James F. O'Brien

James F. O'Brien is a computer scientist and professor of computer science at the University of California, Berkeley. His research includes computer graphics, physically based animation, machine learning, image forensics, human visual perception, digital privacy and virtual reality.

In 2015, he received a Technical Achievement Award from the Academy of Motion Picture Arts and Sciences for research used to simulate fracture and deformation in visual effects. In 2025, he and his coauthors received an ACM SIGGRAPH Test of Time Award for the paper "Fast Simulation of Mass-Spring Systems".

Education and career James O'Brien received a Bachelor of Science in computer science from Florida International University in 1992, followed by a Master of Science in 1997 and a PhD in 2000, both also in computer science, from the Georgia Institute of Technology. His doctoral adviser was Jessica Hodgins.

He joined UC Berkeley's EECS faculty in 2000. He served as a director-at-large of ACM SIGGRAPH from 2010 to 2016.

Research and professional activities O'Brien has published research papers on topics such as surface reconstruction, human figure animation, mesh generation, physically based animation, surgical simulation, computational fluid dynamics, and fracture propagation.

O'Brien served as a consultant on the development of the game physics engine Digital Molecular Matter (DMM). To date, this game engine has been used in Star Wars: The Force Unleashed and an off-line version of it was used for special effects in the film Avatar, Sucker Punch, Source Code, X-Men: First Class, and more than 60 other feature films.

In 2015, his work on developing DMM was recognized by the Academy of Motion Picture Arts and Sciences with a Technical Achievement award. The citation reads:

"To Ben Cole for the design of the Kali Destruction System, to Eric Parker for the development of the Digital Molecular Matter toolkit, and to James O’Brien for his influential research on the finite element methods that served as a foundation for these tools. The combined innovations in Kali and DMM provide artists with an intuitive, art-directable system for the creation of scalable and realistic fracture and deformation simulations. These tools established finite element methods as a new reference point for believable on-screen destruction."

Photo forensics and fake media detection O'Brien is a noted expert on detection and analysis of fake images and video. He has frequently worked with news organizations on exposing fake or altered photographs, as well as images created by generative AI software. His methods have been used to expose fabrication of medical research records prosecute child pornographers, validate evidentiary videos, and rule out conspiracy theories relating to photographs of the Moon landing. In response to their work debunking assertions that the shadows in photos of the 1969 Moon Landing and of Lee Harvey Oswald, coauthor Hany Farid has been accused by conspiracy theorists of being a time-traveling CIA operative.

In addition to developing methods for detecting fake images and video, O'Brien's has studied the impact of fake media on viewers and investigated what factors contribute to a viewer's acceptance or skepticism regarding the media they consume. O'Brien has stated that due to rapid progress in machine learning "it will be impossible to tell the difference between a generated image and a real one" and that detection software will be in an arms race that will eventually be lost to generative AI. He advocates for changing societal attitudes regarding trusting media and that viewers should suspect everything as potentially fake.

Awards SIGGRAPH Impact Award (1999) Technology Review TR100 (2004) Sloan Fellowship (2004) College of Engineering Distinguished Alumni, Florida International University (2006) GVU 15 Impact Award Jim and Donna Gray Endowment Award for Excellence in Undergraduate Teaching (2008) The Academy of Motion Pictures Arts and Sciences Award for Scientific and Technical Achievement ( A Sci-Tech Oscar, 2015 ) DreamWorks Animation award for Technical Achievement for work in the field of Machine Learning related to Character Rigging (2020)