Ahcene Bounceur | Cybersecurity | Best Researcher Award

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. 🚀

 

 

 

Jing Li | Cybersecurity | Best Researcher Award

Dr. Jing Li | Cybersecurity | Best Researcher Award

Dr. Jing Li, University Technology Malaysia, China

🎓 Dr. Jing Li is pursuing his PhD in Computer Science at University Technology Malaysia (UTM) since 2021. He holds a Master’s in Information Management from ZheJiang University and a Bachelor’s in Computer Science from China JiLiang University. With over 15 years in the ICT industry, he specializes in networking, cybersecurity, and IoT. His research interests span IoT security, digital forensics, big data, and machine learning. Dr. Li has authored several publications in prestigious journals and is an active member of IEEE. He is also proficient in AI-based scientific research tools

Publication profile

Scopus

Education 🎓

Dr. Jing Li is currently pursuing his PhD in Computer Science at University Technology Malaysia (UTM), where he also holds an International Doctoral Scholarship. He earned his Master’s degree in Information Management from ZheJiang University and a Bachelor’s in Computer Science from China JiLiang University, Hangzhou.

Professional Experience 💼

Dr. Li has held roles including Technical Co-founder at Hangzhou Yunmei Technology Co., Ltd., Product Architect at ArcSoft (Hangzhou) Technology Co., Ltd., and Software Engineer at Aerohive Networks, inc. His expertise spans networking, cybersecurity, IoT, and machine learning.

Research Focus

Dr. Jing Li’s research focuses on enhancing IoT security through advanced machine learning techniques. His work primarily explores feature selection and reduction methods for improving intrusion detection systems in IoT environments. Through critical reviews and comparative studies, Dr. Li aims to optimize classification models, contributing significantly to the fields of cybersecurity and digital forensics. His research, published in prestigious journals like the Journal of Big Data and Intelligent Systems with Applications, underscores his expertise in applying AI-driven solutions to mitigate IoT security risks. Dr. Li’s efforts are pivotal in advancing the understanding and implementation of robust security measures in interconnected systems. 🔒

Publication Top Notes

Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning

Enhancing IoT security: A comparative study of feature reduction techniques for intrusion detection system

A critical review of feature selection methods for machine learning in IoT security