Alan Carroll
@alancarroll
Dynamic problem solver with a background in systems neuroscience and data science.
United StatesWhat I'm looking for
I am a dynamic problem solver with a background in systems neuroscience and data science. I am passionate about using interdisciplinary approaches to understand complex systems and solve real-world problems. With a strong foundation in Python, JavaScript, MATLAB, R, Clojure/script, and WASM, I bring versatile skills and creative agility to move projects forward.
One of my notable achievements is pioneering an automated touchscreen platform to evaluate learning and memory in rodents. I devised a modular software architecture that facilitated custom task delivery and real-time monitoring through a central server, accelerating dynamic experimental throughput. This platform achieved a 2x reduction in spatial requirements and a 10x reduction in cost compared to commercial alternatives, while offering increased customizability and user-friendliness.
In addition, I have developed an automated data preprocessing tool using a scientific Python stack, enhancing the efficiency and reproducibility of auditory neurophysiological data analysis. I crafted a user-friendly GUI using Kivy and matplotlib, streamlining the data exploration process and enabling interactive engagement with large and complex auditory datasets.
Experience
Scientist
University of Texas at Dallas
Pioneered an automated touchscreen platform for rodent learning and memory evaluation. Developed modular software for custom tasks and real-time monitoring, significantly improving experimental throughput.
Analyst
University of Texas at Dallas
Engineered a scalable auditory training system for rodents, improving productivity with parallel and remote operation capabilities. Adapted research operations to comply with COVID-19 safety measures.
Programmer
University of Texas at Dallas
Created an automated data preprocessing tool for auditory neurophysiology, using Python. Designed a GUI for efficient data exploration, enhancing data analysis reproducibility and user engagement.
Tech stack
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