Fabrice Vidal | Computer Science | Research Excellence Award

Fabrice Vidal | Computer Science | Research Excellence Award

Hospital center|France

Dr. Fabrice Vidal is a hospital pharmacist with extensive experience in hospital pharmacy management, medication safety, and healthcare quality systems. Since 2014, he has served as a Hospital Practitioner and Head of the Pharmacy for Internal Use at the Centre Hospitalier de Dax, where he plays a central role in ensuring the safe, efficient, and compliant use of medicines and medical devices. His responsibilities include the management of medical devices, oversight of pharmaceutical logistics, and active participation in the quality management of medication use and the overall medication care pathway. He has contributed significantly to the modernization of hospital pharmacy operations through involvement in the implementation of a Warehouse Management System and the development and deployment of computerized prescribing decision-support software. His expertise also extends to the validation of chemotherapy prescriptions, ensuring adherence to clinical protocols and patient safety standards. In addition, he has participated in pharmaceutical on-call duties related to medication safety and emergency preparedness. Prior to his permanent appointment, he worked as a full-time contractual Hospital Practitioner at the same institution, gaining strong operational experience within the Pharmacy for Internal Use.


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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.

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