Jiameng Pu

Jiameng Pu is a Researcher in the Department of Computer Science at Virginia Tech, part of the College of Engineering. Their research focuses on cybersecurity, deep learning, and adversarial machine learning, with notable contributions to deepfake detection and AI robustness. Pu holds a Ph.D. in Computer Science and Applications from Virginia Tech (2017–2022) and a B.E. in Computer Science and Technology from Wuhan University (2013–2017).

Education:

• Ph.D. in Computer Science and Applications, Virginia Tech (2017–2022)
• B.E. in Computer Science and Technology, Wuhan University (2013–2017)

Research Interests: Pu’s work addresses cutting-edge challenges in cybersecurity, including detecting deepfake content (text, images, and videos), defending against adversarial attacks on AI models, and improving robustness in medical imaging systems. Their research combines techniques from machine learning, computer vision, and data mining to enhance security and reliability in AI applications.

Key Publications: Pu has authored influential papers on deepfake detection (IEEE S&P 2023, WWW 2021) and AI security (USENIX Security 2021, EuroS&P 2020). Their work spans theoretical advancements and practical tools like NoiseScope for blind deepfake image detection.

Awards:

• Dr. Dennis Kafura Graduate Fellowship (2022)
• Nominated for 2021 PhD Fellowship Awards (Facebook Visa Research Scholarship)
• IEEE S&P 2020 Student Travel Grant
• NDSS 2019 Student Travel Grant
• National Endeavor Fellowship (Twice), Chinese Ministry of Education

Pu’s professional experience includes software engineering at Facebook (2021) and data science roles at IBM and Wuhan University labs. They actively collaborate with industry and academia to advance AI security and ethical AI practices.