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Superspreader Detection in the Dataplane
- Developed a superspreader detection algorithm that ran on programmable switches
- Ran simulations in Java that showed performance improvement compared to other similar algorithms
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GAN on MNIST
- Wrote a GAN network tutorial for generating MNIST hand-written digits
- Examined results and wrote a explanation document in Chinese
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Pedestrian Alert!
- Wrote a convolutional neural network that determined if an image contains persons or bikes
- Explored various methods that improved the model accuracy
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Statistics and Visualization of Point-Patterns with Python Research
- Implemented convolutional kernel smoothing in Python that visualized tornado landing intensity in the US for the past five decades
- Optimized my program that allowed the detection of intensity changes in the US “tornado alley”
- Published research report and code that provided references for future members
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MinneAnalytics: Big Data Challenge for Diabetes
- Performed Python k-means clustering that grouped patients with similar diagnoses to find general patterns in gender, geolocation and age in each cluster
- Ran data preprocessing in Hadoop for better performance and presented findings in the conference
- Commented as "one of the most technical solid presentations" by the judges
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Call Me Maybe Android App
- Developed an Android App that organized and scheduled outgoing phone calls, emails and text messages
- Utilized this app as a way to self-teach Android programming