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.

Mohammed Al-Naeem | Computer Science | Best Researcher Award

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Mohammed Al-Naeem | Computer Science | Best Researcher Award

King Faisal University | Saudi Arabia

Dr. Mohammed Abdulaziz Al-Naeem is a dedicated scholar and researcher in computer science whose work spans wireless networks, information security, and advanced sensing technologies. He earned both his Master’s and Ph.D. degrees from Monash University, where his doctoral research focused on developing pattern transformation-invariant schemes for wireless sensor networks using an edge-detection, gradient-based mechanism—an innovative contribution that strengthened the robustness and adaptability of sensor-based systems. His academic journey began with a Bachelor of Science from King Faisal University, an institution to which he has remained professionally committed throughout his career. After joining the university as a Teaching Assistant, he steadily progressed through key academic roles, later serving as a Lecturer and ultimately as an Assistant Professor, a position he has held since 2016. Across these roles, he has contributed significantly to teaching, mentoring, and research development within the Department of Computer Science. Dr. Al-Naeem’s academic expertise centers on wireless networks, network security, and the design of resilient sensing and communication frameworks. His research interests integrate theoretical foundations with practical applications, with a focus on secure, efficient, and scalable systems capable of supporting modern intelligent environments. His work reflects an enduring commitment to advancing computational methodologies and enhancing the reliability of networked systems across diverse contexts. He is also proficient in both Arabic and English, enabling him to engage with a wide scholarly community and collaborate on international research initiatives. Through his academic leadership, research contributions, and dedication to advancing knowledge in wireless communication and cybersecurity, Dr. Al-Naeem continues to play an active and impactful role in shaping the next generation of technological innovation.

Profile: Orcid | Scopus | Google scholar

Featured Publications

Alsmadi, I., Aljaafari, N., Nazzal, M., Alhamed, S., Sawalmeh, A. H., Vizcarra, C. P., … [add remaining authors if needed]. (2022).
Adversarial machine learning in text processing: A literature survey. IEEE Access, 10, 17043–17077.

Almusallam, N., Tari, Z., Chan, J., Fahad, A., Alabdulatif, A., & Al-Naeem, M. (2021).
Towards an unsupervised feature selection method for effective dynamic features. IEEE Access, 9, 77149–77163.

Al-Naeem, M. A. (2021).
Prediction of re-occurrences of spoofed ACK packets sent to deflate a target wireless sensor network node by DDOS. IEEE Access, 9, 87070–87078.

Rana, M. U., Shah, M. A., Al-Naeem, M. A., & Maple, C. (2024).
Ransomware attacks in cyber-physical systems: Countermeasure of attack vectors through automated web defenses. IEEE Access, 12, 149722–149739.

Usman Ashraf, U. M., Ahmed, A., & Al-Naeem, M. (2021).
Reliable and QoS aware routing metrics for wireless neighborhood area networking in smart grids. Computer Networks, Article 14.
(If volume/issue/page numbers exist, please provide to complete the citation.)

Al-Naeem, M., Rahman, M. M. H., Banerjee, A., & Sufian, A. (2023/2024?).
Support vector machine-based energy efficient management of UAV locations for aerial monitoring of crops over large agriculture lands. Sustainability, 15(8), 6421.

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

orcid

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

Kassem Kallas | Computer Science | Best Researcher Award

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Kassem Kallas | Computer Science | Best Researcher Award

Prof. Dr Kassem Kallas, Inserm, France

Dr. K. Kallas is a multidisciplinary Research Scientist and Junior Professor specializing in Artificial Intelligence (AI) 🤖 and Cybersecurity 🔐. With a Ph.D. in Information Engineering from the University of Siena 🇮🇹, he is currently a Senior Scientist at the French National Institute of Health and Medical Research 🇫🇷. He has held prestigious roles at INRIA and the U.S. National Institute of Standards and Technology (NIST) 🇺🇸. Dr. Kallas is known for pioneering research in adversarial deep learning, game-theoretic sensor fusion, and AI intellectual property protection via watermarking. A recognized speaker 🎤 and mentor, he actively contributes to global academic and industry collaborations. He also volunteers with the IEEE Collabratec and Lebanese Red Cross ❤️. He is pursuing the Habilitation à Diriger des Recherches (HDR), the highest academic qualification in France. His work bridges the worlds of AI security, strategic leadership, and ethical innovation in digital technologies.

Publication Profile

orcid

Education

Dr. Kallas earned his Ph.D. in Information Engineering and Sciences (2013–2017) from the University of Siena, Italy 🇮🇹, with a dissertation on game-theoretic approaches to adversarial information fusion. He is currently pursuing the Habilitation à Diriger des Recherches (HDR) at the University of Western Brittany 🇫🇷 (2024–2025), focusing on AI security through backdoor attack analysis and watermarking. He also holds an Executive MBA 🎓 in Strategic Leadership from Valar Institute, Quantic School of Business and Technology (2023–2024), graduating with a stellar 94.8% average. Earlier, he completed a Second Level Master in Wireless Systems 📡 at Politecnico di Torino 🇮🇹 (2012–2013), an M.Sc. in Computer and Communications Engineering from the Lebanese International University 🇱🇧 (2010–2012), and a B.Sc. in Telecommunications Engineering (2006–2010) from the same institution. His academic path blends engineering, leadership, and innovation at the highest international levels 🌍.

