Vision Science & AI @ Meta Reality Labs

Joined April 2021
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Pinned Tweet
šŸ–ļø Headed to St. Pete Beach for VSS! Presenting new work Monday morning with Phil Guan, Ian Erkelens & Oliver Cossairt @RealityLabs. Come say hi! šŸ“„ Abstract: visionsciences.org/presentat… šŸ”¬ More from Meta Reality Labs: visionsciences.org/presentat… visionsciences.org/presentat… #VSS2025
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I'm hiring my first Research Scientist (PhD) Intern Topic areas: • Vision science (brightness, blur) • Environmental & retinal image statistics • Perceptually-aligned vision models • Sensor-to-display control algorithms Please apply if interested: lnkd.in/ea8B-kJv
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Charlie S. Burlingham retweeted
18 Jul 2024
So in 2007, physicists wrote a paper that made the headlines: according to their calculations, human coin flips aren’t 50/50 - more like 51/49. Why is that, and did students in Amsterdam really flip 350,000 coins to find out? 🧵
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Charlie S. Burlingham retweeted
I’m very excited to share that my graduate work is now online in @ScienceMagazine today! With generous help from my mentor @yuji_ikegaya and my amazing teammates, we investigated a top-down pathway for volitional heart rate regulation! science.org/doi/10.1126/scie…
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Charlie S. Burlingham retweeted
All-day AR would benefit from AI models that understand a person's context & eye tracking could be key for task recognition. Yet past work - including our own research.facebook.com/public… - hasn't found much added value from gaze in addition to computer vision & egocentric video 2/
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Charlie S. Burlingham retweeted
Got Butterflies in your Stomach?šŸ˜µā€šŸ’«I am super excited to share the first major study of my postdoc @visceral_mind! We report a multidimensional mental health signature of stomach-brain coupling in the largest sample to date šŸ§µšŸ‘‡biorxiv.org/content/10.1101/…
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New paper alert! @RealityLabs Eye gaze in everyday life contains multi-scale temporal dependencies across objects (1-7 fixations into past, depending on task). Akin to natural language. Key to foundation models for visual understanding in mixed reality dl.acm.org/doi/10.1145/36499…
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But object-part-based image segmentation is just starting to gain traction, and universal segmentation (segmenting and labelling all image pixels) is still a challenge. So this is one major bottleneck for aligning the model input state space with that of human active vision. 5/
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Once the input state space is well-aligned with human action & vision, and appropriate models that can represent long-term dependencies are used, we believe that multiple problems in contextual AI may be solved convergently by a single (gaze-based) visual foundation model. 6/
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Charlie S. Burlingham retweeted
4 Jun 2024
PETMEI Workshop at @ETRA_conference 2024 kicked off with the keynote speech by @MichaelProulx from @RealityLabs. Insightful speech on pervasive eye tracking challenges for interactions in #ExtendedReality. petmei.org/2024/ #ETRA2024
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Charlie S. Burlingham retweeted
5 Jun 2024
Paper Session 1: Visual Attention @ETRA_conference 2024 just started. @olegkomo from @RealityLabs and @txst is now presenting their paper on "Per-Subject Oculomotor Plant Mathematical Models and the Reliability of Their Parameters" at #ETRA2024. Paper: doi.org/10.1145/3654701
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