Yanxia Liang | Computer Science | Research Excellence Award

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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.

Lesole Kalake | Computer Science | Best Research Article Award

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Lesole Kalake | Computer Science | Best Research Article Award

Dr. Lesole Kalake, National Department of Health, South Africa

Dr. Lesole Soldaat Kalake is a South African ICT and AI researcher, educator, and database professional with a strong interdisciplinary background in computer science, statistics, and business intelligence. He holds a PhD in Information and Communication Engineering from Shanghai University, China. With professional experience spanning over two decades, he has served in both academia and government, notably at the National Department of Health as a Business Analyst and Assistant Director. He has lectured at various institutions including the University of KwaZulu-Natal, UNISA, and Kobe Institute of Technology in Japan. Dr. Kalake has published extensively in peer-reviewed journals, focusing on multi-object tracking, electronic health system security, and computer vision. He is also an active peer reviewer for IEEE Access and Springer journals. Passionate about applying AI in public sector systems, he is known for his expertise in SQL databases, SAS tools, and machine learning frameworks, and continues to contribute to South Africa’s eHealth transformation.

Publication Profile

scopus

Education

Dr. Kalake earned his PhD in Information and Communication Engineering from Shanghai University, China in 2024. He also holds an MSc in Information Systems from Kobe Institute of Technology, Japan, and a BSc Honours in Applied Population Science from the University of KwaZulu-Natal, where he also completed his BSc in Computer Science and Statistics. His academic credentials further include professional diplomas and certificates: a Business Analysis degree from Desto Pty Ltd, Moderation of Outcomes-Based Assessment from Edutel Pty Ltd, and Assessment of Outcomes-Based Assessment from PC Training Holdings. Dr. Kalake is certified as a SAS Base 9 Programmer, SAS Advanced Programmer, and MCTS in Microsoft SQL Server 2008. These qualifications highlight his strong foundation in analytics, software engineering, and IT systems design, supporting his multidisciplinary contributions in both academia and government sectors, particularly in the realms of digital health and artificial intelligence.

Experience

Dr. Kalake has extensive professional experience in software development, tutoring, business analysis, and database administration. Since 2009, he has served the National Department of Health (South Africa) as an Assistant Director focusing on SQL database management, project coordination, and business intelligence. He previously worked for organizations such as Sasuka Pty Ltd and Gauteng Department of Public Works as a Business Analyst and SAS Developer. In academia, he held roles at the University of KwaZulu-Natal, UNISA, and Kobe Institute of Technology, tutoring in IT and statistics. His work has involved e-Governance coordination (JICA/IDCJ project) and developing reporting systems, security frameworks, and decision-support tools for government and private sectors. He is highly skilled in SAS tools, Microsoft SQL Server, Power BI, and modern AI frameworks like PyTorch and Keras, contributing to a seamless integration of data science into public health and development systems.

Awards and Honors

Dr. Lesole Kalake’s scholarly contributions have garnered international recognition. He has served as a peer reviewer for prestigious journals such as IEEE Access and Springer’s Multimedia Tools and Applications since 2021. His critical reviews have covered advanced topics in federated learning, AI for health diagnostics, and cross-dataset validation for age estimation. As a conference presenter, he co-authored a paper at the AFRICATEK 2017 international conference on the use of 3D facial recognition for secure eHealth authentication, published in Springer. His ongoing government work in pharmaceutical economic evaluations has also contributed to national policy development. Though his academic work is recent, it reflects high-impact innovation, especially in multi-object tracking and real-time computer vision, indicating growing recognition in the AI and public sector technology communities. His combined academic, research, and government contributions position him as a forward-thinking leader in the application of technology for development.

