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Farid: Digital image forensics

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farid.berkeley.edu·farid.berkeley.edu/

Farid's research is relevant to AI safety discussions about synthetic media, epistemic harm, and the need for detection tools as generative AI capabilities advance; his homepage links to publications, tools, and policy commentary.

Metadata

Importance: 52/100homepage

Summary

Hany Farid is a UC Berkeley computer science professor and leading researcher in digital forensics, focusing on computational methods to detect manipulated photos, deepfakes, and AI-generated synthetic media. His work is foundational to the technical field of media authentication and misinformation detection. He also engages in policy discussions around platform accountability and digital trust.

Key Points

  • Pioneered computational techniques for detecting image and video manipulation, including deepfakes and AI-generated synthetic media.
  • Research spans forensic analysis of photos, videos, and documents to establish authenticity in legal, journalistic, and security contexts.
  • Engages with policy and governance issues around platform responsibility for hosting manipulated or harmful content.
  • Work is directly relevant to AI safety concerns about epistemic integrity and the societal harms of synthetic media at scale.
  • Serves as a public expert witness and advisor on digital forensics cases involving media authenticity.

Review

Hany Farid has established himself as a leading researcher in digital forensics, with groundbreaking work across multiple domains including deepfake detection, photo manipulation forensics, and understanding human perception. His research bridges technical computational methods with critical societal implications, particularly addressing the challenges of misinformation and AI-generated media. Farid's methodological approach combines advanced computational techniques with perceptual studies, examining not just how to detect manipulated media, but also how humans perceive and interact with potentially fraudulent content. His work spans multiple disciplines, from computer vision and machine learning to cognitive psychology, providing comprehensive insights into the emerging challenges of digital media authenticity.

Cited by 2 pages

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Hany Farid 
 
 
 
 

 

 

 
 

 
 
 
 
 
 
 
 
 
 
 
 
 HANY FARID 
 
 Contact & CV |
 Bio 

 pronunce: Ha [ha-ha] - ny [knee] - Fa [far] - rid [read] 
 

 
 

 
 
 
 GROUP 
 
 Sarah Barrington | alumni | prospective students 
 
 
 &nbsp 
 
 TEACHING 
 
 Learn Computer Vision [ video tutorials ]
 
 
 
 
 Learn to Code in Python [ video tutorials ]
 
 
 
 
 Physics-Based Photo Forensics [ video tutorials ]
 
 
 &nbsp 
 
 
 PAPERS 
 
 
 digital forensics |
 forensic science |
 misinformation |
 image analysis |
 human perception |
 computer vision |
 medical imaging |
 computational biology |
 miscellaneous |
 all [google scholar] 
 
 

 &nbsp 
 
 
 OTHER 
 
 
 in the news |
 podcasts |
 op-eds |
 blog |
 talks |
 tutorials |
 code |
 funding 
 
 
 
 &nbsp 
 
 
 RECENT 
 
 
 
 S. Barrington, M. Bohacek, and H. Farid. The DeepSpeak Dataset, CVPR Findings , 2026. [ read ] [ dataset ]
 OpenAI Closing Its One-Stop AI Slop Shop Sora Is a Cautionary Tale, Tech Policy Press , 3.31.26 [ op-ed ]
 S. Barrington and H. Farid. Distinguishing Authentic from AI-Generated Explosions using Spatiotemporal Dynamics, APAI Workshop at CVPR , 2026 [ read ] [ AI-generated summary ]
 C. Davodi, S. Barrington, H. Farid, and E.A. Cooper. Perceptual Judgments of Video Authenticity: An Examination of Viewing Duration, Confidence, Content, and Strategies, APAI Workshop at CVPR , 2026 [ read ] [ AI-generated summary ]
 How to Stop AI Slop, PBS News Hour , 3.9.26 [ listen ]
 
 
 
 
 
 
 
 photo credit: Rusi Ko Photography 

 
 
 

 
 
 
 
 
 
 
 
 
 
 
 top 

 

 
 BIO

 I am a Professor at the University of California, Berkeley with appointments in the School of Information and Electrical Engineering & Computer Sciences. I am also the co-founder and Chief Science Officer at GetReal Security . My research focuses on digital forensics, forensic science, misinformation, image analysis, and human perception. I received my undergraduate degree in Computer Science and Applied Mathematics from the University of Rochester in 1989, my M.S. in Computer Science from SUNY Albany in 1992, and my Ph.D. in Computer Science from the University of Pennsylvania in 1997. Following a two-year post-doctoral fellowship in Brain and Cognitive Sciences at MIT, I joined the faculty at Dartmouth College in 1999 where I remained until 2019. I am the recipient of an Alfred P. Sloan Fellowship, a John Simon Guggenheim Fellowship, and am a Fellow of the National Academy of Inventors. 
 

 
 TUTORIALS
 
 Learn Computer Vision [ video tutorials ]
 Learn to Code in Python [ video tutorials ]
 Physics-Based Photo Forensics [ video tutorials ]
 H. Farid. Fake Photos, MIT Press Essential Knowledge series, 2019. [ Publisher ] [ Amazon ]
 H. Farid. Photo Forensics. MIT Press, 2016. [ Publisher ] [ Amazon ] [ Table of Contents , Preface , Introduction ]
 Digital Image Forensics: lecture notes, exercises, and matlab code for a survey course in digital image and video forensics. [ tutorial ]
 Fundamentals of Image P

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