Maty(as) Bohacek

Maty(as) Bohacek

Stanford, CA, USA

I am a student at Stanford University with a passion for AI research. Advised by Professor Hany Farid, I focus on generative AI, deepfake detection, and other problems at the intersection of AI, computer vision, and media forensics. My full name is Matyas, but I go by Maty.

News

(January 2025) Discussed AI and disinformation at Unicef’s DCE workshop in Nairobi, Kenya.
(November 2024) Honored to receive the Czech AI Personality Award (Osobnost.ai) as the Discovery of the Year.
(November 2024) Discussed my research on Hyde Park Civilization, a Czech TV show about science.
(November 2024) Delivered a guest lecture in Stanford’s DATASCI 194D.
(November 2024) Joined a panel at the Aspen Institute’s Annual Conference in Prague, Czechia.
See full archive here.

Upcoming

(February 2025) I will deliver an invited talk at the WACV workshop on synthetic realities in Tucson, AZ.
(March 2025) I will deliver an invited talk at the Hoover Institution.
(March 2025) I will join a panel discussion and a fireside chat at SXSW in Austin, TX.
(April 2025) I will deliver a short invited talk at the workshop on data quality at ACM WWW in Sydney, Australia.
(April 2025) I will deliver a keynote for the UNYP URC conference.

Selected Publications & Preprints

Has an AI Model Been Trained on Your Images?

Bohacek M. & Farid H. ArXiv, abs/2501.06399.
Paper Dataset — This paper introduces a method to determine whether a generative AI model was trained on a specific image, helping to address concerns around fair use and copyright in generative AI.

Human Action CLIPS: Detecting AI-generated Human Motion

Bohacek M. & Farid H. ArXiv, abs/2412.00526.
Paper Dataset — This paper proposes a method for distinguishing real from text-to-video clips using multi-modal semantic embeddings, evaluated on DeepAction, a new dataset of real and AI-generated human motion.

DeepSpeak Dataset v1.0

Barrington S., Bohacek M., and Farid H. ArXiv, abs/2408.05366.
Paper Dataset — This paper introduces DeepSpeak, a large-scale dataset of real and deepfake footage designed to support research on detecting state-of-the-art face-swap and lip-sync deepfakes.

Lost in Translation: Lip-Sync Deepfake Detection from Audio-Video Mismatch

Bohacek M. & Farid H. CVPR 2024 Workshops.
Paper — This paper presents a method for detecting lip-sync deepfakes by comparing mismatches between audio-to-text transcription and automated lip-reading, evaluated on both controlled and in-the-wild datasets.

Nepotistically Trained Generative-AI Models Collapse

Bohacek M. & Farid H. ArXiv, abs/2311.12202.
Paper — This paper demonstrates how some generative AI models, when retrained on their own outputs, produce distorted images and struggle to recover even after retraining on real data.

For a complete list of my academic publications, please refer to my Google Scholar profile.

Open-Source Resources

Contact & Misc.

Email: maty (at) stanford (dot) edu
Resume (coming soon)