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

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

Mrs. Menatalla Abououf | Event Detection Award | Best Researcher Award

Mrs. Menatalla Abououf, Khalifa University, United Arab Emirates

Menatalla Abououf is a Research Engineer at Khalifa University’s Center for Cyber-Physical Systems in Abu Dhabi, UAE. With a Master’s degree in Electrical and Computer Engineering, she has over five years of experience in cyber security research, teaching, and curriculum development. Her expertise spans software and hardware, including AI, IoT, and blockchain. She’s published in esteemed journals, presented at conferences, and received awards for her contributions to IoT data monetization and more. Fluent in English and Arabic, Menatalla is known for her adaptability, leadership, and commitment to advancing technology. 🌟🔒🔬

Publication Profile

Google Scholar

Education and Qualification

👩‍💼 Mrs. Menatalla Abououf brings over five years of versatile experience as a researcher, lab engineer, and teaching assistant, specializing in areas like Penetration Testing, Digital Forensics, and Advanced Operating Systems. Her extensive technical expertise spans both software and hardware domains, encompassing HPC, Kali Linux, Matlab, Python, C++, Assembly, Verilog, HTML, and CSS. Committed to advancing cybersecurity, she delivers training courses in related topics and pursues research in artificial intelligence, cyber security, crowdsensing/sourcing, internet of things, and blockchain. With a Master’s degree in Electrical and Computer Engineering and a Bachelor’s degree in Electrical and Electronic Engineering, both from Khalifa University, she maintains a stellar academic record with a GPA of 3.96 and 3.89, respectively. 🎓

Professional Experience

👩‍💼 Menatalla Abououf has amassed a rich professional portfolio, showcasing her expertise and dedication across various roles. As a Research Engineer at the Center for Cyber-Physical Systems, Khalifa University, she spearheads research on privacy and security in cyber-physical systems, while also serving as a pivotal figure in the Information Security department, contributing as a teaching assistant and lab engineer. Her commitment extends beyond academia, as seen in her role as a Trainer at the Cyber Security Academy, where she imparts knowledge and fosters practical skills in cybersecurity. Additionally, her contributions to curriculum development with the Ministry of Education reflect her commitment to shaping future generations. Her multifaceted roles as a Project Manager, Teaching Assistant, and Expert Judge underscore her versatility and leadership in various capacities within the educational and technological landscape. 🌐

Achievements

🏆 Menatalla Abououf’s achievements reflect her consistent dedication to academic excellence and professional growth. She received the prestigious IET Networks Premium Award for her outstanding paper on ‘Monetization of IoT data using smart contracts,’ showcasing her innovative contributions to the field. Her academic journey was marked by accolades such as the Khalifa University Scholarship and being designated a Top 20 student, President’s List, and Dean’s List awardee, demonstrating her exceptional academic performance. Additionally, her participation in competitions like the Khalifa University Programming Contest and Gulf Programming Contest highlights her prowess in problem-solving and programming. These achievements, coupled with her non-academic awards and professional certifications, underscore her commitment to excellence. 🎓

Research Focus

🔍 Menatalla Abououf’s research focus revolves around leveraging advanced technologies, particularly in artificial intelligence and machine learning, to address critical challenges in cyber-physical systems, mobile crowd sensing, and IoT monetization. Her work spans various domains, including privacy and security enhancement in cyber-physical systems, anomaly detection in IoT devices, and behavior-based recruitment models in mobile crowd sourcing. Through her publications and contributions to prestigious conferences, she has demonstrated a deep understanding of these areas and a commitment to advancing knowledge in the field. Her interdisciplinary approach underscores her versatility and dedication to tackling complex issues at the intersection of technology and society. 🌐