About the website

• I made this website to display my skills, interests and accomplishments to potential schools, employers, and collaborators. Some of the materials on this web site are password protected.
• Also, I wanted a place to keep track of random stuff I've created which I think is neat, things I've researched, and stuff I've thought about.

About me

I’m currently a data scientist at Pacific Northwest National Laboratory. My current research projects involve applications of deep learning to cyber security, bio-surveillance, natural language processing and image processing. My undergraduate background is primarily in Linguistics and Mathematics. My graduate studies in Computer Science have covered the breadth of the field by the core curriculum, with electives focused on Machine Learning and Data Analysis (Recommendation Systems, Machine Learning, Artificial Intelligence, Spoken Language Processing, Computational Linguistics, and Data Mining). My graduate school research was focused first in low rank tensor and matrix factorization approaches to recommendation systems and subsequently deep learning methods.

Publications

• Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection Artificial Intelligence in Cyber Security Workshop AAAI-2018. To Appear.
• Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams. Artificial Intelligence in Cyber Security Workshop AAAI-2017.
• Predicting User Roles from Computer Logs using Recurrent Neural Networks. AAAI-2017 Student Abstract

Presentations

• Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams.
  
  PNNL (Fall 2016)
• Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams.
  
  WWU ACM Club (Winter 2017)
• Predicting User Roles from Computer Logs using Recurrent Neural Networks.
  
  AAAI-2017 3 Minute Contest. (Winter 2017)
• Predicting User Roles from Computer Logs using Recurrent Neural Networks.
  
  AAAI-2017 Poster sesssion. (Winter 2017)
• Recurrent Neural Networks
  
  CSCI 570: Artificial Intelligence Graduate Student Lecture (Fall 2016)
• Deep Learning and Multivariate Features for Online Anomaly Detection in Network Traffic
  
  PNNL: National Security Internship Program Symposium (Summer 2016)
• Matrix Factorization Recommender Systems and Cold Start
  
  WWU Graduate Student Conference (Spring 2015)
• Boosting
  
  Machine Learning: CSCI 571 (Spring 2015)
• Matrix Factorization Recommender Systems and Cold Start
  
  WWU Scholars Week (Winter 2015)
• Modeling the Semantics of "tall": A probabilistic approach
  
  WWU Linguistics Colloquium (Spring 2014)

Projects

Python

• Automated Neural Graph Toolkit (2016)
  
  Extension library for Google's Tensorflow toolkit

Matlab

• Low Rank Matrix Factorization (2015)
• Linear Regression (2016)

Java

• Ternary Fast Fourier Transform | Background | Assignment | Writeup
  
  FFT using powers of 3 roots of unity instead of powers of 2 roots of unity.
• Shortest Monotonic Cycle Solver | Background | Assignment | Writeup
• Tridiagonal PLU Decomposition | Background | Assignment | Writeup
• Multinomial Logistic Regression
• Clustering | Assignment
  
  kmeans, gaussian mixture model, and single-link agglomerative clustering
• Neural Network | Writeup
• Concurrent Jacobi Iteration | Writeup

C

• File Browser
• Command Line Interpreter
• Piggy: Networking Tool

Writing

• Deep Learning and Multivariate Features for Online Anomaly Detection in Network Traffic (Summer 2016)
• Matrix Factorization Notes (Summer 2015)
• Koch Snowflake (Summer 2014)
• Tromino Puzzle (Fall 2014)
  
• On Meaning (Spring 2014)
• Language Logic and Reality: A Stoic Perspective (Spring 2013)
• Greek Clause Structure: Deriving free constituent order in Standard Modern Greek (Spring 2014)
• Ambiguity, Humor, and Grice’s Cooperative Principle (Spring 2014)
• Subspaces of Linear Algebra (Fall 2012)
• Elementary Number Theory (Spring 2012)
• Germature (Summer 2012)
• Crisis: Extensions in Meaning from Renaissance to Contemporary Times (Spring 2011)
• The Parable of Giordano Bruno (Winter 2010)

Tutorials

• (Winter 2017) Writing and Distributing Open Source Python Software
• (Fall 2016) Introduction to Tensorflow (Neural Networks)
  materials
  
• (Spring 2016) Introduction to Matlab
  materials
• (Spring 2016) Introduction to ANTk (loader module)
• (Spring 2016) Introduction to ANTk (config module)
• (Spring 2016) Introduction to ANTk (generic_model module)