Experience

Runway
• Mexico
• Technology, Information and Media
• Staff Machine Learning Infrastructure Engineer

  • May 2023 - Present


Doma

• Poland
• Retail Office Equipment
• 1 - 100 Employee

• Machine Learning Engineering Manager

  • Sep 2021 - Apr 2023

• Senior Staff Machine Learning Engineer

  • Jul 2021 - Sep 2021

• Staff Machine Learning Engineer

  • Apr 2021 - Jul 2021

• Staff Data Scientist

  • Jan 2020 - Apr 2021

• Senior Data Scientist

  • May 2019 - Jan 2020


Orbital Insight, Inc.
• Software Engineer - Computer Vision/Deep Learning

  • Oct 2016 - May 2019


NASA Langley Research Center

• United States
• Aviation and Aerospace Component Manufacturing
• 700 & Above Employee

• Data Analyst, Applied Machine Learning

  • Nov 2015 - Sep 2016

  At NASA, I worked on a variety projects that utilized machine learning to solve problems in science and engineering. Here are some of my accomplishments: Implemented new convolutional neural network architecture for image segmentation based on the encoder-decoder model that led to a 1,000 time speedup over previous window-based approach. Code was developed in Lua and utilized the Torch library. Developed an instance-based image retrieval system that allows for retrieval… Show more At NASA, I worked on a variety projects that utilized machine learning to solve problems in science and engineering. Here are some of my accomplishments: Implemented new convolutional neural network architecture for image segmentation based on the encoder-decoder model that led to a 1,000 time speedup over previous window-based approach. Code was developed in Lua and utilized the Torch library. Developed an instance-based image retrieval system that allows for retrieval based on visual similarity of the images or the faces of people in the images for NASA Langley's catalog of technical images. Code was implemented in Python using the libraries such as pycaffe (CNNs), Openface (face recognition), and Falconn (locality sensitive hashing). Created content for an internal machine learning website that provided a gentle introduction to fundamental concepts of machine learning (e.g. supervised vs. unsupervised) and compiled summaries of external online resources for learning about machine learning for scientists and engineers at Langley Research Center who are interested in utilizing machine learning for their work.

• Pathways Intern - Big Data and Machine Intelligence

  • May 2014 - Nov 2015

  As an intern, I researched and implemented methods for segmenting damage in images of materials such as carbon fiber. Results of this work, which utilized convolutional neural networks, were presented as a poster at the 42nd Annual Review of Progress in Nondestructive Evaluation and subsequently published as a paper in the conference proceedings. At the conclusion of the internship, I was offered and accepted the opportunity to continue at NASA Langley as an employee.



Old Dominion University

• Higher Education
• 700 & Above Employee

• Graduate Teaching Assistant

  • Aug 2013 - May 2014

  As a T.A., I taught a lab for an "Information Literacy" course and graded papers for an online "Computers in Society" course. As a T.A., I taught a lab for an "Information Literacy" course and graded papers for an online "Computers in Society" course.