• Mar. 2020 Tips for Succeeding in a CS Ph.D.

    Or: Things I Wish I Knew Four Years Ago. A collection of lessons that took me longer to learn than I would have liked. Much of these are the soft skills needed to survive a Ph.D.

  • Nov. 2019 The Basic Math of Neural Networks

    Some slides from a recent talk internal to our lab group at Clemson. Covers the absolute fundamentals of neural networks and back propagation.

  • Jul. 2019 Embeddings Conceptualized

    Talks about how text embeddings and more typical neural networks are conceptually related.

  • Mar. 2018 Basic Iterative Numeric Optimization

    Covers the very basics of iterative optimization.

  • Nov. 2017 Producer and Consumer Model in C++

    Describes a pattern to write really easy parallel code using tasks in OpenMP.

  • Sep. 2017 Document Embedding Basics

    Covers the basis of doc2vec, as well as other methods for learning latent representations of documents, extending the word embedding overview.

  • Sep. 2017 Agile Project Management in Google Sheets

    Many small teams spend a lot of time and money on agile project management software. However, you can get a majority of the same function from free tools like Google Sheets.

  • Sep. 2017 Word Embedding Basics

    Describes that mathematical basis of word2vec. A method of learning latent representations of natural language words.

  • Sep. 2017 Hypothesis Generation Explained

    A sizable write up that details the basics of hypothesis generation, and how the Moliere project fits in.