🎸🐶 Hello, I'm Evan!

I am a data scientist at Stanford Libraries 📚

Currently working on:

• Attitudes about envronmental catastrophes in the Mascarenes
• Machine learning to better understand perioperative depression
• Ecological effects of chlorinated water, disease, and conflict in Northwest Syria
• Health, agriculture, and armed conflict in Syria and Yemen
• Postoperative complications in young female diabetics

I can help with:

• R/RStudio/Tidyverse, Python/Jupyter Notebooks, Bash, Git/GitHub, Microsoft Excel, Qualtrics, Google Suite
• Data preparation: text, image, quantitative, machine/deep learning, data imputation
• Data visualization: ggplot2, geospatial mapping, matplotlib, seaborn, plotly, altair, geopandas, gnuplot
• Machine learning: caret, SuperLearner, H2O, scikit-learn, tensorflow, pytorch, keras, regression (lm, glm, penalized, step, spline, hinge), classification, tree-based methods, confusion matrix derivations, cross-validation
• Deep learning: quantitative, text, image, MLP, GAN, RNN, CNN, LSTM, transfer learning
• Text: mining, classification, word embeddings, topic modeling (assisted/anchored/weighted/neural), sentiment analysis, semantic structure/analysis
• Unsupervised methods/dimension reduction: PCA, MCA, CCA, tSNE, UMAP, clustering
• API access, social network data, webscraping
• Categorical data analysis
• Time series, forecasting
• Survey design and analysis
• Bloomberg Terminal