I'm a research scientist working in low-level vision, signal processing and security. My work addresses problems at the intersection of multimedia and security, with particular focus on verification and assurance of media integrity. This interdisciplinary field combines concepts from computer vision, image processing, image quality assessment, machine learning, statistical signal processing, and communication & information theory.

If you’d like to know more about the field, feel free to check out my recent survey. If you'd like to experiment with some of the techniques that I was/am working on, the best place to start is the featured content below and my github profile. The publications section also lists supplementary materials and source code that accompanies specific papers.

I'm currently working with prof. Nasir Memon on modeling and optimization of photo acquisition and distribution pipelines to inform development of media authentication capabilities in next-generation systems. I did my post-doctoral research on forensic photo manipulation detection with prof. Jiwu Huang at the Key Laboratory of Media Information Content Security at Shenzhen University, China. My doctoral work was under the supervision of prof. Andrzej Dziech at the Department of Telecommunications of AGH University of Science and Technology, Kraków, Poland. I used tools from communication and information theory to design new techniques for photo authentication and restoration based on digital watermarking.

I currently serve the research community as a reviewer for technical journals and conferences and as a member of the IEEE Information Forensics and Security Technical Committee.

Research Interests

low-level vision · machine learning · image processing · multimedia security · forensics · media integrity · communications

Featured Content

neural imaging toolbox

Modeling and optimization of complex photo acquisition and distribution channels

cvpr'19 · arxiv'19 · iclr'20

lightweight learned lossy image codec

Lightweight codec with good rate-distortion performance (~BPG) and fast runtime

iclr'20

multi-scale tampering localization

Improved tampering localization thanks to multi-scale analysis and decision fusion

tip'16 · wifs'16 · tifs'17 · arxiv'18

photo integrity survey

Overview of techniques for verification and active protection of digital photographs

dsp'17

realistic tampering dataset

220 realistic forgeries created by hand in modern photo-editing software

wifs'16 · tifs'17

self-recovery of digital photos

Detailed study and practical demonstration of various edit recovery schemes

tip'13 · tifs'14 · wifs'14 · tmm'15

Media Coverage

• wired.com: To Fight Deepfakes, Researchers Built a Smarter Camera
• gizmodo.com: Researchers Want to Build Fake Photo Detection Tools Right Into Our Cameras
• photonics.com: AI-Driven Imaging System Protects Photo and Video Authenticity End-to-End
• verdict.co.uk: Fighting fake news with anti-deepfake technology
• helpnetsecurity.com: Researchers spot manipulated photos and video using AI-driven imaging system
• engineering.nyu.edu: Outsmarting deep fakes: Researchers devise an AI-driven imaging system that protects authenticity
• pdnonline.com: Your Future Camera May Watermark Images Automatically, Whether You Want It To or Not