Matthew Stamm

Matthew Stamm is an Associate Professor at Drexel University's College of Engineering, specializing in Electrical and Computer Engineering through the Multimedia and Information Security Lab (MISL). His work bridges signal processing, machine learning, and information security to detect multimedia forgeries and develop anti-forensic countermeasures.

• Education: PhD, MS, BS from University of Maryland, College Park

Research Interests focus on Information Forensics, including synthetic media detection, deepfake analysis, adversarial dynamics, and forensic algorithm optimization. His lab explores techniques to identify AI-generated content using statistical fingerprints and scene context.

Recent Publications (2025-2023) emphasize synthetic audio/video detection, forensic self-description methods, and adversarial attack mitigation. These works often leverage deep learning architectures and ensemble approaches for robust identification.

Scientific Awards
• 2016 NSF CAREER Award
• 2017 Drexel College of Engineering Outstanding Early-Career Research Achievement
• Dean's Doctoral Research Award (University of Maryland)
• Ann G. Wylie Dissertation Fellowship
• Clark School of Engineering Future Faculty Fellowship
• Distinguished Teaching Assistant Award

Service Roles include General Chair of ACM Workshop on Information Hiding and Multimedia Security (2017), lead organizer for IEEE Signal Processing Society's Student Competition (2018), and member of the Information Forensics and Security Technical Committee. He has received funding from NSF, DARPA, ARO, and DFBA.