I am a PhD student in Computer Science at Johns Hopkins University, under advisor Randal Burns. I like scalable, graph algorithms & graph ML and edge Machine Learning. Part of the Institute for Data Intensive Engineering and Science (IDIES) I also have a Medium profile where I publish articles on High Performance Python, Scientific Data Management, hands-on Graph Data Science. I love speaking at various events, most recently the 2023 Google Deepmind's EEML seminar in Albania. My hobbies are skiing and boxing and also have a YouTube channel



Publications

Edge-Parallel Graph Encoder Embedding - ArXiV - GitHub
Parallel Batched CPU & GPU Orthogonal Matching Pursuit with Sebastian Praesius
ChatGPT can’t count, and that’s a problem
Hands-On Quickstart to Training Large Language Models
To Compress or Not to Compress — A Zarr Question
Plot Most Important Nodes in a Graph with NetworkX and MatPlotLib
More CPU cores is seldom better, and here’s why
The Reasons Behind Numpy’s Speed are Often Misunderstood - Part 2
Efficiently Querying Large Scientific Data Using Zarr’s partial decompress
The Reasons Behind Numpy’s Speed are Often Misunderstood - Part 1
Parallelize Graph Computations Using Ligra Framework’s EdgeMap Interface

Talks

DeepMind's EEML Albania 2023

Projects

Dall-E Image Generator for Google Docs, Sheets and Slides (Deprecated) Documentation
Deploy Scientific Datasets to Multi-Disk Systems
Alice in Wonderland BERT-based chatbot - Cool Interactive project
Hierarchical Time Series Analysis
Visualize Turbulence Data
Tools for Working with Graphs
Hand Gesture Recognition
Malaria Detection & Segmentation

Repositories I Maintain

Johns Hopkins Turbulence Database for Python (pyJHTDB)