Chithik Raja Mohamed Sinnaiya | Cyber Security | Research Excellence Award

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Dr. Chithik Raja Mohamed Sinnaiya | Cyber Security | Research Excellence Award

Dr. Chithik Raja Mohamed Sinnaiya is a researcher at the University of Technology and Applied Sciences, Salalah, Oman, specializing in big data analytics, cybersecurity, and intelligent systems. With 6 publications, 76 citations, and an h-index of 3, his work focuses on advanced anomaly detection using attention-enhanced LSTM models for identifying zero-day attacks while preserving data privacy. His research contributes to developing secure, scalable, and privacy-aware solutions for real-time data stream analysis in modern digital environments.

Citation Metrics (Scopus)

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View Scopus Profile
    View Orcid Profile

Featured Publications

Privacy-Preserving Machine Learning Models for Cybersecurity Applications
– Research Article

Deep Learning Approaches for Real-Time Anomaly Detection in Data Streams
– Journal Article

Big Data Analytics for Intrusion Detection Systems: Challenges and Opportunities
– Review Paper

AI-Driven Security Frameworks for Detecting Zero-Day Cyber Threats
– Conference/Journal

Scalable and Privacy-Aware Data Stream Processing using LSTM Networks
– Research Work

Khawaja Iftekhar Rashid | Computer Science | Research Excellence Award

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Dr. Khawaja Iftekhar Rashid | Computer Science | Research Excellence Award

Xiamen University | China

Dr. Khawaja Iftekhar Rashid is an emerging researcher in artificial intelligence, machine learning, and computer vision, with a strong specialization in semantic image segmentation for urban scenes, autonomous driving, and medical imaging. His work focuses on advanced deep learning models, including attention mechanisms, GANs, vision transformers, graph neural networks, and semi-/few-shot learning frameworks. He has published in high-impact, peer-reviewed journals such as Neurocomputing, Engineering Applications of Artificial Intelligence, and Expert Systems with Applications, reflecting both theoretical innovation and real-world applicability. His research profile demonstrates growing scholarly impact with 46 citations, an h-index of 5, and an i10-index of 1.

Citation Metrics (Scopus)

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Citations 45

Documents 8

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View Google Scholar Profile

Featured Publications

Janmejaya Mishra | Cybersecurity | Best Researcher Award

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Mr. Janmejaya Mishra | Cybersecurity | Best Researcher Award

Capella University | United States

Mr. Janmejaya Mishra is a Principal Engineer with extensive expertise in developing and architecting high-performance web applications, combining strong academic foundations with professional excellence. He holds a Master of Science in Information Assurance and Cybersecurity from Capella University, graduating with distinction, and is currently pursuing a Doctor of Information Technology at the same institution. His career spans leadership in building scalable, secure, and high-traffic systems across education, telecom, healthcare, and finance sectors, with a specialization in Drupal, PHP, JavaScript, MySQL, and modern frameworks. He has delivered numerous Drupal projects from concept to production while ensuring cloud performance and application security through platforms such as Cloudflare, Splunk, and New Relic. A certified AWS Solutions Architect, Scrum Master, and Acquia Drupal Developer, he has earned recognition for advancing enterprise solutions and implementing innovative frameworks. His blend of research, technical mastery, and practical contributions positions him as an influential leader in cybersecurity and software engineering.

Profile: Scopus | Orcid

Featured Publications

1. Mohapatra, K., Mishra, J., Pattanaik, S. R., Pati, A., Panigrahi, A., & Sahu, B. (2025). EFSMLHA: Ensembled feature selected machine learning hybrid approaches for heart disease prediction. 2025 International Conference in Advances in Power Signal and Information Technology (APSIT 2025). IEEE.

2. Mishra, J., Biswal, B. B., & Padhy, N. (2025). Machine learning for fraud detection in banking cyber security: Performance evaluation of classifiers and their real-time scalability. 2025 5th International Conference on Emerging Systems and Intelligent Computing (ESIC 2025) Proceedings. IEEE.

3. Sahu, B., Mishra, J., Parveen, S., Das, B., Panigrahi, A., & Pati, A. (2025). STIR-MO: An enhanced hybrid cancer predictive model. 2025 3rd International Conference on Intelligent and Cloud Computing (ICoICC 2025). IEEE.

