I am a software engineer specialized in performance optimization, GPU Compute and Deep Learning. Skills: Performance optimization for Deep Learning and GPU compute kernels, hardware software co-designing. Toolchain support: GPU compiler and driver, and ML accelerator compiler.

Experience

2020 — NowWaymoSenior Software Engineer

2020 — Now

Mountain View, California, United States

2019 — 2020AppleSoftware Performance Engineer

2019 — 2020

Sunnyvale, California

AR/VR related performance analysis and optimization for computer vision pipeline and deep learning model

Led the performance optimization of neural network on ASIC accelerator

2018 — 2018scikit-learn (Machine Learning in Python)Contributor

2018 — 2018

Remote

Contributed a new metric to Scikit-learn: multi-label confusion matrix, and conducted thorough tests (codecov 99.18%)

Conducted benchmarking and line profiling on multi-label confusion matrix, reduced runtime by 81.8%

Maintained warning message suppression code, suppressed 2239 expected warnings in testing

2018 — 2018Carnegie Mellon UniversityIndependent Study on Speech Recognition

2018 — 2018

Under guidance of Prof. Bhiksha Raj, used deep learning for speech recognition problem.

Developed an attention-based encoder-decoder model and a recurrent network trained with CTCLoss, used curriculum learning and beam search to improve results

Adopted MFCC and implemented Vocal Tract Length Perturbation as a method of data augmentation in speech recognition

Implemented weight-dropped LSTM which uses DropConnect on hidden-to-hidden weights and variational dropout on the input

Achieved 3x speedup by reducing data transfer between CPU and GPU and replacing iterations with high level indexing