Jing Li | Deep Learning for Cybersecurity | Best Paper Award

Dr. Jing Li | Deep Learning for Cybersecurity | Best Paper Award

 Researcher at University Technology Malaysia, China

Summary:

Dr. Jing Li is a dedicated computer scientist currently pursuing a PhD in Computer Science at University Technology Malaysia. His research interests encompass networking, Internet of Things, machine learning/deep learning, cybersecurity, and big data. He has achieved academic excellence, being awarded the International Doctoral Scholarship (IDF) for the periods 2022-2023 and 2023-2024. Dr. Li holds a Master’s degree in Information Management from Zhejiang University, where he was recognized with the First Prize for his entrance essay submission and conducted research on “Hangzhou Wireless City Construction Planning.” He completed his Bachelor’s degree in Computer Science and Technology at China Jiliang University, distinguished as a four-time scholarship recipient.

Profile:

Education:

Dr. Jing Li is currently pursuing a PhD in Computer Science at University Technology Malaysia, focusing on networking, Internet of Things, machine learning/deep learning, cybersecurity, and big data. He has been awarded the prestigious International Doctoral Scholarship (IDF) for the academic years 2022-2023 and 2023-2024. Prior to this, he earned a Master’s degree in Information Management from Zhejiang University, where he received the First Prize for his entrance essay submission and completed a thesis titled “Research on Hangzhou Wireless City Construction Planning.” Dr. Li also holds a Bachelor’s degree in Computer Science and Technology from China Jiliang University, where he was a four-time scholarship winner.

Professional Experience:

Dr. Jing Li brings a wealth of professional experience in the technology sector, having held significant roles across various organizations. He started his career as a Software Engineer at UTStarcom (China) Co., Ltd., where he gained foundational experience from June 2003 to June 2006. He then progressed to roles with increasing responsibility, serving as a Software Engineer/Product Architect at Aerohive Networks, Inc. from June 2006 to September 2014, focusing on networking solutions. Subsequently, Dr. Li joined ArcSoft (Hangzhou) Technology Co., Ltd. as a Product Architect from June 2014 to June 2018, where he contributed to product development and architecture. His entrepreneurial spirit led him to co-found Hangzhou Zijie Technology Co., Ltd., where he served as Technical Co-founder from June 2018 to 2021, involved in the strategic and technical leadership of the company. Throughout his career, Dr. Li has demonstrated expertise in Python, C++, and C, alongside a profound understanding of networking, Internet of Things, machine learning/deep learning, cybersecurity, and big data applications.

Research Interests:

Dr. Jing Li’s research interests are centered around several key areas in computer science and technology. His primary focus lies in networking, where he explores advancements in network protocols, architectures, and performance optimization. Dr. Li is also deeply engaged in the Internet of Things (IoT), investigating methods to enhance IoT device connectivity, security, and data management. His expertise extends to machine learning and deep learning applications, particularly in developing intelligent algorithms for data analysis and decision-making processes. Additionally, Dr. Li is passionate about cybersecurity, researching techniques to safeguard networks and IoT ecosystems from emerging threats. Finally, he explores big data analytics, aiming to develop scalable and efficient algorithms for processing and extracting valuable insights from large datasets.

Skills:

Dr. Jing Li is equipped with a comprehensive skill set that spans diverse areas within computer science and technology. His expertise includes advanced proficiency in networking, encompassing thorough knowledge of network protocols, architectures, and optimization strategies. Dr. Li demonstrates a deep understanding of Internet of Things (IoT), where he excels in enhancing device connectivity, ensuring robust security measures, and optimizing data management systems. His proficiency extends to machine learning and deep learning, where he develops and implements sophisticated algorithms for data analysis and decision-making tasks. Additionally, Dr. Li is adept in cybersecurity practices, employing effective techniques to safeguard networks and IoT environments from evolving threats. His skills in big data analytics enable him to design and implement scalable algorithms that efficiently process and derive valuable insights from large datasets. With fluency in programming languages such as Python, C++, and C, Dr. Li leverages his technical acumen to drive innovation and contribute significantly to research and development initiatives in his field.

Peer Reviewer in Journals:

Dr. Jing Li has served as a peer reviewer for prestigious journals in the fields of computer and electrical engineering. His expertise as a reviewer extends to journals such as Expert Systems With Applications, Knowledge-Based Systems, Journal of Ambient Intelligence and Humanized Computing, Journal on Internet of Things, International Journal of Electrical and Computer Engineering, International Journal on Data Science and Technology, and Journal of Applied Engineering and Technological Science. Through his role, Dr. Li contributes to maintaining the quality and integrity of research in these specialized domains, ensuring rigorous evaluation and feedback for scholarly publications.