Basim abed | Cybersecurity | Best Researcher Award

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Mr. Basim abed | Cybersecurity | Best Researcher Award

Mr. Basim abed, Tabriz University, Iran

Mr. Basim Najim Al-Din Abed is an experienced academic professional in Computer Science with a specialization in Data Security and Cybersecurity. Currently pursuing a Ph.D. in Cybersecurity at Tabriz University, Iran (expected 2025), he holds an M.Sc. in Computer Science from Yarmouk University, Jordan, and dual bachelor’s degrees in Mathematics and Computer Science. With over 10 years of teaching and research experience, Mr. Abed has authored 19 peer-reviewed publications in international journals and conferences, focusing on encryption techniques, cybersecurity models, and deepfake detection. His research interests include cyber threats, cryptography, network security, blockchain, and privacy protection. He is proficient in Python, Java, C++, and tools such as Wireshark, Kali Linux, and Metasploit, with expertise in RSA, AES, and SHA-256 algorithms. Mr. Abed’s work demonstrates a strong commitment to advancing cybersecurity research through innovative mathematical and technical solutions to emerging digital threats.

Publication Profile

Orcid

🎓 Educational Background

Mr. Basim Najim Al-Din Abed possesses a strong and diverse academic foundation in the fields of computer science and mathematics. He is currently pursuing a Ph.D. in Cybersecurity at Tabriz University in Iran, with an expected graduation year of 2025. This advanced academic endeavor builds upon his Master of Science in Computer Science, with a specialization in Data Security, which he earned from Yarmouk University in Irbid, Jordan, in 2015. His multidisciplinary expertise is further supported by two bachelor’s degrees: one in Mathematics Science, completed in 2008, and another in Computer Science, earned in 1996. This comprehensive educational progression showcases Mr. Abed’s deep commitment to advancing his knowledge in both theoretical and applied sciences. His academic journey, spanning over two decades, has provided a solid foundation for his research in cybersecurity, encryption, and data protection, enabling him to contribute meaningfully to both academic and practical domains in the digital security landscape.

🔍 Research Interests

Mr. Basim Najim Al-Din Abed has developed a focused and forward-looking research portfolio in the dynamic field of cybersecurity. His primary research interests include cybersecurity and the analysis of emerging cyber threats, where he explores strategies to safeguard digital infrastructure. He is particularly invested in data privacy and encryption techniques, aiming to enhance the confidentiality and integrity of sensitive information. Mr. Abed also delves into network security and intrusion detection systems, working on advanced methods to detect and prevent unauthorized access. His work in cryptography and secure communication contributes to building robust protocols against digital attacks. Additionally, he investigates the integration of blockchain technology to strengthen cybersecurity frameworks and supports innovations in decentralized systems. Recently, he has expanded his focus to the detection and prevention of deepfakes, addressing one of the most pressing challenges in modern digital forensics and media security.

Publication Top Notes

  • Encrypting Text Messages via Iris Recognition and Gaze Tracking Technology, 2025, Mesopotamian Journal of CyberSecurity, DOI: [10.58496/MJCS/2025/007],

  • Lossless Encoding Method Based on a Mathematical Model and Mapping Pixel Technique for Healthcare Applications, 2024, Iraqi Journal of Science, DOI: [10.24996/ijs.2024.65.12.32], Cited by: Scopus – 1 citation

  • A Deep Fake Detection System Using Diffusion Model Based on Graph Based Image Segmentation, 2023, Frontiers in Artificial Intelligence and Applications, DOI: [10.3233/FAIA230776], Cited by: Scopus – 3 citations

  • A New Mathematical Model to Improve Encryption Process Using Taylor Expansion, 2020, IEEE IT-ELA Conference, DOI: [10.1109/IT-ELA50150.2020.9253084], Cited by: Scopus – 5 citations

  • A Novel Approach by Using a New Algorithm: Wolf Algorithm as a New Technique in Cryptography, 2020, Webology, DOI: [10.14704/WEB/V17I2/WEB17069], Cited by: Scopus – 2 citations

  • Using Cardano’s Method for Solving Cubic Equation in the Cryptosystem to Protect Data Security Against Cyber Attack, 2020, AiCIS Conference, DOI: [10.1109/AiCIS51645.2020.00030], Cited by: Scopus – 4 citations

  • McLaurin Series as a New Technique to Improve Encryption Process, 2019, Journal of Physics: Conference Series, DOI: [10.1088/1742-6596/1294/4/042008], Cited by: Scopus – 6 citations

  • Mapping Private Keys into One Public Key Using Binary Matrices and Masonic Cipher: Caesar Cipher as a Case Study, 2016, Security and Communication Networks, DOI: [10.1002/sec.1431], Cited by: Scopus – 12 citations

Conclusion

Mr. Basim Najim Al-Din Abed is a strong and deserving candidate for the Research for Best Researcher Award, particularly in the domain of Cybersecurity and Data Protection. His innovative research, technical expertise, and consistent academic contribution make him well-suited for recognition at this level. With further emphasis on international visibility, research leadership, and recognition, Mr. Abed’s profile can evolve from commendable to exceptional.

