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R&D Engineer at the University of Arizona studying the biology of aging || Robotics || AI || Data science || Biology ||
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Assessing your cultural and operational fit
University of Arizona
Data Scientist
June 29, 2026 – Present
Mask-Fixer
March 10, 2025 – March 17, 2025
this is a GUI that allows the user to fix simple masks for Neural Networks
View Projectrpi_camera_tests
November 25, 2024 – December 1, 2025
testing outputs for raspberry pi cameras primarily using python
View Projectentropy_DIC
February 18, 2022 – Present
Using a 2D entropy filter to segment DIC (Differential Interference Contrast) imaging of cells
View ProjectCNN_regression
February 2, 2022 – September 1, 2022
This is a simple CNN model used for image recognition and regression
View Projectpython_to_GRBL
December 1, 2021 – January 17, 2024
A simple open-source python 🐍 to grbl 🤖 sender || Controlling 3-axis GRBL/CNC/gcode machines with python over a serial/usb connection that waits for completion of movement before sending the next command
View ProjectDynamic_Unet
August 31, 2021 – December 9, 2021
A somewhat dynamic implementation of the Unet CNN that can be easily changed modified
View ProjectSICKO
February 17, 2021 – January 6, 2025
Systematic Imaging of C. elegans Killing Organisms
View ProjectLightSaver
February 17, 2021 – Present
Fluorescent analysis of individualized C. elegans without using neural networks
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and academic in nature, focusing on image processing, machine control, and basic CNNs. While demonstrating initiative, the breadth of projects and technologies is somewhat limited for a senior Data Scientist role. The single listed professional experience as 'Data Scientist' at a university, with a future start date, provides insufficient information to assess cultural fit or alignment with typical industry practices. The projects indicate a strong interest in research-oriented or niche applications of data science.
Soft Skills & Operational Fit
The candidate's project descriptions are concise, but lack detail regarding problem-solving approaches, collaboration, or impact, making it difficult to assess soft skills or operational fit. The personal projects suggest a self-starter with an interest in practical applications.