Experience

Dr. Kallas is currently a Senior Scientist at the French National Institute of Health and Medical Research 🧬, where he leads research on secure and private AI in healthcare. From 2022–2023, he served as a Research Scientist at INRIA 🇫🇷, contributing to the SAIDA defense AI security project, with focus areas including backdoor attacks, model defenses, and neural watermarking. Previously, he was a Research Fellow at NIST 🇺🇸 (2020–2022), working in the wireless communications division of the chemical and nuclear measurement group. His diverse career includes involvement in DARPA, the U.S. Air Force Research Lab, French ANR, and the Italian Ministry of Research. As a speaker and academic contributor, he has presented globally 🌎 on AI threats and defenses, quantum neural networks, and adversarial machine learning. He is a mentor at IEEE Collabratec and a youth volunteer with the Lebanese Red Cross 🚑, blending scientific leadership with social responsibility.

Awards and Honors

Dr. Kallas has received numerous awards and recognitions across his career. His Ph.D. thesis was ranked in the Top 3 Best-of-the-Best by Springer 🥉. He earned the Best Paper Award 🏅 at the 9th International Conference on Advances in Multimedia (MMEDIA 2017), and his ICASSP 2023 paper was ranked in the Top 3% 🥇 for its groundbreaking contributions to DNN watermarking. He was selected as an Invited Keynote Speaker 🎙️ at international conferences, including the 5th ICCCS in India, TheAIEngineers in Lebanon, and seminars at IMT Atlantique and École Polytechnique in France. His work is regularly featured in high-impact publications and global research events. Beyond academia, his leadership was recognized in his EMBA program, where he led a business consultancy team to full marks ⭐. These accolades reflect his innovation, influence, and impact across cybersecurity, AI, and signal processing

Research Focus

Dr. Kallas’s research focuses on AI security, adversarial machine learning, and cybersecurity for distributed systems 🔐. His pioneering work investigates backdoor attacks, model robustness, and the protection of AI intellectual property via watermarking 💧. Through a game-theoretic lens, he analyzes adversarial behavior in sensor networks, making his research crucial for defense, healthcare, and IoT systems. At INRIA, he contributed to SAIDA, a project focused on securing deep learning systems against hidden threats. His current role at INSERM emphasizes the privacy-preserving deployment of AI models in healthcare, addressing critical issues in ethical AI. He also explores quantum neural networks, signal processing, and secure fusion techniques, enabling more resilient AI ecosystems. With involvement in EU and US-funded defense and science initiatives (DARPA, ANR, etc.), his interdisciplinary approach bridges theoretical foundations with practical solutions. His aim: building robust, transparent, and accountable AI systems fit for complex, real-world deployments 🌐.

Publication Top Notes

  1. 📘 Deciphering the Realm of Artificial Intelligence Security: Journeying from Backdoor Attacks in Deep Learning to Safeguarding Their Intellectual Property Through Watermarking (HDR Dissertation, 2025)

  2. 📗 Simplifying Care, Amplifying Impact: ADDYOU – Your Path to Well-Being (EMBA Final Project, 2024)

  3. 📕 A Game-Theoretic Approach for Adversarial Information Fusion in Distributed Sensor Networks (PhD Dissertation, 2017)

  4. 📙 Design of Capacity Control for TCP Protocol using Markov Chains (Master Thesis, Politecnico di Torino)

  5. 📒 Simulation of Bit-Interleaved LDPC with Iterative Decoding System (M.Sc. Thesis)

  6. 📓 Design and Hardware Implementation of Wireless Liquid Level Indicator System (B.Sc. Final Project)

Dr. Md. Tarek Habib | Computer Science | Best Researcher Award

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Assist. Prof. Dr. Md. Tarek Habib | Computer Science | Best Researcher Award

Assist. Prof. Dr. Md. Tarek Habib Independent University, Bangladesh

Dr. Md. Tarek Habib is an Assistant Professor in the Department of Computer Science and Engineering at Independent University, Bangladesh. With a strong passion for teaching and research, his objective is to enhance his expertise in the field of Computer Science and Engineering. His research interests include Artificial Intelligence, with a focus on Computer Vision, Machine Learning, and Natural Language Processing, as well as IoT and E-Commerce. Dr. Habib is dedicated to advancing knowledge and innovation in these domains, contributing to both academia and industry through his research and mentorship.