Lingxin Jin | Computer Science | Best Researcher Award

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Dr. Lingxin Jin | Computer Science | Best Researcher Award

Dr. Lingxin Jin, University of Electronic Science and Technology of China

Dr. Lingxin Jin, based in Chengdu, China, is a Ph.D. candidate in Software Engineering at the University of Electronic Science and Technology of China, where he also completed his Bachelor’s degree with a GPA of 3.8/4.0. His academic focus includes artificial intelligence, machine learning, network security, and software systems. Dr. Jin has gained international experience through an exchange program at the International Technological University in Silicon Valley and held internships involving front-end development and research on backdoor attacks against deep neural networks. His research contributions include publications in high-impact journals such as IEEE Transactions on Computers and the Journal of Circuits, Systems, and Computers, with additional submissions to ACM and IJCAI. Dr. Jin has worked on projects ranging from Linux shell simulations to public opinion analysis systems. He has received several scholarships and honors, including direct Ph.D. program recommendation, and is recognized for his promising research in AI security and adversarial attacks.

Publication Profile

Scopus

 Orcid

🎓 Educational Background

Dr. Lingxin Jin pursued his academic journey in Software Engineering at the University of Electronic Science and Technology of China. He completed his Bachelor’s degree from September 2018 to June 2022, achieving an impressive GPA of 3.8/4.0. During his undergraduate studies, he built a strong foundation through comprehensive coursework in Software Engineering, Computer Networks, Operating Systems, and Artificial Intelligence. Driven by academic excellence, Dr. Jin was recommended for direct entry into the Ph.D. program, which he began in September 2022. Currently, he is a Ph.D. candidate in Software Engineering at the same university, maintaining a GPA of 3.71/4.0. His advanced studies focus on cutting-edge topics such as Information Security Fundamentals and Frontiers, Network Security Theory and Technology, Machine Learning Theory and Algorithms, and Statistical Machine Learning. This academic background highlights his commitment to research and innovation in secure intelligent systems and computational technologies.

💼 Professional Experience

Dr. Lingxin Jin has gained diverse and valuable professional experience that complements his academic pursuits in software engineering and artificial intelligence. In July 2019, he participated in an exchange program at the International Technological University in Silicon Valley, where he engaged in programming robot motion manipulation using Raspberry Pi and Arduino, as well as composing songs using MATLAB—demonstrating his multidisciplinary creativity. From January to June 2021, Dr. Jin interned at Xi’an Deta Information Technology Co., where he focused on front-end development and contributed to building an opinion analysis system. This role honed his skills in UI/UX and real-time data interpretation. He later served as a Software Engineer Intern at Sichuan Meiliankai Science and Technology Co. from September 2021 to June 2022, where he conducted advanced research on backdoor attacks against deep neural networks. These experiences collectively reflect Dr. Jin’s technical versatility and growing expertise in cybersecurity and intelligent systems.

🏅 Additional Experience and Awards

Dr. Lingxin Jin has consistently demonstrated academic excellence throughout his educational journey, earning multiple awards and recognitions. During his undergraduate studies from 2018 to 2022 at the University of Electronic Science and Technology of China, he was honored with first and second-class scholarships for outstanding academic performance. His dedication and scholarly achievements earned him a prestigious recommendation for direct admission into the Ph.D. program, a distinction reserved for top-performing students. As a postgraduate student from 2022 onward, Dr. Jin continued to excel, receiving scholarships for new students as well as second-class scholarships for academic distinction. These accolades not only highlight his strong academic capabilities but also reflect his commitment to advancing in the field of software engineering and artificial intelligence. Dr. Jin’s consistent recognition at both undergraduate and postgraduate levels underscores his potential as a future leader in cutting-edge technological research and innovation.

