James O'Brien
Also known as James F. O'Brien
James O'Brien is a computer science professor at UC Berkeley whose work includes deep learning for character animation, image forensics and virtual reality privacy. He completed his computer science PhD at Georgia Tech in 2000 and joined Berkeley's computer science department in 2000. His research on simulated destruction received an Academy Technical Achievement Award in 2015, and he coauthored “Fast and Deep Deformation Approximations” in 2018. In 2023, he coauthored a study that identified VR users from head and hand motion; in 2026, he helped develop Robo-Saber for VR game tests. As of October 2026, he is also a co-founder of KronosAI and Cosine Energy.
- Now at
- University of California, Berkeley, KronosAI and Cosine Energy
- Works
- 163
- Citations
- 11,639
- h-index
- 61
- Badges
Publication numbers from OpenAlex, as of 28 October 2026.
Timeline
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1992–2000
Computer science degrees
He earns a BS in computer science at Florida International University in 1992. At the Georgia Institute of Technology, he completes an MS in computer science in 1997 and a PhD in computer science in 2000.
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2000–2016
Berkeley and SIGGRAPH roles
He joins Berkeley's computer science department in 2000. By 2015, he leads the Berkeley Computer Animation Modeling Group. He serves as a director at large of ACM SIGGRAPH from 2010 to 2016.
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2013
Detecting inconsistent shadows
In 2013, he coauthors “Exposing Photo Manipulation with Inconsistent Shadows” with Eric Kee and Hany Farid. The method uses geometry and linear programming to test whether shadows in a photograph are physically consistent, helping detect photo manipulation.
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2015
An Academy technical award
In 2015, he receives a Technical Achievement Award from the Academy of Motion Picture Arts and Sciences for finite element research used in the Digital Molecular Matter toolkit. The toolkit simulates the motion of objects and structures as they are damaged or destroyed.
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2018
Deep learning for character rigs
With Stephen Bailey, Dave Otte and Paul DiLorenzo, he coauthors “Fast and Deep Deformation Approximations” in 2018. The method uses deep learning to approximate nonlinear character deformations and reduces deformation computation time by a factor of five to ten in its production rig examples.
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2021
Testing the Picture-O-Meter
In 2021, he coauthors a study with Cuihua Shen and Mona Kasra that tests the Picture-O-Meter image authenticity label with 2,440 participants. Images marked “Altered” receive lower credibility ratings than images with no label or an “Un-altered” label.
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2023
Identifying virtual reality users
In 2023, he coauthors “Unique Identification of 50,000+ Virtual Reality Users from Head and Hand Motion Data”. After training on five minutes of motion per person, the classification model identifies users among 55,541 participants with 94.33% accuracy from 100 seconds of motion.
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2025
A Test of Time Award
In 2025, he shares a SIGGRAPH Asia Test of Time Award with Tiantian Liu, Adam W. Bargteil and Ladislav Kavan for “Fast Simulation of Mass-Spring Systems”.
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2026
Robo-Saber for game tests
In 2026, he coauthors “Robo-Saber: Generating and Simulating Virtual Reality Players”. Trained on BOXRR-23 and applied to Beat Saber, the model generates VR headset and handheld controller movements from game object arrangements and examples of player styles.
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As of October 2026
Professor and company co-founder
In October 2026, he is a professor in Berkeley's Division of Computer Science (EECS), with research in machine learning, image synthesis and image and video forensics. He is also a co-founder of KronosAI and Cosine Energy.
Career
- NowUniversity of California, BerkeleyProfessor
- NowKronosAICo-founder
- NowCosine EnergyCo-founder
- From 2000University of California, Berkeley
- University of California, BerkeleyLeader of the Berkeley Computer Animation Modeling Group
Education
- 2000Georgia Institute of TechnologyPhD in computer science
- 1997Georgia Institute of TechnologyMS in computer science
- 1992Florida International UniversityBS in computer science
Sources and credits
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- James O'Brien | EECS at UC Berkeley
- Thanking the Academy - Berkeley Engineering
- James F. O'Brien - OBJF
- Exposing Photo Manipulation with Inconsistent Shadows - OBJF
- Fast and Deep Deformation Approximations - OBJF
- Research note: This photograph has been altered: Testing the effectiveness of image forensic labeling on news image credibility | HKS Misinformation Review
- Unique Identification of 50,000+ Virtual Reality Users from Head and Hand Motion Data - OBJF
- Award Winners | SIGGRAPH Asia 2025
- [2602.18319] Robo-Saber: Generating and Simulating Virtual Reality Players
- James O'Brien | Research UC Berkeley