Philip Xu
Software Engineer at Microsoft
Redmond, Washington, United States
Summary
👤
Senior🎓
Top SchoolPhilip Xu is a software engineer at Microsoft with 12 years of hands-on experience building computer vision systems augmented by large language AI models. His background spans facial recognition and tracking, live media streaming, and research internships where he implemented CNNs, GANs, and on-device model optimizations for companies like Samsung and HiScene. At Brown he supported a research-focused deep learning course as a teaching assistant, reflecting a strong foundation in both theory and practical mentorship. He has built end-to-end ML systems—from data collection and Android deployment to LSTM-based prediction models showcased on his GitHub—demonstrating an appetite for applying deep learning to diverse domains, including unusual uses like technical stock analysis. Based in Redmond, Philip blends research curiosity with production engineering at scale, frequently bridging prototyping and deployment. Colleagues describe him as someone who moves fluidly between research labs and product teams to deliver practical AI solutions.
11 years of coding experience
High School/Secondary Diplomas and Certificates, High School/Secondary Diplomas and Certificates at Lord Byng Secondary SchoolBachelor of Applied Science (B.A.Sc.), Computer Science, Bachelor of Applied Science (B.A.Sc.), Computer Science at Brown UniversityChoate Rosemary Hall
English, Chinese
Github Skills (13)
lstm10
deep-learning10
tensorflow10
python10
neural-network9
technical-indicators9
analyse9
convolutional-neural-networks9
machine-learning8
pandas8
data-analysis8
numpy8
plotly7
Programming languages (3)
Github contributions (5)
philipxjm/Deep-Convolution-Stock-Technical-Analysis
Mar 2016 - Jul 2017
Uses Deep Convolutional Neural Networks (CNNs) to model the stock market using technical analysis. Predicts the future trend of stock selections.
Role in this project:
ML Engineer
ML EngineerContributions:25 commits, 23 pushes, 1 branch in 1 year 3 months
Contributions summary:Philip primarily contributed to building a deep learning model for stock market prediction. They developed and modified a neural network framework with Python, incorporated historical stock data, and added candlestick chart visualization. They integrated PyBrain to construct and train recurrent neural networks using LSTM layers and added supporting modules. This work involved implementing and refining core components for stock data analysis and prediction.
convolutional-neural-networksneural-networkstock-marketstock-price-prediction
philipxjm/PieMessengerBackend
Sep 2015 - Oct 2015
Contributions:16 commits, 11 pushes, 1 branch in 22 days
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.