Projects
Worked with the University of Washington Bothell and Pacific
Northwest National Laboratory on a research project sponsored by the
Mathematical Association of America. Processed and analyzed
extensive genome sequence data using Python and BioPython for a
multitude of genera, focusing on k-mer frequency distributions.
Applied statistical models and machine learning techniques to
compare genomic patterns across bacteria and predict DNA sequence
characteristics. Utilized neural networks to classify and predict
DNA sequences accurately. Presented findings through visualizations,
reports, and presentations.
Jan 2024 - Present
Leveraged Tableau for advanced visual analytics of Edmond School
District survey responses, focusing on student perceptions of
cultural and linguistic appreciation within the education system.
Employed data cleansing techniques in Excel to ensure accuracy and
quality of data prior to analysis. Synthesized insights and created
an impactful presentation using PowerPoint to communicate findings
to the Edmond School District.
Jan 2023 - Mar 2023
Used Python, NumPy, Pandas, Matplotlib, and data analysis to develop
and assess a range of stock trading algorithms. Utilized historical
data obtained through APIs to thoroughly test the algorithms for
their performance and effectiveness, demonstrating strong
quantitative and analytical abilities
Mar 2021 - Nov 2021
Gathered, cleaned, and analyzed a decade of weather and sensor data
using Python and Excel. Presented findings in a research paper and
presentation, demonstrating strong analytical and communication
skills.
Feb 2021 - Jun 2021
Used NumPy and Numba to calculate in two minutes up to 300 million
points and their corresponding roots for two nonlinear equations
using newtons method with 12 digits of accuracy.
Sep 2023 - Dec 2023
Used Python, specifically NumPy, OpenCV, and Numba, to simulate the
behavior of millions of particles in real-time.
Sep 2023 - Dec 2023
In a personal project that leveraged Python, OpenCV, and NumPy, I
used my knowledge of computer vision and pathfinding by applying
object recognition techniques to analyze a map image. The project's
objective was to accurately identify the starting location's
coordinates and orientation, followed by calculating the optimal
path to the end location through the implementation of the A*
pathfinding algorithm. I furthered its capabilities by optimizing
the system to work in real-time.
Aug 2021 - Sep 2021