Yanxia Liang | Computer Science | Research Excellence Award

Yanxia Liang | Computer Science | Research Excellence Award

西安邮电大学 | China

Dr. Yanxia Liang is a distinguished researcher and associate professor whose work advances the fields of communication engineering and intelligent information processing. She serves at the Shaanxi Key Laboratory of Information Communication Network and Security and the School of Communication and Information Engineering at Xi’an University of Posts and Telecommunications, where she contributes to both academic research and graduate mentorship. Her expertise spans interference management, radio resource management, and information compression within mobile communication systems, with a particular emphasis on improving the efficiency, reliability, and adaptability of next-generation networks. With a strong background in clustering algorithms, K-means optimization, cluster-head selection, image processing, and advanced compression techniques—including discrete cosine transform, entropy coding, and lossless compression—she has established a diverse research profile bridging theory and practical applications. Her work on imaging data processing, compression ratio optimization, and the design of robust image compression algorithms contributes to the development of faster, more bandwidth-efficient communication technologies. Across her career, she has authored numerous studies that integrate signal processing, resource allocation strategies, and intelligent algorithmic frameworks to address modern challenges in wireless communication environments. She is also engaged in exploring emerging trends in mobile communication systems, aiming to enhance system performance through improved data handling and reduced interference. Her contributions support the broader evolution of smart communication infrastructures, including applications in multimedia transmission, network optimization, and secure information exchange. Recognized for her interdisciplinary approach, Yanxia Liang continues to advance research that connects communication theory with real-world technological demands, making her a vital contributor to the scientific community working toward more efficient and intelligent communication networks.

Profile: Scopus

Featured Publications

Liang, Y., Sun, C., Jiang, J., Liu, X., He, H., & Xie, Y. (2020). An efficiency-improved clustering algorithm based on KNN under ultra-dense network. IEEE Access, 8. IEEE.

Liang, Y., Zhao, S., Liu, X., He, H., Zhao, X., & Wang, H. (2024). A balanced energy-efficient clustering strategy for WSNs. IEEE Sensors Journal, 24(22). IEEE.

He, H., Liang, Y., & Li, S. (2021). Clustering algorithm based on azimuth in mmWave massive MIMO–NOMA system. In 2021 IEEE/CIC International Conference on Communications in China (ICCC Workshops). IEEE.

Liang, Y., Liu, X., Jiang, J., Du, J., Sun, C., & Xie, Y. (2020). A practical dynamic clustering scheme using spectral clustering in ultra-dense network. In 2020 IEEE/CIC International Conference on Communications in China (ICCC Workshops). IEEE.

Liang, Y., Jia, T., Li, N., Liu, X., Jiang, J., Lu, G., & Zhao, M. (2024). Review of static image compression algorithms. In 2024 IEEE 7th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). IEEE.

Liu, X., & Liang, Y. (2021). A novel Moore–Penrose-inverse-matrix-based data compression method. In 2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT). IEEE.

Xiaohang Zhao | Computer Science | Best Researcher Award

Xiaohang Zhao | Computer Science | Best Researcher Award

Dr. Xiaohang Zhao, Changchun Institute of Optics, Fine Mechanics and Physics, China

Xiaohang Zhao is a dedicated Ph.D. candidate in Mechatronic Engineering at the University of Chinese Academy of Sciences (UCAS), affiliated with the esteemed Changchun Institute of Optics, Fine Mechanics and Physics. His research emphasizes cutting-edge infrared imaging and remote sensing technologies, particularly for spaceborne applications. Zhao has demonstrated his scientific innovation through multiple first-author publications in high-impact SCI-indexed journals and the successful filing of four patents. His work addresses critical challenges in image quality, including low-light enhancement, stripe noise removal, and blind deblurring. In addition to his academic research, Zhao has contributed to major national defense projects such as the DXX infrared grating camera and the Geological-1 satellite imaging system. With strong expertise in algorithm development, FPGA hardware design, and detector-driven imaging techniques, he actively explores real-time enhancement solutions in space-based imaging. Zhao combines theoretical rigor with practical engineering, aiming to advance China’s capabilities in aerospace and remote sensing.

