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Jenny Wu
Junior Biomedical Engineering student and full-stack developer specializing in robotics & computer vision
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About
Robotics/software engineer who deployed a Raspberry Pi computer-vision-controlled 3-axis platform at FuelCell Energy, improving screen-print alignment from >10mm to 0.01mm repeatability via encoder-based closed-loop PID control. Currently designing an AI-enabled hearing-aid accessory for the cocktail party problem using a multi-mic array, beamforming, and an edge-accelerated neural network with <10ms latency via shared-memory DSP integration.
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Key Strengths
- Improved screen printing alignment from >10mm error to 0.01mm precision using CV + motion control
- Designed closed-loop 3-axis platform control with stepper encoders and PID to overcome backlash/microstepping limits
- Built low-latency on-device audio AI pipeline (beamforming + edge NN) achieving <10ms speech separation
- Strong real-time systems engineering: deterministic design, lock-free/preallocated patterns, watchdogs/fallback modes, worst-case stress testing
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