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Hello everyone,

This is Xiaoyu Xie, a third-year PhD candidate at Northwestern University, USA. A brief summary for me is shown below:

  • 6+ years of research experience in machine learning and deep learning for scientific knowledge (e.g., ODEs/PDEs, scaling laws, dimensionless numbers) discovery, digital twin creation, surrogate modeling, image and statistical analysis using physics-based and data-driven approaches.
  • 2 years of industrial experience in computer vision and deep learning of designing and implementing visual spam detection systems (images, videos, and live streaming data), online training, computing, monitoring, and evaluating systems.
  • Demonstrated experience in the development of open-source software. Independently contributing to the development of PyDimension, a python library for discovering scientific knowledge from scarce data.
  • Strong communication and writing skills and ability to work collaboratively in interdisciplinary teams.
  • Authored and co-authored 5 scientific publications in top journals (e.g., Nature Communications and Npj Computational Materials-Nature).
  • Actively looking for a 2023 intern position in machine learning, deep learning, and computer vision-related fields.

Please go to my personal website to read more.

XiaoyuXie's Projects

d2l-en icon d2l-en

Interactive deep learning book with code, math, and discussions. Available in multi-frameworks.

d2l-pytorch icon d2l-pytorch

This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.

dem_hyperelasticity icon dem_hyperelasticity

A method based on a feed forward neural network to solve partial differential equations in nonlinear elasticity at finite strain based on the idea of minimum potential energy. The method is named "Deep Energy Method".

dominant-balance icon dominant-balance

Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)

jax-am icon jax-am

Additive manufacturing simulation with JAX.

manim icon manim

Animation engine for explanatory math videos

meal icon meal

Official Implementation of MEAL: Multi-Model Ensemble via Adversarial Learning on AAAI 2019

ml_notes icon ml_notes

机器学习算法的公式推导以及numpy实现

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