At Applied Intuition, I work on autonomy models and the challenges of bringing hardware and software to production.
At Stanford, I studied Computer Science and Electrical Engineering.
OOPSLA 2026
Co-authored a domain-specific language and compiler that separates recurrence definitions from scheduling and pruning, generating efficient C++ implementations of bioinformatics algorithms.
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2024
Built C++ streaming operators for Apache Arrow Feather and Parquet data and worked on projection-pushdown optimizations for composable security-data pipelines.
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CHI 2024
Contributed to research on an augmented-reality science-learning experience that combines interactive storytelling with large language models, published at CHI 2024.
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2023 publication
At UCSF's Burlingame Lab, I co-authored research improving the isolation and mass spectrometry identification of newly synthesized proteins.
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Davidson Fellowship
Researched machine-learning approaches to predicting cancer-drug response using molecular and gene-expression data; recognized with a Davidson Fellowship.
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