Awards & Honors:

Dr. Jing Li has garnered significant recognition for his contributions in computer science and technology. He has served as a peer reviewer for esteemed journals including Expert Systems With Applications, Knowledge-Based Systems, and Journal of Ambient Intelligence and Humanized Computing, among others. In 2023, Dr. Li was appointed as a Professor Assistant for AI-SLR courses at UTM, showcasing his expertise and leadership in the field. His commitment to academic excellence is further underscored by his involvement in committees such as the EGE Committee Technical Team and PARS2023/2024 Committee Publication and Technical Team. In 2024, Dr. Li was honored with the Asian Youth Leaders Scholarship Award, reflecting his outstanding achievements and dedication to advancing research and education in computer and electrical engineering.

Publications:

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

  • Authors: J. Li, M.S. Othman, H. Chen, L.M. Yusuf
  • Journal: Journal of Big Data
  • Year: 2024
  • Volume and Issue: 11(1)
  • Pages: 36
  • Citations: 3

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

  • Authors: J. Li, H. Chen, M.O. Shahizan, L.M. Yusuf
  • Journal: Intelligent Systems with Applications
  • Year: 2024
  • Volume and Issue: 23
  • Article Number: 200407
  • Citations: 0

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

  • Authors: J. Li, M.S. Othman, H. Chen, L.M. Yusuf
  • Journal: International Journal of Communication Networks and Distributed Systems
  • Year: 2024
  • Volume and Issue: 30(3)
  • Pages: 264-312
  • Citations: 0

Oluwafemi Oke | Intrusion Detection | Best Researcher Award

Mr. Oluwafemi Oke | Intrusion Detection | Best Researcher Award

PhD, Near East University, Cyprus

🏆 Mr. Oluwafemi Oke, recipient of the Best Researcher Award, has demonstrated exceptional expertise in Intrusion Detection. Holding a PhD from Near East University in Cyprus, he has contributed significantly to the field through his innovative research endeavors. Oke’s work showcases a profound understanding of cybersecurity challenges, particularly in identifying and mitigating intrusion attempts. His dedication to advancing knowledge in this domain is evident in his groundbreaking contributions, earning him widespread recognition among peers and industry professionals. Oke’s accomplishments serve as a testament to his unwavering commitment to excellence and his invaluable contributions to the field of cybersecurity. 🌟

Profile

Orcid

Research Experience

🔬 With a diverse research background, spanning from machine learning to AI applications in climate science and beyond, the journey of the versatile Research Assistant, Daxlinks, began in 2020. Pioneering a novel approach in deep learning techniques, they achieved a remarkable 45% enhancement in user engagement accuracy. Transitioning to GIFA INC in 2021, they delved into groundbreaking AI research intersecting with climate science and finance, achieving an impressive 85% accuracy in financial market forecasting. Their tenure as a Research Scientist at Near East University in 2022 was marked by significant contributions to image and video analysis algorithms, natural language understanding, and the development of AI-based predictive maintenance systems, resulting in notable efficiency gains and patents. 🚀

Professtional Experience

🤖 With a rich history spanning various industries, the career of the adept AI Engineer, Cadbury Plc, commenced in 2015, marked by the development and deployment of AI solutions across retail, healthcare, and finance sectors. Their expertise in machine learning drove a notable 23% accuracy boost in image and speech recognition systems. Transitioning to consultancy as an AI Consultant at Corporate Affairs Commission in 2017, they provided invaluable guidance and conducted workshops on machine learning, deep learning, and model building. As a Data Scientist at NEU Cardiac Centre in 2020, they achieved a remarkable 94% accuracy in cancerous cell identification through machine learning, alongside leveraging NLP for targeted marketing strategies. Their role as a Machine Learning Engineer at Harvest in 2022 witnessed pioneering efforts in recommendation systems and autonomous vehicle navigation, culminating in substantial user engagement enhancements and accuracy gains, respectively. 🚀

Education

🎓 With an impressive academic journey, the individual commenced their educational pursuit at Babcock University in July 2016, earning a Bachelor of Science in Computer Engineering. Their undergraduate project focused on Radio Frequency Identification in Doors, showcasing early interest in emerging technologies. Advancing their expertise, they pursued a Master of Science in Computer Science (Software Engineering) at Babcock University, completing in August 2020, with a project titled Hybrid Intelligent Internet of Things (IoT) Systems for Automated Homes, highlighting a fusion of IoT and intelligent systems. Currently, they are pursuing a Doctor of Philosophy in Computer Information Systems (Artificial Intelligence) at Near East University, marking a dedication to advancing knowledge in AI. 📚

Publications 

Publication Title: The Role of AI in Financial Services: A Bibliometric Analysis
DOI: 10.1080/08874417.2024.2304545
Year: 2024
Journal: Journal of Computer Information Systems

Publication Title: THE IMPACT OF ARTIFICIAL INTELLIGENCE IN FOREIGN LANGUAGE LEARNING USING LEARNING MANAGEMENT SYSTEMS: A SYSTEMATIC LITERATURE REVIEW
DOI: 10.33407/itlt.v95i3.5233
Year: 2023
Journal: Information Technologies and Learning Tools