Wenpeng Wang is a research scientist based in Austin with nine years of experience building sensor-enabled IoT systems for wireless sensing, indoor localization, and energy-efficient smart buildings. His work fuses Wi‑Fi, BLE, mmWave radar, and camera data with deep learning to detect, localize, and identify objects in retrofit-ready smart building deployments. After a PhD in computer engineering from the University of Virginia and internships at Bosch, he now applies this research at Apple, translating commodity-sensor innovation into product-grade solutions. Wenpeng has a track record of self-supervised and contrastive learning approaches for cross-modal distillation and practical embedded sensor fusion from prior roles at BU and UVA. He is particularly strong at making advanced sensing techniques work on existing infrastructure, balancing algorithmic novelty with deployment constraints. Colleagues describe him as a researcher who moves seamlessly between theory and hands-on prototyping to deliver usable, energy-conscious systems.
9 years of coding experience
6 years of employment as a software developer
Electrical Engineering and Computer Science, Electrical Engineering and Computer Science at University of California, Berkeley
Doctor of Philosophy - PhD, Computer Engineering, Doctor of Philosophy - PhD, Computer Engineering at University of Virginia
Bachelor’s Degree, Electrical and Electronics Engineering, Bachelor’s Degree, Electrical and Electronics Engineering at Beijing Institute of Technology
Master's degree, Electrical and Computer Engineering, Master's degree, Electrical and Computer Engineering at Boston University
Contributions:2 PRs, 9 pushes, 2 branches in 9 months
boston-universityphysical
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