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AC@alancarroll
Dynamic problem solver with a background in systems neuroscience and data science.
United StatesI 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.
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Work history, roles, and key accomplishments
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.
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.
TDThe University of Texas at Dallas
Pioneered automated touchscreen and auditory behavioral platforms and developed an automated neurophysiology data-preprocessing suite, doubling spatial efficiency and reducing hardware costs 10x while improving reproducibility and throughput.
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.
Degrees, certifications, and relevant coursework
Doctor of Philosophy, Systems Neuroscience
Ph.D. in Systems Neuroscience focused on auditory neurophysiology and automated data analysis tools, completed August 2025.
TDMaster of Science, Applied Cognition and Neuroscience
M.S. in Applied Cognition and Neuroscience with work on automated preprocessing and analysis of auditory neurophysiological data.
TDBachelor of Science, Neuroscience
B.S. in Neuroscience with involvement in developing behavioral and training systems for auditory research.
Software and tools used professionally
United StatesYou can contact Alan and 90k+ other talented remote workers on Himalayas.
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