Peter Wang is an AI/ML senior research scientist with nine years of experience bridging foundational research and product-grade solutions in computer vision, representation learning, and efficient deep networks. He earned a PhD-level research profile at UC Berkeley and Caltech, producing physics-informed, resolution-agnostic models for inverse imaging problems and multi-modal foundation models applied to surgical robotics and ultrasound. At industry-facing roles he shipped compact, robust AI-IoT systems and a patented multi-view virtual try-on system integrated at Amazon, demonstrating an ability to move novel algorithms into production. Currently focused on multi-modal video LLMs and multi-agent platforms at Accenture, he combines deep theoretical work with pragmatic engineering for domain-specific applications. Notably, his background spans both long-tailed/imbalanced learning techniques and lightweight on-device detection, reflecting a rare mix of efficiency-driven and physics-aware modeling.
9 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD Computer Vision, Doctor of Philosophy - PhD Computer Vision at University of California, Berkeley
Bachelor's degree Electrical Engineering, Bachelor's degree Electrical Engineering at Xi'an Jiaotong University
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Peter Wang - AI ML Senior Research Scientist at Caltech