Allen Cheung
Deep Learning Engineer at Matroid, Inc.
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolAllen Cheung is a Deep Learning Engineer based in the San Francisco Bay Area with eight years of hands-on experience building and deploying computer vision and ML systems from edge devices to server-scale inference. He holds an MS in Computer Science from UCLA and has driven performance and throughput improvements—optimizing YOLO models, TensorRT, and Triton deployments to boost mAP and real-time FPS in drone and defense pipelines. His background spans research and product work, including NLP bias analysis for text-to-image models, 2D Transformer models for molecular identification, and 2D-3D fusion for autonomous driving explainability. Comfortable across the stack, he has shipped ARM64 and Jetson edge solutions, orchestrated Docker/Triton pipelines, and contributed to dataset annotation and tooling; an uncommon strength is his combination of model-level algorithmic innovation with low-level inference optimizations for production environments.
9 years of coding experience
3 years of employment as a software developer
University of California, San DiegoUniversity of California, Los Angeles
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (4)
adapter7
nlp5
natural-language-processing5
transformers3
Programming languages (1)
Github contributions (5)
Allen0307/AdapterBias
Apr 2022 - May 2022
Code for the Findings of NAACL 2022(Long Paper): AdapterBias: Parameter-efficient Token-dependent Representation Shift for Adapters in NLP Tasks
Contributions:7 commits, 6 pushes, 1 branch in 6 days
natural-language-processingadapterparameter-efficient-tuningtransformersnlp
Allen0307/allen0307.github.io
Aug 2022 - Sep 2024
Contributions:12 pushes in 2 years 1 month
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