Muhammad Jamal is a Staff ML Scientist in Sunnyvale with a decade of experience building computer vision and multi-modal AI systems, currently focused on foundation models and long-form video understanding at Intuitive. He earned a Ph.D. in Computer Science from UCF and has a strong research track record including CVPR and ICCV publications on self-supervised learning, few-shot/meta-learning, and robust face detection. His background spans industry research stints at Google, Adobe, Tencent, and internships that translated academic ideas into practical evaluation and deployment insights. Known for bridging theory and application, he has repeatedly delivered data-efficient adaptation methods and novel gradient strategies for long-horizon tasks. Colleagues rely on him to move cutting-edge visual-language research toward production-ready video understanding components in healthcare robotics.
10 years of coding experience
10 years of employment as a software developer
Bachelor of Engineering (B.E.) Information and Communication System Engineering, Bachelor of Engineering (B.E.) Information and Communication System Engineering at National University of Sciences and Technology (NUST)
Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at University of Central Florida
Contributions:21 pushes, 1 branch in 2 years 5 months
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