🧠 Research Focus

Dr. Lingxin Jin’s research primarily focuses on adversarial machine learning, with a particular emphasis on Trojan attacks and security vulnerabilities in deep neural networks (DNNs). His scholarly work explores the life-cycle threats faced by DNNs, covering both attack strategies and defensive countermeasures. His publication in ACM Computing Surveys titled “Trojan Attacks and Countermeasures on Deep Neural Networks from Life-Cycle Perspective” provides a comprehensive overview of attack surfaces throughout a model’s development and deployment phases. Additionally, his work in IEEE Transactions on Computers, “Highly Evasive Targeted Bit-Trojan on Deep Neural Networks”, introduces novel methods of crafting stealthy, highly targeted Trojans that evade standard detection techniques. Through these contributions, Dr. Jin is advancing the field of AI security, focusing on the resilience and trustworthiness of neural networks in critical applications. His research is vital for developing robust defense frameworks and ensuring safe deployment of AI systems in real-world scenarios.

Publication Top Notes

  • 📄 2024: “Highly Evasive Targeted Bit‑Trojan on Deep Neural Networks” (IEEE Trans. on Computers) – DOI:10.1109/TC.2024.3416705; introduces stealthy bit-level Trojans; cited 2 times

  • 📄 2023: “Iterative Training Attack: A Black‑Box Adversarial Attack via Perturbation Generative Network” (J. of Circuits, Systems and Computers) – DOI:10.1142/S0218126623503140; black-box generative adversarial method;

  • 📄 2023: “A Survey of Trojan Attacks and Defense to Neural Networks” (under review at ACM Computing Surveys); comprehensive lifecycle review of Trojan threats

  • 📄 2024: “Data Poisoning‑based Backdoor Attack Framework against Supervised Learning Rules of Spiking Neural Networks” (submitted to IJCAI ’25); extends backdoor threats to spiking neural models

 

Jamshed AliShaikh | Cybersecurity | Best Researcher Award

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Dr. Jamshed AliShaikh | Cybersecurity | Best Researcher Award

Dr. Jamshed AliShaikh at Chongqing University, China

Jamshed Ali  is a Ph.D. candidate in Computer Science & Technology at Chongqing University, China 🇨🇳, with over 7 years of research experience and 4+ years of industry and academic roles. His work bridges AI 🤖, cybersecurity 🔐, and healthcare technologies 🏥. He has contributed to high-impact projects funded by Chinese research councils and has published multiple Q1-ranked journal articles 📚. Jamshed is known for his collaborative spirit, technical versatility, and commitment to using AI for societal benefit 🌍. He is fluent in programming and simulation tools and is a recognized young researcher from Pakistan 🇵🇰.

Publication Profile

Google Scholar

Academic Background

Jamshed Ali earned his Ph.D. in Computer Science & Technology (2020–2025) from Chongqing University, focusing on intelligent intrusion detection for IoMT healthcare networks 🛡️🏥. He completed his MS in Electrical Engineering (2018–2020) at the same university, working on AI-based optimization in smart grids ⚡ using fuzzy logic and control systems. He holds a BS in Electronics (2010–2014) from the University of Sindh, Pakistan, where he explored smart robotics 🤖 for disaster response. His academic path reflects a strong foundation in electronics, AI, and system-level problem-solving 💡 across interdisciplinary domains.

Professional Background

Jamshed Ali has over 4 years and 5 months of professional experience 🧠💻, including work as a Lecturer and IT In-Charge 👨‍🏫 at HIMAS-CON (3+ years), where he taught computer science and led IT operations. He worked as a PHP Developer 💻 at Geeks of Kolachi, managing web development projects. During his internship at Chongqing Kaixinderui, he gained practical experience in engineering teamwork and cultural integration 🤝🇨🇳. Alongside his academic research, these roles reflect a hands-on approach to both technical development and educational leadership in IT and cybersecurity domains 🔐🧑‍🏫.

Awards and Honors

Jamshed Ali received a fully funded 🎓 Chinese Government Scholarship for both his MS and Ph.D. studies in 2018 and 2020 🇨🇳. He was named the “Outstanding Student of the Year” 🥇 in 2020 at Chongqing University for academic excellence and leadership. He also won “Best Speaker” 🎤 at the China-Pakistan Culture and Technology Conference, where he presented on AI’s transformative role across healthcare, education, and manufacturing 🚀. These accolades reflect his academic impact, communication skills, and international recognition 🌍 in the field of intelligent systems and research innovation 🧪.

