Visual outreach and matching engine for high school researchers. Connect with professors and labs with precision.
Write up your engineering projects - robotics builds, ML models, IoT rigs. Any hands-on technical work that shows what you can do.
We score your projects against recent papers from local university labs. Find professors whose work actually connects to yours.
Get a citation-anchored cold email that references the professor's specific paper, grounded in your project work. Low friction, high signal.
A real-style draft connecting a LiDAR project to a university lab:
Subject: Real-time LiDAR segmentation on embedded platforms - undergrad research
Dear Professor Chen,
I read your IEEE TPAMI paper on range-aware point cloud segmentation with interest - particularly the SparseConv3D approach you used to handle variable-density LiDAR data. I have been working on a similar problem from the embedded side.
Over the past six months I built a real-time LiDAR obstacle detection pipeline for a campus autonomous go-kart project. The system runs on a Jetson Nano at 15 FPS using a custom downsampled PointNet++ variant. One challenge I hit was balancing inference speed against recall on distant points in the "range-view" projection - your paper's distance-adaptive kernel directly addresses that trade-off. I implemented a simplified version of it and saw a 12% mIoU improvement at 20m+ while staying under 30ms per frame.
I am applying to summer research positions and would love to discuss how my work might fit into your group's ongoing research on efficient perception. Would you have 10 minutes for a quick call in the next couple weeks?
Best,
Aiden Park
Junior, Palo Alto High School
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