Publication Profile

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🎓 Education

Xiaohang Zhao earned his Bachelor of Science degree in Electronic Information Science and Technology from Northeast Normal University, where he gained a strong foundation in signal processing, circuit design, and embedded systems. Following his undergraduate studies, he was admitted to the University of Chinese Academy of Sciences (UCAS) for doctoral research in Mechatronic Engineering, joining the prestigious Changchun Institute of Optics, Fine Mechanics and Physics. At UCAS, Zhao has been engaged in advanced courses and research in optical engineering, infrared imaging, sensor data processing, and mechatronic system design. His academic training includes deep exploration of atmospheric scattering models, hardware-software co-design, and scientific programming for large-scale image processing. Under expert supervision, Zhao continues to sharpen his knowledge through national defense-oriented projects and interdisciplinary collaborations, setting a strong foundation for a future in cutting-edge imaging technology, especially focused on spaceborne and defense-related optical systems.

💼 Experience

Xiaohang Zhao is currently a Ph.D. researcher at the Changchun Institute of Optics, Fine Mechanics and Physics, part of the Chinese Academy of Sciences. His professional work spans both algorithm design and hardware implementation for remote sensing applications. He has developed and implemented advanced image processing techniques—including low-light image enhancement, blind deblurring, and stripe noise removal—for real-time space-based imaging systems. Zhao’s experience includes active involvement in defense and aerospace projects such as the DXX infrared grating camera and the Geological-1 satellite imaging mission. He has also contributed to real-world imaging system development using FPGA platforms, ensuring high-efficiency hardware acceleration. His engineering approach combines deep algorithmic insight with system-level design, detector calibration, and embedded optimization. Zhao has collaborated with multidisciplinary teams, integrating sensor data with advanced image enhancement pipelines and ensuring compliance with strict aerospace-grade performance and reliability standards.

🏆 Honors and Awards

Xiaohang Zhao has been recognized for his outstanding research contributions in infrared and remote sensing imaging with several accolades. His innovative work has led to 4 authorized patents in the field of image enhancement and spaceborne imaging algorithms. He is the first author of 5 SCI-indexed journal articles, including publications in high-impact platforms such as IEEE Sensors Journal and Remote Sensing. His academic excellence earned him multiple research scholarships and commendations from the University of Chinese Academy of Sciences. Zhao has also been selected for participation in key national defense projects, highlighting the practical relevance and strategic importance of his research. His commitment to bridging theoretical development with real-world applications has been recognized through internal awards from the Changchun Institute of Optics for innovation in imaging system design and deployment. These honors underscore his growing reputation in the field of high-performance imaging and optical engineering.

🔬 Research Focus

Xiaohang Zhao’s research centers on infrared and remote sensing image enhancement, with a particular focus on spaceborne systems. His work addresses fundamental challenges in low-light image enhancement, blind deblurring, stripe noise removal, and non-uniform illumination compensation, essential for high-precision satellite and defense imaging. He specializes in image quality enhancement algorithms that are tightly coupled with detector characteristics, enabling real-time implementation through FPGA-based hardware acceleration. Zhao also develops atmospheric scattering models to refine image clarity under complex environmental conditions. His technical portfolio includes detector-driven algorithm optimization, real-time enhancement, and noise-resilient imaging techniques suitable for remote and harsh space environments. Zhao’s applied research contributes directly to national defense projects, including the DXX infrared grating camera and Geological-1 satellite imaging, positioning him as a critical contributor to China’s aerospace imaging capabilities. His future goals include advancing autonomous onboard image correction systems for next-generation satellites.

📚 Publications

  • 📄 Low-Light Image Enhancement Based on Retinex and Adaptive Histogram Equalization for Spaceborne Systems

  • 📄 Stripe Noise Removal in Infrared Images via Dual-Domain Sparse Coding

  • 📄 Blind Image Deblurring for Remote Sensing Using Deep Prior and Motion Estimation

  • 📄 Real-Time FPGA Implementation of Image Enhancement Algorithms for Onboard Satellite Processing

  • 📄 Infrared Image Restoration under Atmospheric Scattering Conditions with Physics-Based Modeling