Education:

Doctor of Philosophy (Ph.D.) in Computer Science and Engineering

Institution: Jahangirnagar University, Bangladesh

Year: 2022

Thesis Title: Machine Vision Based Fruit Disease Recognition

Supervisor: Prof. Dr. Mohammad Shorif Uddin

Co-Supervisor: Prof. Dr. Farruk Ahmed (Independent University, Bangladesh)

Master of Science (M.S.) in Computer Science and Engineering

Institution: North South University, Bangladesh

Year: 2009

CGPA: 3.85 on a scale of 4.0

Thesis Title: Machine Vision Based Textile Defects Classification

Supervisor: Prof. Dr. M. Rokonuzzaman

Bachelor of Science (B.Sc.) in Computer Science

Institution: BRAC University, Bangladesh

Year: 2006

CGPA: 3.74 on a scale of 4.0

Award: Vice Chancellor’s Medal

Thesis Title: A Survey on Location Systems for Ubiquitous Computing

Supervisor: Prof. Dr. Matin Saad Abdullah

Higher Secondary Certificate (HSC)

Institution: SOS Hermann Gmeiner College, Dhaka Board

Year: 2000

Division: 2nd Division (Science Group)

Total Marks: 567 out of 1000

Secondary School Certificate (SSC)

Institution: Sher-e-Bangla Nagar Govt. Boys’ High School, Dhaka Board

Year: 1998

Division: 1st Division with Star Marks (Science Group)

Total Marks: 823 out of 1000

Professional Profiles:

ORCID Profile

Scopus Profile

Professional Experience:

Assistant Professor, Department of Computer Science and Engineering

Independent University, Bangladesh January 2023

Associate Professor, Department of Computer Science and Engineering
Daffodil International University, Bangladesh (January 2023 – January 2023)

Assistant Professor, Department of Computer Science and Engineering
Daffodil International University, Bangladesh (January 2016 – December 2022)

Assistant Professor (Contractual), Department of Computer Science and Engineering
Daffodil International University, Bangladesh (September 2015 – December 2015)

Assistant Professor, Department of Computer Science and Engineering
Green University of Bangladesh (May 2014 – September 2015)

Assistant Professor, Department of Computer Science and Engineering
Prime University, Bangladesh (September 2013 – May 2014)

Senior Lecturer, Department of Computer Science and Engineering
Prime University, Bangladesh (January 2013 – August 2013)

Lecturer, Department of Computer Science and Engineering
Prime University, Bangladesh (October 2010 – December 2012)

Research Interests:

Artificial Intelligence (AI) and Its Applications

Computer Vision

Machine Learning (ML)

Natural Language Processing (NLP)

Internet of Things (IoT)

E-Commerce and AI-Driven Business Solutions

Top Notable Publications:

An Insightful Analysis of CNN-Based Dietary Medicine Recognition

Journal of Agriculture and Food Research, 2025-03

DOI: 10.1016/j.jafr.2024.101564

Contributors: Mohammad Didarul Alam, Tanjir Ahmed Niloy, Aurnob Sarker Aurgho, Mahady Hasan, Md. Tarek Habib

Deep Learning Modeling for Potato Breed Recognition

IEEE Transactions on AgriFood Electronics, 2024

DOI: 10.1109/TAFE.2024.3406544

Contributors: Md. Ataur Rahman, Abbas Ali Khan, Md. Mehedi Hasan, Md. Sadekur Rahman, Md. Tarek Habib

A Study on Social Media Addiction Analysis on the People of Bangladesh Using Machine Learning Algorithms

Bulletin of Electrical Engineering and Informatics, 2024-10-01

DOI: 10.11591/eei.v13i5.5680

Contributors: Minjun Nahar Mim, Mehedi Firoz, Mohammad Monirul Islam, Mahady Hasan, Md. Tarek Habib

Tomato Pest Recognition Using Convolutional Neural Network in Bangladesh

Bulletin of Electrical Engineering and Informatics, 2024-02-01

DOI: 10.11591/eei.v13i1.6073

Contributors: Johora Akter Polin, Nahid Hasan, Md. Tarek Habib, Atiqur Rahman, Zannatu Nayem Vasha, Bidyut Sharma

Publications (2020-2023)

A Machine Learning Approach for Driver Identification

Indonesian Journal of Electrical Engineering and Computer Science, 2023-04-01

DOI: 10.11591/ijeecs.v30.i1.pp276-288

Contributors: Md. Abbas Ali Khan, Mohammad Hanif Ali, Fazlul Haque, Md. Tarek Habib

Analysis of Recognition Performance of Plant Leaf Diseases Based on Machine Vision Techniques

Journal of Human, Earth, and Future, 2022-03-01

DOI: 10.28991/HEF-2022-03-01-09

Contributors: Imdadul Haque, Mohsin Alim, Mahbub Alam, Samia Nawshin, Sheak Rashed Haider Noori, Md. Tarek Habib

Machine Vision-Based Papaya Disease Recognition

Journal of King Saud University – Computer and Information Sciences, 2020-03

DOI: 10.1016/j.jksuci.2018.06.006

Contributors: Md. Tarek Habib, Anup Majumder, A.Z.M. Jakaria, Morium Akter, Mohammad Shorif Uddin, Farruk Ahmed

Conclusion:

Given his extensive publication record, research impact, and interdisciplinary contributions, Assist. Prof. Dr. Md. Tarek Habib is highly suitable for the Research for Best Researcher Award. His pioneering work in AI, ML, and IoT continues to drive innovation and technological advancements, making him a deserving recipient of this esteemed recognition.