Jane Du - Graduate Research Assistant

Jane Du

Graduate Research Assistant

Urbana, Illinois, United States

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Summary

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Rockstar

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Top School

Jane Du is a PhD candidate and Graduate Research Assistant in computer science with a decade of hands-on experience spanning research, teaching, and industry internships at Microsoft and GEOTAB. She blends strong academic foundations from Cornell and UIUC with practical software engineering—building full-stack features such as WinUI audio-preprocessing tools and melspectrogram visualization integrated with NAudio and ML models in Microsoft’s Windows-Machine-Learning repo. Her background includes designing automation for course infrastructure and build-server provisioning, signaling a knack for tooling that improves developer productivity. Based in Urbana, Illinois, she pairs rigorous theoretical knowledge in ML and AI with pragmatic engineering, often focusing on reproducible pipelines and readable, well-refactored code.

10 years of coding experience

3 years of employment as a software developer

Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Cornell University

Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Illinois Urbana-Champaign

Ontario Scholar, Ontario Secondary School Diploma, Ontario Scholar, Ontario Secondary School Diploma at The Woodlands School

French, Chinese, Japanese, German

Github Skills (7)

file-handling10

machine-learning10

audio-processing10

winui10

csharp10

dotnet-core10

uwp9

Programming languages (3)

PowerShellC++Jupyter Notebook

Github contributions (5)

microsoft/Windows-Machine-Learning

Jun 2021 - Aug 2021

Samples and Tools for Windows ML.

Role in this project:

Full-stack Developer

Contributions:45 reviews, 65 commits, 9 PRs in 2 months

Contributions summary:Jane contributed to the development of a WinUI application within the repository, likely for audio preprocessing tasks. Their work involved implementing a file picker for .wav files and displaying a melspectrogram image. The commits showcase integration with the NAudio library and the use of machine learning models for audio processing, which included converting the audio into a specific bitmap format. The user refactored code for better readability and correct color display.

pytorchcaffe2pythonwindowswinmltools

janezdu/sparseIRM-resnet-ver

Sep 2024 - Dec 2024

Contributions:276 pushes, 3 branches, 3 tags in 2 months

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