Samia Haouassi | Computer Science | Best Researcher Award

Samia Haouassi | Computer Science | Best Researcher Award

Samia Haouassi, Dalian university of technology, Algeria

Samia Haouassi is a dedicated researcher in Computer Science, specializing in image processing and intelligent systems. Originating from Khenchela, Algeria, she has pursued an international academic journey that reflects her passion for technology and cross-cultural collaboration. Samia earned her Bachelor’s and Master’s degrees from Constantine University 2, Algeria, before moving to China for her PhD at Dalian University of Technology. Her multilingual abilities in Arabic, French, English, and Chinese have allowed her to navigate academic and multicultural environments with ease. She is well-regarded for her strong communication and organizational skills, demonstrated by leading cultural exchange events and mentoring peers. Samia’s research contributions span image dehazing, iris recognition, and control systems. Beyond academics, she is actively involved in promoting cultural diversity and academic collaboration. With a foundation in both theory and practical applications, she aims to contribute meaningfully to the development of intelligent computer systems and global scientific advancement.

Publication Profile

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Education

Samia Haouassi’s academic journey showcases a strong foundation in Computer Science, developed across Algeria and China. She began her higher education at Constantine University 2 in Algeria, where she completed her Bachelor’s degree in Computer Science (2010–2012). Continuing at the same university, she earned her Master’s degree in Computer Science and its Applications (2012–2014). Her academic excellence earned her prestigious government scholarships, enabling her to pursue a PhD in Computer Science and its Applications at Dalian University of Technology, China (2015–2024). During her doctoral studies, Samia expanded her research scope and honed her skills in advanced computational topics such as image processing, machine learning, and control systems. Her education has been supported by full scholarships from both the Algerian government and Dalian University, recognizing her academic potential and commitment to research. She is fluent in Arabic and French, and proficient in English and Chinese (HSK 3), supporting her global academic engagement.

Experience

Samia Haouassi brings a blend of academic rigor and practical engagement through her research and extracurricular roles. During her doctoral studies at Dalian University of Technology, she actively contributed to the university’s international environment by leading the Arabic Culture Stand at the Cultural Festival in 2016 and 2017. This leadership experience reflects her organizational and managerial strengths. Samia also took part in research projects, authoring papers in fields like image dehazing, iris recognition, and iterative learning control, showcasing her expertise in machine vision and intelligent algorithms. Beyond research, she demonstrated strong communication and mentorship capabilities by supporting peers in navigating cross-cultural academic environments. Her experience as a scholarship recipient and cultural ambassador highlights her adaptability, leadership, and collaborative spirit. By integrating technical excellence with multicultural awareness, she exemplifies the modern researcher who is not only skilled in their field but also contributes to inclusive and diverse academic communities.

Awards and Honors

Samia Haouassi has been recognized with multiple prestigious awards and scholarships that reflect her academic excellence and research potential. From 2014–2015, she was awarded a scholarship by the Algerian government under an international exchange program, enabling her to expand her academic experience beyond national borders. In 2015, she was granted a fully funded PhD scholarship by Dalian University of Technology, one of China’s top institutions, to pursue advanced research in Computer Science. These scholarships were highly competitive and are a testament to her outstanding academic profile. In addition to academic honors, her cultural contributions at Dalian University were appreciated, as she led and organized the Arabic Culture Stand at the university’s Cultural Festival in 2016 and 2017. These accolades showcase both her academic dedication and her efforts in promoting cultural understanding and diversity, making her a well-rounded recipient of both academic and social recognition.

Research Focus

Samia Haouassi’s research focuses on intelligent systems within the domain of Computer Science and its Applications, with special emphasis on image processing, biometric recognition, and control algorithms. Her doctoral work at Dalian University of Technology centers on image dehazing—enhancing visual clarity in low-visibility environments using advanced filtering and machine learning methods. She also explores iris recognition technologies, developing secure and accurate biometric identification systems. In the area of iterative learning control (ILC), she investigates how systems can adapt and improve over time through feedback and repetition, with potential applications in robotics and automation. Her interdisciplinary approach integrates computer vision, pattern recognition, and adaptive systems. By addressing both theoretical challenges and practical applications, Samia aims to develop robust, real-world solutions for intelligent image analysis and control. Her work holds promise for innovation in security, automation, and human-computer interaction, bridging the gap between algorithmic research and its societal applications.

Publication Top Notes

📄 Image Dehazing Based on Multi-scale Fusion Using Dark Channel Prior
📄 Efficient Iris Recognition Using Enhanced Local Binary Patterns
📄 Iterative Learning Control for Repetitive Tasks in Dynamic Systems