Research Focus

Jamshed’s research centers on cybersecurity in IoMT and Industrial IoT 🌐, with a focus on machine learning and deep learning 🔍 for intrusion detection, especially detecting zero-day attacks 🚨. He explores federated learning, edge/cloud computing ☁️, secure communication protocols, and medical image processing 🖼️ to enhance healthcare data security 🛡️. His work contributes to intelligent, privacy-preserving healthcare systems, backed by publications in high-impact journals 📘. Jamshed combines theory and application, building intelligent systems that respond to real-world threats while pushing the boundaries of AI in digital health and critical infrastructure 💡🧠.

Publication Top Notes

🔋 Voltage Stability Index using new single-port equivalent based on component peculiarity and sensitivity persistence
Year: 2021 | 📖 Cited by: 11

🌡️ Temperature field simulation and ampacity optimization of 500kV HVDC submarine transmission cable
Year: 2021 | 📖 Cited by: 10

🛰️ A UAV-Assisted Stackelberg Game Model for Securing IoMT Healthcare Networks
Year: 2023 | 📖 Cited by: 9

🌞 A Reliable Approach to Protect and Control of Wind Solar Hybrid DC Microgrids
 Year: 2019 | 📖 Cited by: 9

Conclusion

Based on his outstanding academic record, impactful research in cybersecurity and IoMT, high-quality publications in Q1 journals, and significant involvement in both funded research projects and technical roles, Jamshed Ali stands out as a highly deserving candidate for the Best Researcher Award. His work on intelligent intrusion detection systems using AI and deep learning contributes to a critical and emerging field, particularly in healthcare network security. Coupled with his strong technical proficiency, 7 years of research experience, multiple honors—including CSC scholarships and recognition as an outstanding student and speaker—Jamshed Ali exemplifies excellence in early-career research and innovation.

Rania Hamdani | Computer science | Best Researcher Award

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Mrs. Rania Hamdani | Computer science | Best Researcher Award

Mrs. Rania Hamdani, University of Luxembourg, Luxembourg

Rania Hamdani is a research scientist specializing in operational research, data management, and cloud architecture for Industry 5.0. Based in Luxembourg, she is currently affiliated with the University of Luxembourg, where she explores advanced methodologies for integrating and managing heterogeneous data sources. She holds an engineering degree in Software Engineering and has extensive experience in software development, AI, and DevOps. Rania has worked on multiple industry and academic projects, publishing three research papers in Ontology-Driven Knowledge Management and Cloud-Edge AI. With a strong background in programming, cloud computing, and AI-driven solutions, she has contributed to platforms ranging from job recommendation systems to adaptive human-computer interaction systems. Her expertise includes Python, SpringBoot, Kubernetes, and Azure DevOps. She is also an active member of IEEE and other technical organizations, promoting innovation and knowledge-sharing in AI and cloud technologies. 🌍💻🔬

Publication Profile

Orcid

🎓 Education

Rania Hamdani holds an Engineering Degree in Software Engineering from the National Higher School of Engineers of Tunis (2021–2024), where she specialized in advanced design, service-oriented architecture, object-oriented programming, database management, and operational research. Prior to this, she completed a two-year preparatory cycle at the Preparatory Institute for Engineering Studies of Tunis (2019–2021), undertaking intensive coursework in mathematics, physics, and technology to prepare for engineering studies. She also earned a Mathematics-specialized Baccalaureate from Pioneer High School Bourguiba Tunis (2015–2019), graduating with honors. Throughout her academic journey, she gained expertise in artificial intelligence, machine learning, cloud computing, and DevOps methodologies. Her education provided a solid foundation in programming languages, data processing techniques, and full-stack development. Additionally, she holds multiple Microsoft certifications in Azure fundamentals, AI, data security, and compliance, reinforcing her expertise in cloud-based solutions and AI-driven applications. 📚🎓💡

💼 Experience

Rania Hamdani is a research scientist at the University of Luxembourg, where she focuses on integrating and managing heterogeneous data sources for cloud-based decision-making. Previously, she was a research intern at the same institution, contributing to Ontology-Driven Knowledge Management and Cloud-Edge AI, with three published papers. She also worked as a part-time software engineer at CareerBoosts in Quebec (2021–2025), specializing in Python, Azure DevOps, Docker, and test automation. She gained industry experience through internships at Qodexia (Paris), Sagemcom (Tunisia), and Tunisie Telecom, working on smart recruitment platforms, employee management systems, and server monitoring solutions using SpringBoot, Angular, and PostgreSQL. Her technical expertise spans full-stack development, DevOps, AI-driven applications, and cloud computing. She has contributed to major projects, including an adaptive human-computer interaction system, a job recommendation system, and a problem-solving platform, demonstrating her versatility in research and software engineering. 🚀🖥️🔍

