RESUME
GRADUATE EDUCATION
I am currently a research Master’s student at Stanford University. I work under Rosemary Knight in the geophysics department’s environment geophysics group. I study how remote sensing data can be used to enhance groundwater models used to help inform groundwater sustainability agencies as they develop groundwater sustainability plans in accordance with the Sustainable Groundwater Management Act passed by the state of California in 2014. I utilize my skills in Python and data science to manage remote sensing data obtained from Google Earth Engine. I also have done research involving interpolating groundwater levels using well data.
I received a world-class geophysics education from the Colorado School of Mines. I graduated summa cum laude with my bachelor’s of science in geophysical education in May 2019. I was trained in all of the main geophysical methods: gravity, magnetics, electrical, electromagnetic, and seismic. I also took advanced coursework in well logging, remote sensing, and data science/machine learning. My education included a field camp in Pagosa Springs, where my class investigated the geothermal system underneath Pagosa Springs. This invaluable experience taught me practical geophysical skills regarding survey design, instrument usage, and data wrangling.
UNDERGRADUATE
EDUCATION
SKILLS
Geophysics: Seismic interpretation, mapping, and AVO analysis using Petrel; seismic forward modeling; well log interpretation and rock physic modeling using RokDoc and TechLog; geophysical field methods including gravity and magnetics, electrical, electromagnetics, and shallow seismic; geophysical inversion
Computer Science: Programming in Python (most proficient), MATLAB, R, and C++; machine learning using TensorFlow/Keras, PyTorch, and Sci-kit Learn; database management using SQL and Pandas; working in a Linux OS; version control using Git; cloud solutions using AWS; distributed data processing with Hadoop and Spark/PySpark; image processing using OpenCV
Geology: Drawing, mapping, and reading geologic and topographic maps; familiarity with geomorphic and structural features; understanding and working with stratigraphic concepts; comprehension of basic sedimentology; data plotting and map creation in ArcGIS
Work Experience
Shield AI (Formally Heron Systems Inc.),
Rosslyn VA – Machine Learning Engineer
DECEMBER 2020 – DECEMBER 2021
At Shield AI, I worked with talented software and machine learning engineers to develop models that solve the toughest problems in the defense industry. I trained and deployed models both low-side and high-side using PyTorch, Catalyst, Flask, and Gunicorn. I also helped developed heuristic models for some other tasks not as well suited to machine learning, as well as helped refactor computation code to be more time efficient.
ExxonMobil Corporation,
Houston TX – Geoscientist
FULL-TIME: SEPTEMBER 2019 – PRESENT
INTERNSHIP: AUGUST 2018 – NOVEMBER 2018
My work at ExxonMobil’s Upstream Integrated Solutions company involved researching the latest cutting-edge deep learning technologies in an effort to automate seismic interpretation. My particular work involved researching strategies related to automatic labeling by generating seismic images from geologic models. This work involves a combination of interfacing with business units to determine their needs, rock physics modeling, seismic forward modeling and QC work, and machine learning model tuning. This workflow was done via Python and Tensorflow scripting, with additional geophysical analysis performed with Petrel and RokDoc. Our team’s work had helped reduce cycle time for interpretation by up to eight months in some business units.
Work Experience
Work Experience
United States Geological Survey,
Golden CO – Physical Science Intern
INTERNSHIP: APRIL 2017 – JULY 2018
At the USGS, I learned from some of the best minds in geologic hazards research. I studied landslide forecasting and threshold determination, seeking to answer the question: “Given a database of landslides and the hydrological and meteorological conditions in which they occurred, can we determine the best threshold for predicting times when landslides are likely to occur?” This research became the foundation for the first scientific paper I co-authored, and I later presented this research at a poster presentation during AGU 2018 in Washington D.C.