Howard Wang is a Visiting Researcher and robotics-focused ML engineer with 11 years of experience building resilient perception and distributed ML infrastructure. He designs end-to-end vision pipelines and embodied AI systems, most recently leading the perception stack for Agrobot TOM v2—a zero-shot, foundation-model-fusion ROS 2 system deployed for MassRobotics 2026. His research on scalable vector search produced a hierarchical HNSW (Pyramid Search) and a locality-aware routing layer that matched single-index recall while enabling 10k+ QPS with sub-5 ms p99 latency. Comfortable moving between C++/FAISS high-performance systems and PyTorch/ROCm model stacks, he emphasizes reproducibility, fault tolerance, and rapid deployment across new domains. Formerly an undergraduate researcher at UCSC and now pursuing advanced AI studies at Columbia and NYU, he combines academic rigor with hands-on field deployments and industry collaborations.
11 years of coding experience
1 year of employment as a software developer
Computer Science, Computer Science at New York University
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Baskin Engineering at UCSC
Simple and intuitive React JS web app for group location sharing
Contributions:3 pushes in 6 years
reactjs-webjavascriptsharingintuitive
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