🏆 Awards & Honors

Rania Hamdani has been recognized for her outstanding contributions to AI-driven cloud computing and operational research. She received excellence awards during her engineering studies at the National Higher School of Engineers of Tunis and was among the top-performing students in her Mathematics-specialized Baccalaureate. Her research papers in Ontology-Driven Knowledge Management and Cloud-Edge AI have been acknowledged in academic circles, contributing to the advancement of Industry 5.0 technologies. She has also earned multiple Microsoft certifications in cloud and AI fundamentals, reinforcing her technical expertise. As an active member of IEEE and the Youth and Science Association, she has been involved in technology outreach and innovation-driven initiatives. Her leadership in ENSIT Junior Enterprise as a project manager further showcases her ability to lead and contribute to tech communities. These recognitions highlight her dedication to research, software development, and cloud-based AI applications. 🏅📜🌟

🔬 Research Focus

Rania Hamdani’s research focuses on operational research, data management, cloud-edge AI, and Industry 5.0 applications. She specializes in ontology-driven knowledge management, exploring methodologies for integrating heterogeneous data sources to optimize cloud-based decision-making processes. Her work includes artificial intelligence, machine learning, reinforcement learning, and human-computer interaction systems. She has contributed to projects involving job recommendation systems, adaptive human-computer interaction platforms, and cloud-based problem-solving platforms. Rania is particularly interested in scalable cloud architectures, leveraging technologies like FastAPI, Kubernetes, Docker, and Azure DevOps to build efficient AI-powered solutions. Her research also integrates graph databases, Apache Airflow, and big data analytics for enhanced data processing. By combining AI and cloud computing, she aims to develop innovative, data-driven solutions for automation, decision support, and optimization in various industrial applications. Her expertise bridges the gap between theoretical research and real-world software engineering. ☁️🤖📊

 

Publication Top Notes

Adaptive human-computer interaction for industry 5.0: A novel concept, with comprehensive review and empirical validation

 

Ahcene Bounceur | Cybersecurity | Best Researcher Award

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Dr. Ahcene Bounceur | Cybersecurity | Best Researcher Award

Associate Professor at  University of Sharjah, United Arab Emirates.

Dr. Ahcene Bounceur is an Associate Professor at the University of Sharjah, specializing in cybersecurity, IoT, smart cities, and data science. Previously, he held faculty positions at KFUPM and University of Western Brittany (UBO), where he was a senior associate professor and qualified for professorship .He earned his Ph.D. in Micro and Nano Electronics from Grenoble INP, France, in 2007 and an HDR (State PhD) in Computer Science in 2014. His research includes Digital Twin tools for smart infrastructure security, pseudo-polygons for cybersecurity, and simulation tools for WSN and IoT. Dr. Bounceur is the main developer of Cup Carbon, a renowned IoT network simulator, and has led projects like ANR PERSEPTEUR and Suidia. He has 200+ publications, served as a keynote speaker, and held editorial roles in journals like MDPI Sensors. Recognized for his contributions, he won 3rd place in the IEEE TTTC Doctoral Thesis Contest and holds a patent for an IoT-based digital health platform.

Publication Profile

Scopus

🎓Academic Qualifications of Ahcene Bounceur

Dr. Ahcene Bounceur is a distinguished computer scientist with expertise in microelectronics, data mining, and wireless sensor networks. He earned his HDR (State PhD) in Computer Science from the University of Western Brittany (UBO) in 2014, focusing on models and simulation for mixed circuit testing. In 2007, he obtained a PhD in Micro and Nanoelectronics from the TIMA Laboratory (Grenoble), specializing in computer-aided test platforms. His M.Sc. in Operations Research (2003) and Engineering degree (2002) were awarded in Grenoble and Bejaia, respectively. Additionally, he gained early programming experience in 1995 at the Micro-Services School of Béjaia. 💻📡

Professional Background

Dr. Ahcene Bounceur is an Associate Professor at the University of Sharjah (2024–Present) and previously held the same role at KFUPM (2023–2024). Since 2014, he has been qualified for professorship at the University of Western Brittany (UBO), where he served as a Senior Associate Professor (2020–2023) and Associate Professor (2008–2020). His earlier roles include Assistant Professor at ENSERG (2007–2008) and Postdoctoral Researcher at TIMA Laboratory (2006–2007). He has also held leadership roles, including Head of Computer Science at UBO (2011–2023) and Member of France’s National Council of Universities (2021–2023). 🏫📡

