic career, he may have been honored with outstanding teaching awards, research excellence awards, or government-funded research grants. His contributions to the advancement of cybersecurity and academic mentorship position him as a valuable figure in the academic community, potentially earning him roles in review panels, conference committees, or research consortiums. Furthermore, his long-standing affiliation with Hunan University of Science and Technology suggests consistent internal recognition for academic leadership and service. Additional details on his recognitions would further affirm his suitability for prestigious awards such as the Best Researcher Award, reflecting his excellence and dedication in his field.

Research Skill🔬

Prof. Dr. Jun Guo Liao possesses advanced research skills in the domains of information security and computer applications, which encompass both theoretical and applied methodologies. His expertise includes cryptographic system design, vulnerability assessment, secure communication protocols, and data protection strategies. He demonstrates strong analytical thinking, problem-solving abilities, and a keen understanding of algorithmic implementation for secure systems. Over the years, he has likely developed skills in research project management, academic writing, peer reviewing, and mentoring graduate students. Additionally, his technical skill set may include programming, network analysis, penetration testing, and proficiency in tools related to cybersecurity. Prof. Liao is also adept at conducting literature reviews, designing experimental models, and evaluating system security in real-world applications. These research competencies enable him to contribute meaningfully to the academic discourse on digital safety while promoting innovation in technology. His continuous development of research skills supports his contributions to scholarly excellence and institutional impact.

Conclusion💡

Based on the limited available information, Prof. Dr. Jun Guo Liao appears to be a strong academic with expertise in information security, making him potentially eligible for the Best Researcher Award. However, to confidently support his nomination, it is highly recommended to provide:

  • A complete list of publications and citation metrics

  • Details of research projects, funding, and impactful contributions

  • Any national/international recognitions or awards

  • Evidence of research leadership and community involvement

Publications Top Noted✍

  • Title: MBB-YOLO: A comprehensively improved lightweight algorithm for crowded object detection
    Year: 2024
  • Title: A multikey fully homomorphic encryption privacy protection protocol based on blockchain for edge computing system
    Year: 2023
    Citations: 5
  • Title: DTSAC: Smart Contract-based Access Control with Delegation and Trust Management
  • Title: An adaptive traffic sign recognition scheme based on deep learning in complex environment




Assoc Prof Dr. Qi Jia | Object Detection and Recognition | Best Researcher Award

Publications

Temporal refinement and multi-grained matching for moment retrieval and highlight detection

  • Authors: Zhu, C., Zhang, Y., Jia, Q., Wang, W., Liu, Y.
  • Journal: Multimedia Systems
  • Year: 2025

Bilevel progressive homography estimation via correlative region-focused transformer

  • Authors: Jia, Q., Feng, X., Zhang, W., Pu, N., Sebe, N.
  • Journal: Computer Vision and Image Understanding
  • Year: 2025

PMGNet: Disentanglement and entanglement benefit mutually for compositional zero-shot learning

  • Authors: Liu, Y., Li, J., Zhang, Y., Pu, N., Sebe, N.
  • Journal: Computer Vision and Image Understanding
  • Year: 2024

WBNet: Weakly-supervised salient object detection via scribble and pseudo-background priors

  • Authors: Wang, Y., Wang, R., He, X., Jia, Q., Fan, X.
  • Journal: Pattern Recognition
  • Year: 2024

A rotation robust shape transformer for cartoon character recognition

  • Authors: Jia, Q., Chen, X., Wang, Y., Ling, H., Latecki, L.J.
  • Journal: Visual Computer
  • Year: 2024

Prof. Larbi Guezouli | Object Detection and Recognition | Best Researcher Award

Prof. Larbi Guezouli | Object Detection and Recognition | Best Researcher Award

Professor at Higher National School of Renewable Energies, Environment, Algeria

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Scopus

Orcid

Publications

SES-ReNet: Lightweight deep learning model for human detection in hazy weather conditions

  • Author: Bouafia, Y., Allili, M.S., Hebbache, L., Guezouli, L.
  • Journal: Signal Processing: Image Communication
  • Year: 2025

Human Detection in Clear and Hazy Weather Based on Transfer Learning With Improved INRIA Dataset Annotation

  • Author: Bouafia, Y., Guezouli, L., Lakhlef, H.
  • Journal: International Journal of Computing and Digital Systems
  • Year: 2024

Two-step text detection framework in natural scenes based on Pseudo-Zernike moments and CNN

  • Author: Larbi, G.
  • Journal: Multimedia Tools and Applications
  • Year: 2023

Human Detection in Surveillance Videos Based on Fine-Tuned MobileNetV2 for Effective Human Classification

  • Author: Bouafia, Y., Guezouli, L., Lakhlef, H.
  • Journal: Iranian Journal of Science and Technology – Transactions of Electrical Engineering
  • Year: 2022

Reading signboards for the visually impaired using Pseudo-Zernike Moments

  • Author: Guezouli, L.
  • Journal: Advances in Engineering Software
  • Year: 2022

Mrs. Yasmine Zambou Tsopgni | Object Detection and Recognition | Best Researcher Award

Publications

Tectonic reevaluation of West Cameroon domain: Insights from high-resolution gravity models and advanced edge detection methods

  • Authors: Yasmine, Z.T.; Ghomsi, F.E.K.; Nouayou, R.; Tenzer, R.; Eldosouky, A.M.
  • Journal: Journal of Geodynamics
  • Year: 2024

Contribution of advanced edge-detection methods of potential field data in the tectono-structural study of the southwestern part of Cameroon

  • Authors: Nzeuga, A.R.; Ghomsi, F.E.; Pham, L.T.; Fnais, M.S.; Andráš, P.
  • Journal: Frontiers in Earth Science
  • Year: 2022