Emily Shen
Clinical Research Assistant at Northern California Retina Vitreous Associates Medical Group Inc
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolEmily Shen is a Biomedical Engineering student at Washington University in St. Louis with eight years of hands-on experience blending clinical research and software skills to advance healthcare. Currently a Clinical Research Assistant in Northern California, she has driven neuroimaging and radiochemistry projects—analyzing fMRI connectivity, handling gamma-counting and HPLC workflows, and supporting grant-backed studies—while coding in Python, R, and MATLAB for data visualization and analysis. Emily also brings machine learning engineering experience from contributions to the widely used facebookresearch/pytext project, where she optimized PyText for hardware-accelerated deployments including NNPI and torchscript exports. Comfortable recruiting and testing human participants in clinical settings, mentoring clinical scribes, and translating lab results into reproducible analyses, she seeks research and internship roles that bridge computational methods with patient-centered care.
8 years of coding experience
3 years of employment as a software developer
Bachelor's degree Bioengineering and Biomedical Engineering, Bachelor's degree Bioengineering and Biomedical Engineering at Washington University in St. LouisMonta Vista High School
English, Chinese
Github Skills (5)
pytorch10
machine-learning10
nlp10
python9
roberta9
Programming languages (4)
Github contributions (5)
facebookresearch/pytext
Feb 2021 - Nov 2021
A natural language modeling framework based on PyTorch
Role in this project:
ML Engineer
ML EngineerContributions:14 commits, 8 PRs in 9 months
Contributions summary:Emily primarily contributed to the enhancement and optimization of PyText, a natural language modeling framework built on PyTorch, focusing on features related to hardware acceleration. Their work included adding input padding functionality for RoBERTa tensorizers, implementing multi-export capabilities for torchscript models, and incorporating support for NNPI (Neural Network Processing Interface) export. These efforts aimed to improve performance and expand the framework's capabilities for deployment on specialized hardware.
pytorchnlpbertmachine-learningnatural-language
mleshen/main-website
Apr 2020 - Jan 2021
Harvard Advocate Website
Contributions:13 pushes in 9 months
advocatedjangorubyjekyllharvard
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