Taha Khan
Associate Teaching Professor, Information Networking Institute
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Contact
4616 Henry Street
Pittsburgh, PA 15213
4616 Henry Street
Pittsburgh, PA 15213
Bio
Taha Khan is an Associate Teaching Professor at the Information Networking Institute at Carnegie Mellon University (CMU). Khan’s research interests span usable security and privacy, measuring cybercrime, trustworthy AI, online censorship and computer science education. His work focuses on understanding how people interact with security systems and designing tools that are secure and robust. Khan earned his Ph.D. in Computer Science from the University of Illinois at Chicago and holds a B.S. in Electrical Engineering from the Lahore University of Management Sciences. Prior to joining CMU, he held a faculty appointment in the Computer Science Department at Washington and Lee University and an adjunct position at Virginia Tech. He also consults for small-scale startups and, in the past, has provided expert guidance on security and AI to companies in industries ranging from blockchain, finance and insurance, to cyber-physical systems. Khan brings a dynamic, active-learning approach to the classroom. He has taught courses ranging from introductory programming and hardware organization to systems, security, networks, programming languages, and databases. He is passionate about cultivating deeper understanding through hands-on learning that empowers the next generation of technologists.Education
Ph.D. Computer Science, University of Illinois at Chicago, 2020
B.S. Electrical Engineering, Lahore University of Management Sciences, 2013
Research
Areas of Interest: Khan’s recent work explores a range of empirical cybersecurity challenges, particularly those involving user behavior, system transparency and privacy in real-world contexts. His work has been published in top-tier venues, including IMC, CHI, CCS, USENIX Security and IEEE S&P. He has led projects developing learning-based tools to automatically identify and manage sensitive files in cloud storage, studied privacy management on social media and conducted large-scale analysis of the security and performance of the commercial VPN ecosystem. His work also includes reverse-engineering mobile applications to uncover surveillance risks, and examining how users in different cultural contexts respond to online censorship. More recently, he has explored the use of large language models for secure and effective code debugging.Looking ahead, Khan is excited to continue advancing his work in security and privacy while also exploring areas that align with the safe and effective use of AI. He is particularly interested in emerging challenges from AI in cyber forensics and blockchain-based verification. He remains deeply committed to mentoring students, actively guiding them in conducting impactful and socially relevant research.