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Danish Attique is an Assistant Professor in the Department of Computer Science at Bahria University Lahore Campus, Pakistan. He received his Ph.D. in Computer Science and Technology from Chongqing University of Posts and Telecommunications, China, in 2024, following an M.Eng. in Information and Communication Engineering from Southwest University of Science and Technology, China, in 2020, and a B.Eng. in Computer Systems Engineering from Mirpur University of Science & Technology, Pakistan, in 2014.
His research is primarily focused on cybersecurity for Industrial IoT (IIoT), deep learning-based intrusion detection systems, federated learning, and Explainable AI (XAI). He has developed novel methodologies for enhancing IIoT security through decentralized learning techniques, with his work featured in the IEEE Internet of Things Journal, among other high-impact international publications. His contributions include deep-learning-driven anomaly detection, fog-assisted security architectures, and hybrid AI-based threat mitigation strategies for resource-constrained IIoT environments.
Beyond academia, Danish has industry experience as an IT Security Analyst, where he specialized in penetration testing, threat modeling, and network security policy development. He has also served as a Computer Science Instructor, designing and delivering courses in computer networks.
Danish has received multiple competitive academic scholarships and has held leadership roles, including serving as President of the International Student Union at CQUPT. He holds professional certifications such as Cisco Certified Network Associate (CCNA) and Microsoft Certified Solutions Expert (MCSE).
With a strong research portfolio and a commitment to advancing AI-driven cybersecurity solutions, Danish continues to contribute to the academic and professional community by mentoring students, publishing in prestigious venues, and developing innovative approaches to securing next-generation IIoT ecosystems. |
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