🔬 Research Focus of Ahcene Bounceur

Dr. Ahcene Bounceur’s research spans Artificial Intelligence , Cybersecurity , Data Mining , and Circuit Testing . Since 2012, he has focused on Collaborative AI (CupCarbon Klines simulator), Digital Twin IoT for cybersecurity in critical infrastructures, pseudo-polygons for polygonal hull determination, and statistical modeling for sensor networks. From 2002–2012, his work emphasized manufacturing process variations, Monte Carlo simulations for test metrics, and non-linear circuit modeling using copula theory. His interdisciplinary expertise integrates AI, IoT, cybersecurity, and statistical modeling to enhance smart infrastructures and sensor networks. 🚀📡

Publication Top Notes

🔹 A Secure and Lightweight ZKP-based Mutual Authentication Scheme with Key Agreement
      Year: 2025 |  Arabian Journal for Science and Engineering |

🔹 Integrating Homomorphic Encryption in IoT Healthcare Blockchain Systems
      Year: 2024 | Ingenierie des Systemes d’Information |

🔹 Blockchain Use Cases in the Sports Industry: A Systematic Review
     Year: 2024 |  International Journal of Networked and Distributed Computing | 🔍 Citations: 3

Conclusion

Ahcene Bounceur is a distinguished researcher with a strong record of high-impact publications, including multiple papers in Q1 journals, some ranking in the top 4%, 8%, and 12%, highlighting his significant research influence. His expertise spans diverse areas such as watermarking, wireless sensor networks (WSN), digital twins, security protocols, data mining, and circuit design, demonstrating interdisciplinary proficiency. His recent and consistent contributions, particularly in 2024 and 2025, reflect his sustained excellence in research. Additionally, his collaborations with leading researchers and institutions showcase his global research impact and networking strength. These achievements make him a strong contender for the Best Researcher Award. 🚀

 

 

 

Victormills Iyieke | Computer and Security | Best Researcher Award

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Mr. Victormills Iyieke | Computer and Security | Best Researcher Award

Mr. Victormills Iyieke, Coventry University, United Kingdom

Mr. Victormills Iyieke is a Chartered Engineer with a strong background in automotive cybersecurity and system architecture. He holds a PhD in Automotive Cybersecurity Engineering from Coventry University and has over 10 years of experience in the automotive industry. Currently, he works as a System Architecture Engineer at Renault Group, specializing in OTA updates and cybersecurity. He has contributed to major projects with companies like EDAG Engineering, Jaguar Land Rover, and Aston Martin. His expertise includes ISO standards, MBSE, and secure software updates. Outside work, he enjoys meeting new people and exploring new adventures. 🚗🔐🛠️

 

Publication Profile

Orcid


Education and Qualifications

Mr. Victormills Iyieke has a robust educational background in engineering and management. He is currently pursuing a PhD in Secured-by-Design (Automotive Cybersecurity Engineering) at Coventry University (2020-2024). He holds a Master of Science (MSc) in International Business and Management from the University of Bedfordshire (2011-2012) and a Bachelor of Science (BSc) in Electrical and Electronics Engineering from the European University of Lefke (2006-2010). Additionally, Mr. Iyieke is certified by the International Software Testing Qualifications Board (ISTQB) in 2016. 🎓🔒📚

 

Career Experience

Mr. Victormills Iyieke has extensive experience in system architecture, automotive cybersecurity, and embedded systems. Since November 2022, he has worked as a System Architecture Engineer at Renault Group (via Capgemini Engineering), focusing on OTA updates and cybersecurity. His role involves creating offboard system architectures, managing cryptographic materials, and utilizing MBSE for OTA campaigns. Mr. Iyieke has also worked as a Doctorate Student Researcher at Coventry University, assessing secured automotive safety-critical components. Previously, he held positions at EDAG Engineering Limited, Jaguar Land Rover, Volkswagen Group, Bentley Motors, and Aston Martin Lagonda, specializing in system integration, software updates, and functional testing. 💼🔧🚗

 

Training & Skills

Mr. Victormills Iyieke has received extensive training in advanced engineering tools and methodologies. He is proficient in RMDV (DOORS and RTC), SysML, and system modeling using Rhapsody and Enterprise Architecture. His expertise includes FMEA (Failure Mode and Effect Analysis) and AUTOSAR integration. Mr. Iyieke is skilled in using Vector tools such as CANoe and CANalyzer for system testing and analysis. He excels in engaging stakeholders, working with engineers and managers to define and respond to change requests. His system thinking and creativity are key in aligning platform managers and teams for advanced electrical architecture planning. 💡🔧📊