Research Focus

Dr. Kalake’s research lies at the intersection of artificial intelligence, eHealth security, and computer vision. His recent investigations explore real-time multi-object tracking across non-overlapping camera views, aiming to enhance detection and re-identification using deep learning models. He has worked on improving object detection performance by integrating methods like HOG (Histogram of Oriented Gradients) with Convolutional Neural Networks (CNNs). Additionally, he has focused on video processing, smart surveillance, and deep learning algorithms to improve detection quality in constrained environments. In the healthcare domain, he is investigating security frameworks for Electronic Health Record (EHR) systems, proposing models using 3D face recognition, Wi-Fi, and smartphone-based authentication to safeguard patient data. His interdisciplinary focus contributes to advancements in AI-driven diagnostics, public sector information systems, and the digital transformation of health systems. This blend of academic and applied research highlights his commitment to AI for public good.

Publication Top Notes

  • 📄 Analysis Based on Recent Deep Learning Approaches Applied in Real-Time Multi-Object Tracking: Review, IEEE Access, 2021

  • 📄 Enhancing Detection Quality Rate with a Combined HOG and CNN for Real-Time Multiple Object Tracking, Sensors, 2022

  • 📄 Applying Ternion Stream DCNN for Real-Time Vehicle Re-Identification and Tracking, Sensors, 2022

  • 📘 Designing an Electronic Health Security System Framework Using Wi-Fi, Smartphone, and 3D Face Recognition, AFRICATEK 2017, Springer

Samia Haouassi | Computer Science | Best Researcher Award

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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

Emmanouil Zoulias | Computer Science | Best Researcher Award

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Emmanouil Zoulias | Computer Science | Best Researcher Award

Dr Emmanouil Zoulias, Department of Nursing, National and Kapodistrian University of Athens, NKUA, Greece

Emmanouil A. Zoulias is a highly experienced electrical and computer engineer with specialization in health informatics and biomedical technology. Born on May 25, 1973, he currently serves as a Laboratory Teaching Staff member at the Faculty of Nursing, School of Health Sciences, National and Kapodistrian University of Athens 🇬🇷. His academic journey and professional career reflect a unique blend of technical expertise and medical application, with a strong foundation in medical informatics. A PhD holder with research experience in advanced data mining methods for medical diagnostics, Dr. Zoulias is known for his contributions to digital health systems, telemedicine, and biomedical engineering. He is an active member of notable professional bodies such as the IEEE, the Greek Biomedical Informatics Association, and the National Technical Chamber of Greece. Emmanouil is a team player, lifelong learner, and passionate educator with a vision to advance healthcare technologies for better patient outcomes. 🧠💻📊

Publication Profile

google scholar

Education

Emmanouil Zoulias holds a PhD in Biomedical Informatics (2012) from the National Technical University of Athens and the Medical School of the University of Patras. His doctoral thesis focused on developing a decision-support system for diagnosing thyroid smears using advanced data mining techniques 🔬📈. He also earned an MSc in Biomedical Instrumentation Engineering (1997) from the University of Dundee, UK, where he studied medical equipment, signal measurements, and imaging systems, completing a dissertation on telemetry systems in anesthesia monitoring 🏥📡. He began his academic journey with a Diploma in Electrical & Computer Engineering (1996) from the National Technical University of Athens, with a specialization in electronics, telecommunications, and computing systems ⚙️💡. His diploma project involved designing data management tools for telemedicine databases. Emmanouil’s academic path demonstrates a consistent commitment to integrating engineering with healthcare innovation. 📚🔧🩺

Experience

Emmanouil Zoulias has over two decades of diverse experience in health informatics, biomedical systems, and IT engineering. Since January 2020, he has been part of the Laboratory Teaching Staff at the National and Kapodistrian University of Athens, teaching Biomedical and Health Informatics 🧑‍🏫💡. Previously, he served as a Computer Engineer (2008–2018) at the National Centre of Public Administration and Local Governance. His earlier roles include IT Engineer at the 1st Regional Health Care System (2004–2008), Electronic Engineer at ISAP S.A. for urban railway signaling (2003–2004), and Project Manager at ANKO S.A. (2002–2003). He also worked as Research Manager at the National Centre for Scientific Research “Demokritos” (2000–2002), contributing to EU-funded projects 🌍📊. Emmanouil’s multidisciplinary expertise spans public health, telemedicine, traffic systems, and biomedical research. His career showcases a dynamic integration of technical problem-solving and public service impact. 🧪🖥️🔌

