Afshin Dehghan
AI ML Lead at Apple
Cupertino, California, United States
Summary
👤
Senior🎓
Top SchoolAfshin Dehghan is an AI/ML lead with a decade of experience translating cutting-edge research into production systems, currently heading Apple’s Multimodal INTelligence (MINT) group in Cupertino. He has driven multimodal foundation models, agentic AI systems, and large-scale perception tech that power features across Apple products—from FaceID and real-time camera semantic reasoning to 3D perception for Vision Pro. Trained as a PhD computer scientist, Afshin blends deep academic credentials and award-winning research with hands-on startup experience building mobile-friendly vision models and large-scale image and video systems. He excels at bridging bold research and product engineering, often leading cross-disciplinary teams to deliver deployable, privacy-conscious perception and reasoning capabilities. A less obvious strength is his track record of shepherding long-term research (e.g., 3D scene understanding and agentic AI) from early incubation to core platform technologies used company-wide.
10 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at University of Central Florida
Github Skills (27)
depth-estimation10
depth-camera10
stereo9
scene9
rgb9
3d-reconstruction8
python8
machine-learning8
pytorch8
data-science7
caffe7
tensorflow7
deep-learning7
arxiv7
computer-vision7
Programming languages (5)
Github contributions (5)
afshindn/GMMCP_Tracker
Mar 2017 - Jul 2018
Contributions:8 commits, 4 pushes, 1 branch in 1 year 4 months
apple/ARKitScenes
Dec 2021 - Mar 2022
This repo accompanies the research paper, ARKitScenes - A Diverse Real-World Dataset for 3D Indoor Scene Understanding Using Mobile RGB-D Data and contains the data, scripts to visualize and process assets, and training code described in our paper.
Contributions:3 commits, 2 PRs, 8 pushes in 2 months
diversevisualizescene-understandingtrainingresearch-paper
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