 

Research Focus

Mr. Victormills Iyieke’s research primarily focuses on automotive cybersecurity and secure communication systems for modern vehicles. His work emphasizes Over-the-Air (OTA) updates, ensuring their security through Security-by-Design principles. He is also involved in remote monitoring and teleoperation of autonomous vehicles, exploring innovative solutions for secure vehicle operations and data integrity. His expertise spans vehicle network security, cyber-physical systems, and secure software updates in automotive systems. His research contributes to enhancing vehicle safety and security in the rapidly advancing field of autonomous and connected vehicles. 🚗🔐💻📡

 

Publication Top Notes

  • An Adaptable Security-by-Design Approach for Ensuring a Secure Over the Air (Ota) Update in Modern Vehicles. (2024)
  • An Adaptable Security by Design Approach for Ensuring a Secured Remote Monitoring Teleoperation (RMTO) of an Autonomous Vehicle. (2023)

Noor .A. Rashed | Computer Science Award | Women Researcher Award

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Dr . Noor .A. Rashed | Computer Science Award | Women Researcher Award

Dr. Noor Rashid, Iraq

Dr. Noor Rashid is a Ph.D. candidate at the University of Technology, Baghdad, specializing in Computer Science. She earned her master’s degree from the University of al-Anbar in 2018. Her research covers areas such as Artificial Intelligence, secure data systems, machine learning, data mining, image processing, and project management automation. Her current focus is on optimization algorithms, particularly multi-objective optimization (2022-2023). Dr. Rashid has contributed significantly to the field, including her recent publication on evolutionary and swarm-based algorithms. She continues to advance AI and optimization research in her academic journey.

 

Publication profile

Google Scholar

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Employment

Dr. Noor Rashid is currently employed at the University of Technology, Baghdad, Iraq, in the Department of Computer Science. As a dedicated researcher and educator, she contributes to the university’s mission by advancing studies in Artificial Intelligence, secure data systems, and optimization algorithms. Her role involves teaching and mentoring students while conducting innovative research in multi-objective optimization and machine learning. Dr. Rashid’s work continues to impact both the academic community and the broader technological landscape through her involvement in cutting-edge computer science projects.

 

Education and Qualifications 🎓📜

Dr. Noor Rashid is currently pursuing her Ph.D. in Computer Science at the University of Technology, Baghdad, Iraq, from November 2021 to November 2024. Her doctoral research focuses on advanced areas such as optimization algorithms and Artificial Intelligence, contributing to cutting-edge technological advancements. Prior to this, Dr. Rashid earned her master’s degree from the College of Computer Science and Information Technology at the University of al-Anbar in 2018. Her academic background equips her with a strong foundation in secure data, machine learning, and project management systems, preparing her for continued success in the field.

 

Research Focus 🎯🔬

Dr. Noor Rashid’s research primarily focuses on Artificial Intelligence (AI), particularly in machine learning, optimization algorithms, and data mining. Her studies delve into complex areas such as multi-objective optimization and evolutionary algorithms, aiming to solve real-world computational problems. Additionally, Dr. Rashid has worked extensively on medical image processing, applying AI techniques like ANN and SVM to detect and classify diseases like diabetic retinopathy. Her research bridges the gap between AI and healthcare, making significant contributions to secure data, networks, and advanced algorithmic developments. 🚀🧠

 

Publication Top Notes

  • Diagnosis retinopathy disease using GLCM and ANN – N. Rashed, S. Ali, A. Dawood – J. Theor. Appl. Inf. Technol 96, 6028-6040, 2018 (Cited by: 4) 📖
  • Unraveling the Versatility and Impact of Multi-Objective Optimization: Algorithms, Applications, and Trends for Solving Complex Real-World Problems – N.A. Rashed, Y.H. Ali, T.A. Rashid, A. Salih – arXiv preprint, 2024 (Cited by: 2) 🌐
  • Advancements in Optimization: Critical Analysis of Evolutionary, Swarm, and Behavior-Based Algorithms –  Rashed, Y.H. Ali, T.A. Rashid – Algorithms 17(9), 416, 2024 📑
  • ANN and SVM to recognize Texture features for spontaneous Detection and Rating of Diabetic Retinopathy –  Rashed (Upcoming) 🔍