Awards and Honors

While no individual honors or awards were specifically listed in the CV, Emmanouil Zoulias’ recognition can be seen through his active membership in prestigious professional associations and his long-standing contributions to both academia and public service. He became a member of the National Technical Chamber of Greece in 1997 🏛️, reflecting his early professional credibility. In 2017, he joined the Hellenic Unit of Biomedical Instrumentation, followed by membership in the IEEE in 2018, acknowledging his alignment with global standards in engineering excellence 🌐🔧. Most recently, in 2020, he joined the Greek Biomedical Informatics and Health Informatics Association, recognizing his growing influence in medical data systems and informatics innovation 💻🔍. His consistent engagement with interdisciplinary fields and national organizations is a testament to his respected status in the Greek engineering and health informatics community.

Research Focus

Dr. Emmanouil Zoulias’ research centers on the integration of health informatics, biomedical instrumentation, and advanced computational methods in medical diagnostics 🧠💾. His PhD research pioneered the use of data mining techniques for supporting diagnostic decisions in thyroid FNA smears, demonstrating his vision for intelligent, automated healthcare solutions. His broader interests encompass telemedicine systems, signal processing, biomedical device development, and clinical information management systems 📊🩺. Through his academic and professional roles, he continues to explore how technology can improve patient monitoring, diagnostic accuracy, and healthcare delivery. As a university instructor, Emmanouil promotes interdisciplinary knowledge that merges medical science with informatics, aiming to equip future healthcare professionals with the tools to navigate a tech-driven clinical environment. His work stands at the intersection of engineering, computer science, and medicine, targeting innovations that enhance both individual care and public health infrastructures ⚙️💡🌍.

Publication Top Notes

  • Forecasting transmission and distribution system flexibility needs for severe weather condition resilience and outage management. 🌩️📉🔌📊

  • Active System Management Approach for Flexibility Services to the Greek transmission and distribution system. 🇬🇷⚙️🔋📡

  • Introducing maker movement in educational robotics: beyond prefabricated robots and “black boxes”. 🤖🎓🔧📚

  • Computer-aided diagnosis of thyroid malignancy using an artificial immune system classification algorithm. 🧠💻🧬🔍

  • A flexibility platform for managing outages and ensuring the power system’s resilience during extreme weather conditions. 🌪️🔌🛠️📈

  • Development and implementation of a flexibility platform for active system management at both transmission and distribution level in Greece. 🏗️📊🇬🇷🔋

  • Impacts of robotic assisted surgery on hospital’s strategic plan. 🏥🤖📈📋

  • The route to patient safety in robotic surgery. 🛡️🧑‍⚕️🤖❤️

  • A review of techniques to counter spam and spit. 📧🚫🕵️‍♂️🔐

  • Organization Style and Its Effect on Employee Satisfaction and Personal Performance. 🏢😊📈👥

 

 

 

Pedro Stalyn Aguilar Encarnacion | Computer Science | Best Research Article Award

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Pedro Stalyn Aguilar Encarnacion | Computer Science | Best Research Article Award

Prof Pedro Stalyn Aguilar Encarnacion, Escuela Superior Politécnica de Chimborazo, Ecuador

Pedro Stalyn Aguilar Encarnación 🇪🇨 is an experienced software engineer, researcher, and educator currently serving as a professor at the Escuela Superior Politécnica de Chimborazo (ESPOCH). With a strong foundation in programming and systems development, he integrates technical expertise with business acumen, holding an MBA alongside advanced degrees in Software Engineering. His academic journey reflects a commitment to innovation and excellence, culminating in his ongoing PhD in Computer Science. Pedro has contributed significantly to the academic community through impactful research in artificial intelligence, software engineering, and web technologies. Passionate about empowering future IT professionals, he actively participates in research projects and international conferences. He is known for developing intelligent platforms for environmental monitoring and sustainable agriculture. His diverse experiences in academia and industry, paired with leadership in research, make him a dynamic figure in Ecuador’s tech-education landscape.

