Ph.D student in chemistry with a Bachelor of Science in physics (with honors). Two years experience in a collaborative software development environment as a controls engineer at SLAC National Accelerator Laboratory earning the SLAC Spot Award for Dependability. Certificate in data analytics and skills including Python, SQL, MongoDB, JavaScript/HTML, and PLC programming. Highly organized with experience balancing multiple responsibilities and a dedicated learner with a passion for problem solving. Quantitative analysis experience in a variety of technical environments and excellent written/oral communication skills to express ideas and learn from others.
Python, NumPy, pandas, Matplotlib, hvPlot, Flask, PySpark, SQLAlchemy/SQLite, scikit-learn, imbalanced-learn, TensorFlow/Keras, Jupyter Notebook, Google Colaboratory, C++, SQL, PostgreSQL, MongoDB, AWS RDS, AWS S3, JavaScript ES6+, D3.js, Plotly, Leaflet, GeoJSON, HTML5, Bootstrap, R, Tidyverse, MATLAB, Experimental Physics and Industrial Control System (EPICS), EPICS Display Manager, PLC, Tc2_MC2, Beckhoff, Excel/VBA, Tableau, Visual Molecular Dynamics, Visual Studio Code, Git/GitHub, SVN
Jupyter Notebook files to build, train, test, and optimize a deep neural network modeling charity success from nine features in a loan application data set relying on the TensorFlow Keras Sequential model with Dense hidden layers and a binary classification output layer.
CodeUnsupervised machine learning model pipeline for the clustering of cryptocurrencies including scaling, dimensionality reduction with principal component analysis (PCA), grouping using a K-means cluster model, and visualization with scatter plots.
CodeJupyter Notebook files containing supervised machine learning classification models along with oversampling, undersampling, and combination sampling techniques to classify loan applicants as low risk or high risk from other features in our data set.
CodeGoogle Colaboratory Notebook files for ETL pipeline of Amazon music reviews to an AWS PostgreSQL database and analysis of the ratio of five star reviews as it relates to participation in the Vine program.
CodeR Script files for the statistical analysis of car manufacturing data to identify predictive variables of fuel efficiency, collect summary statistics on suspension loads, and analyze the statistical differences among specific manufacturing lots relative to the population.
CodeWeb application with interactive maps of cities, airports, airline routes, and earthquakes from local JSON/JavaScript files and API calls to USGS GeoJSON sources.
CodeInteractive web scraping application acquiring Mars data, storing using MongoDB, and then visualizing in a Python Flask application.
CodeJupyter Notebook files for the analysis of weather data contained in a local SQLite database. We load this data using SQLAlchemy and query/summarize key difference in Hawaii weather data between the months of December and June.
CodeJupyter Notebook files for an Extract, Transform, Load (ETL) pipeline of movie data csv/json files extracted from web sources, cleaned/transformed using pandas, and loaded into a PostgreSQL database using SQLAlchemy.
CodeSchema/Entity Relationship Diagram and associated SQL queries written in PostgreSQL to generate a list of employees eligible for retirement, a breakdown of the number of retiring employees by title, and a list of the employees eligible for the mentorship program.
CodeJupyter Notebook files to retrieve and collect weather data and create maps for vacation plans based on user specified weather parameters using OpenWeatherMap and Google Maps APIs.
CodeJupyter Notebook files for the analysis and visualization of ride share data using pandas and Matplotlib to compare the success of ride share companies in rurual, suburban, and urban environments.
CodeJupyter Notebook files to read and analyze school district data and determine the top/bottom five performing school from metrics such as overall passing rate, average math/reading scores, and school size/type.
CodePython script to read a csv file containing vote counts in an election and report the voting breakdown by county and candidate to the console and an output file.
CodePLC library for LCLS optics designed with LCLSII-style Beckhoff motion control architecture.
CodePLC project and EPICS Input/Output Controller (IOC) for deployed LCLS optics MR1L0 and MR2L0 relying on lcls-twincat-optics library.
CodeCollection of device subclasses including LCLS optics defining Python interfaces to EPICS IOCs for staff scientists to operate instruments in IPython sessions.
Code