Who i am
About Me
Math PhD from UC Berkeley seeking an AI / ML role
Previously a software engineer at Google on the Trust & Safety team
I have over 7+ years of experience in software engineering and mathematical research. My core skills include machine learning, numerical analysis, scientific computing, and teaching. I am passionate about applying my skills to solve real-world problems and make a positive impact on society. On the weekends, I love to swim, bike and run.
ML/Data Science Projects
2024
GITHUB PROJECT #1
Classify MNIST data with Tensorflow/Keras
Methods: LDA, neural nets
2024
GITHUB PROJECT #2
Analyze men’s D1 NCAA times in the 500 freestyle
Cluster swimmers based on race strategy
Predict final times from the first few splits
Methods: Ridge and LASSO regression
research
Publications
2023
Numerische Mathematik
2023
SIAM Journal on Matrix Analysis and Applications
Description: Analyze floating-point summation error for large/low-precision problems on arbitrary summation trees.
Description: Proposes a method for finding a low-rank approximation to f(A) using Krylov subspace projections. Gives applications to trace estimation.
research
Publications
2023
SIAM Journal on Matrix Analysis and Applications
Description: Provides accuracy bounds on Monte Carlo estimators for the diagonal of a symmetric matrix.
2023
SIAM Journal on Scientific Computing
Description: Proposes randomized algorithms for compressing tensors stored in tensor-train format; compares with deterministic methods.
research
Publications
2022
SIAM Journal on Matrix Analysis and Applications
Description: Block Lanczos matrix sketching is competitive with randomized subspace iteration.
2022
Linear Algebra and its Applications
Description: Uses multilevel Monte Carlo techniques to approximate the trace of f(A) by splitting the approximating polynomial into several smaller ones.
research
Publications
2021
Applied Mathematics Letters
2020
Linear Algebra and its Applications
Description: Estimates the trace of a matrix polynomial 2x faster compared to standard methods.
Description: New backward error estimate for AX=B (multiple columns) guaranteed within 2x of true value.
research
Publications
2020
SIAM Journal on Matrix Analysis and Applications
2018
SIAM Journal on Matrix Analysis and Applications
Description: Proposes error estimate when solving Ax~=b; under certain assumptions it can’t be improved.
Description: Proposes new method LSMB for solving Ax~=b, offers efficient backward error estimation. Iterates are linear interpolation of LSQR/LSMR.