I am a data scientist, currently with the National Renewable Energy Lab. Through my career I have worked in fields spanning from ocean physics to transportation, energy, IoT, and beyond. I use a variety of machine learning techniques, spatio-temporal statistics, and numerical simulations to discover relationships in the underlying data and to build predictive models that can turn insight into actionable intelligence.
Distribution network operators (DNOs) face enormous pressure to properly prepare for widespread power outage events, which are mostly due to big storms. In this project, MeteoGroup partnered with DNOs in the UK to develop advanced machine learning models that leverage our weather data and forecasts by predicting the expected volume of weather-related network faults. This product is currently being developed for operational use.Energy, Machine Learning, Data Science
In this research project I created a sample dashboard for monitoring data from a simulated sensor. The dashboard allows the user to generate new data, test how different linear model fitting techniques change with degrees of freedom, and to investigate the limitations of using certain linear models for predicting future sensor values.IoT, Anomaly Detection, Trend Analysis
All cars since the mid-1990s have been equipped with sensors to measure the vehicle's 'diagnostics. Modern vehicles record information from significantly more vehicles. I am actively working with data from connected cars and from simulated vehicles to identify features about the roads from driver-generated data. The above animation shows data from cars in Ann Arbor, MI and demonstrates how windhshield wiper activity compares to weather radar intensity.Connected Cars, Transportation, Big Data
As modern energy grids evolve to handle the growing number of renewable energy generators, energy providers are also evolving their operations to use data-driven approaches for outage prediction and management. In this Proof-of-Concept project, I was the lead data scientist from T-Systems International to investigate how the structure of a power grid could lead to increased probability and severity of outages in Western Germany. My approach used network analysis, graph theory, and machine learning to uncover the relationship among the network structure and associated outages.Energy, Network analysis, Machine Learning
I contributed to the development of algorithms to detect oil and gas bubbles in time-lapse video from the deep Gulf of Mexico. These videos were recorded by the Ian MacDonald group at Florida State University by placing cameras in the deep sea near oil and methane release sites. The algorithms have been used to quantify the volume release rate of naturally-released bubbles and are presented in Marine and Petroleum Geology.Image recognition, Oil and Gas, Deep Sea, Geology
In July 2015, I was a member of the three-person science observing crew aboard DSV Alvin to discover a shipwreck at 2500m beneath the ocean's surface. The shipwreck, found off the coast of North Caolina, is believed to date back to the 18th Century. This discovery was featured on many international news sites, such as CNN, NBC, The Washington Post, and The Boston Globe.Shipwreck, Ocean Exploration, Deep Sea
Ski resorts depend on a reliable amount of artificially-generated snow for their daily wintertime operations. However, the quality and quantity of artifical snow generation can vary significantly with the ambient weather. Together with the Research & Innovation division of MeteoGroup and TechnoAlpin, we demonstrated our ability to save more than 100€ per snow cannon per day by using hyper-local weather forecasts to optimize snow generation times.Weather Forecasting, Optimization, Snow Cannons
The first ever sampling of Gulf Stream waters in the South Atlantic Bight with an autonomous underwater vehicle was performed in March 2014. I used the glider output to compare anomolous cross-shelf fluxes of heat and salt in the vacinity of the Gulf Stream. This work was submitted to Marine TechnologyGliders, Gulf Stream
National Renewable Energy Laboratory
2019 - present • Golden, CO
2017 - 2018 • Berlin, DE
Telekom Innovation Labs/TU Berlin
2015 - 2016 • Berlin, DE
NC State University
2013 - 2015 • Raleigh, NC
Florida State University Center for Ocean-Atmospheric Prediction Studies
2006 - 2013 • Tallahassee, FL
Florida State University Ahlquist Lab
2003 - 2006 • Tallahassee, FL
StormCenter Communications, Inc.
2003 • Columbia, MD
PhD, Oceanography • 2013 My dissertation work investigated the circulation of coastal ocean waters in the Northeast Gulf of Mexico. The work used an understanding of ocean physics to understand how the larvae of gag grouper could be transported from deep waters to shallow coastal waters. I used numerical modeling approaches with a high-performance computing system. My primary advisors for this work were Dr. Eric P. Chassignet and Dr. Steven L. Morey.
B.S., Meteorology (cum laude) • 2007
B.S., Mathematics (cum laude) • 2007
Internet of Services Lab
Technische Universität Berlin, Winter 2015/2016 and Summer 2016
MEA642: Observational Methods and Data Analysis in Marine Physics
NC State University, Spring 2014
OCE4017: Issues in Environmental Science
Florida State University, Spring 2013
Stars Middle School Career Day
Tallahassee, FL, May 2012
Antarctic Research Facility Tour
Florida State University, July and December 2011
Young Scholars Program
Florida State University, Summer 2009
OCE4017: Issues in Environmental Science
Florida State University, Fall 2008
TU Berlin Report: http://www.snet.tu-berlin.de/...
Telekom Press Release: http://www.telekom.com/media/company/321718
ELTE Press Release: http://www.elte.hu/...
Hír TV (in Hungarian language, 09:15-11:58): http://aszt.inf.elte.hu/...
NC State Press Release: https://news.ncsu.edu/2015/07/shipwreck-2015/
CNN Report: http://edition.cnn.com/...
NBC Report: http://www.nbcnews.com/news/...
Washington Post: http://www.washingtonpost.com/news/...
Boston Globe: http://www.bostonglobe.com/news/...
D.M. McVeigh, D.B. Eggleston,