Publication Profile

google scholar

Education

Pedro Aguilar holds multiple degrees in Information Technology and Business. He earned his Bachelor’s Degree in Computer Systems Engineering from the Escuela Superior Politécnica de Chimborazo in 2018. He later pursued a Master’s in Software from the Universidad Técnica de Machala, graduating in 2023. To complement his technical skills with business strategy, he obtained a Master in Business Administration (MBA) from the Universidad Internacional de La Rioja, Spain, in 2024. Continuing his academic excellence, he is currently a PhD candidate in Computer Science at the Escuela Politécnica Nacional as of 2024. His formal education is further enhanced by certifications in English proficiency (B1), leadership, talent management, and organizational culture from institutions such as MIU City University Miami, Universidad Nacional de Chimborazo, SETEC, and IECAP. This diverse educational background reflects his dual focus on technical innovation and strategic management in the digital age.

Experience

Pedro Aguilar’s professional journey spans both the private sector and academia. He began his career as a Hardware and Software Technician at TEINCORP (2009–2011) and then served as a Full Stack Developer at CYMOGSYS in 2017. His work in academia began in 2018 at ESPOCH, where he held various roles such as IT Support Analyst, Registration Analyst, and currently serves as a Professor and Researcher since April 2023. His teaching covers programming, mobile computing, and web technologies, shaping the next generation of software engineers. Pedro’s experience is also deeply rooted in research and innovation, leading projects that use smart technologies like IoT and Progressive Web Apps. His interdisciplinary approach—blending IT systems with real-world applications like agriculture and water monitoring—demonstrates his commitment to socially impactful solutions. With over 5 years in academia and multiple years in industry, Pedro has developed a well-rounded, hands-on approach to technology and education.

Awards and Honors

Pedro Aguilar has earned multiple recognitions for his academic involvement and leadership. He was acknowledged by ESPOCH as a Reviewer at the II International Congress on Innovation, Science, and Technology (May–Nov 2023), reflecting his contributions to scientific quality and peer evaluation. He also received certifications in Leadership and Training from SETEC and MIU City University Miami, recognizing his ability to lead and inspire teams in technological and educational settings. His English language proficiency (B1) was certified by the Universidad Nacional de Chimborazo, supporting his active participation in international collaborations. In addition, he completed over 180 hours of certified training in areas like diversity, inclusion, human resources, organizational well-being, and corporate image—enhancing his ability to lead educational and research projects with a human-centered focus. While his academic and research achievements shine, his consistent pursuit of self-improvement stands as a testament to his professional excellence.

Research Focus

Pedro Aguilar’s research focus lies at the intersection of Software Engineering, Artificial Intelligence, and Information Systems for societal applications. His projects are strongly rooted in smart agriculture, environmental monitoring, and IoT systems, addressing real-world challenges through data-driven platforms. Notably, he contributed to the creation of a Predictive Platform for Cocoa Moniliasis Detection using sensors and AI, benefiting Ecuadorian agricultural zones. Currently, he is involved in developing an Intelligent Geoportal to monitor potable water quality using IoT technologies. Pedro is particularly interested in Progressive Web Applications (PWAs) and machine learning models to improve decision-making in critical sectors. His work integrates semantic web technologies, mobile computing, and vehicular networks (VANETs) to create scalable, sustainable digital solutions. With publications in international high-impact journals and conference proceedings, his research continues to evolve with emerging technologies while staying aligned with sustainable development and technological equity in Latin America.

Publication Top Notes

  • 🧠 Desarrollo de un modelo predictivo utilizando técnicas de aprendizaje supervisado para detectar la moniliasis en plantas de cacao de la Provincia de Orellana

  • 🌱 Fighting moniliasis in Orellana with sensors and PWA for sustainable agriculture

  • 🌾 Prevention of cocoa moniliasis using Progressive Web Applications and sensor data in the province of Francisco de Orellana

  • 📊 Predictive Model in Production through Progressive Web Applications to Forecast Moniliasis in Cacao

  • 🚗 Vehicular Ad-Hoc Network (VANET)