This is an index of publicly-available projects I’ve worked on.

Open Source Contributions


Started November 2019

Elastiknn is an Elasticsearch plugin for exact and approximate nearest neighbor search on numerical vectors. It allows Elasticsearch developers to combine traditional queries (e.g. documents containing “some product”) with vector search queries (e.g. documents with images similar to some image).

Talks and Presentations

Keras Library for Neural Networks and Deep Learning

June 2017 – Knoxville Data Science Meetup

Meetup presentation covering various aspects and use-cases for the Keras library.

Slides, Recording

Exploring Serverless Architectures with AWS Lambda and Node.js

July 2016 – Codestock Conference

Conference presentation introducing the AWS Lambda service with a simple web application implemented on Lambda.

Slides, Code

React, Flux, and Realtime RSVPs

April 2016 – Knoxville JavaScript Meetup

Meetup presentation where I live-coded a web-application that uses React and D3.js to display statistics about RSVPs from the streaming API.

Slides, Source Code, Online demo

Machine Learning

Kaggle KKBox Music Recommendation Competition

October - December 2017 – Competition

Used collaborative filtering, vector-space models, and gradient-boosting classifiers to train a music recommender system. Submission ranked 222nd (top 21%).


Kaggle Understanding the Planet from Space Image Classification Competition

May - July 2017 – Competition

Trained convolutional networks to do multi-class image classification on satellite images. Submission ranked 103rd (top 11%).


Neurofinder Calcium Imaging Segmentation Challenge

April - July 2017 – Competition

Trained a fully-convoluational neural network to segment neurons from images of a mouse brain taken using a calcium-imaging technique. Placed third in the Neurofinder competition. Published results at the 2017 Deep Learning in Medical Image Analysis Workshop.

Paper, Code

ISBI 2012 Electron Microscopy Segmentation Challenge

March 2017 – Competition

Electron microscopy example image

Trained a fully-convolutional neurla network to segment electron microscopy images. Placed top 50 on leaderboard (search “ORNL_Klibisz”).


Reservoir Computing Summary Paper

December 2016

Term-paper for Biologically-Inspired Computing course at the University of Tennessee. Covers Reservoir Computing, Liquid State Machines, and Echo State Machines.


Web Applications

Meetup RSVP Visualization

February 2016

Application Screenshot

Real-time visualization of streaming data from the open events RSVP API. Visualizes events as a map with markers and bar charts showing the most frequent countries, states (USA), and names.

Live Demo, Code

Dynamic Adaptive Neural Network Array Visualization

Fall 2015

Application Screenshot

The Dynamic Adapative Neural Network Array (DANNA) is a neuromorphic computing model created by the Neuromorphic Computing research group. I built DANNA-View, a web-app for visualizing the DANNA networks, as an independent study course with Dr. James Plank. The tool produces interactive visualizations and heat maps for network activity, which are used for understanding and debugging the networks. The app uses a node.js server to transform network definition files to a JSON format for rendering, and React.js and D3.js in the browser to render the network and provide controls for interacting with it.

Animated Finite State Machine Converter

Spring 2015

Application Screenshot

An application that lets the user interactively build a Nondeterministic Finite Automaton and visually convert it to an equivalent Deterministic Finite Automaton. Built as an honors project for the spring 2015 COSC312 course at the University of Tennessee. Used D3.js and Angular.js to create the visualization and controls.

Live Demo