I'm a Research Software Engineer at Meta Reality Labs Research, specializing in computer vision, super resolution models, and high-performance inferencing pipelines. With a background in both software engineering and mechanical engineering, I bridge the gap between theoretical machine learning and practical implementation—particularly in resource-constrained environments.
My expertise lies in optimizing neural networks for real-world applications, with a focus on improving image fidelity and processing efficiency. Throughout my career, I've consistently delivered solutions that push the boundaries of what's possible with existing hardware, achieving significant improvements in precision, speed, and overall performance.
ML Algorithm Developer (Feb 2024 - Present)
At Meta Reality Labs, I work with the Sensors & Systems Research team developing super resolution models and rendering pipelines that significantly enhance image fidelity. I've developed custom CUDA kernels for neural network optimization, achieving a 4x resolution boost and 60% image fidelity increase in user tests. Through pipeline refactoring, I helped increase framerate from 6 FPS to 36 FPS, and built an end-to-end data processing pipeline handling images at 360 FPS with sub-10ms latency.
Software Development Engineer (Mar 2023 - Feb 2024)
At ATT Metrology, I contributed to the Artemis system, improving industrial robot precision from 2mm to as low as 0.05mm using dynamic corrections. I architected a split calculation system between real-time and server components with low latency, and developed data collection infrastructure capturing 20 sensor inputs simultaneously for ML model training.
Master of Science in Computer Science (Expected Dec 2025)
Specialization: Machine Learning
Bachelor of Science in Mechanical Engineering (Dec 2022)