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Trained as a computational neuroscientist, I've spent the past 11 years processing, storing, analyzing, and visualizing complex datasets.

Born and raised in New Orleans, I attended Tulane University, where I received my BS and MS degrees in Neuroscience. There, I began designing and implementing data processing architectures to support analysis of complex datasets containing behavioral and electroencephalogram (EEG) data.

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In 2015, I moved to New York and joined a lab that performed neuroscientific research at a larger scale: tens of thousands of participants with not only behavioral and EEG data but also detailed genealogical, survey, and genetic information. I co-wrote a Python module for building, updating, and accessing the lab database, which contained 100k+ records from disparate sources. I also wrote a module for analyzing and plotting EEG data, and I used the code I wrote to create visualizations supporting the lab's grants and publications.
 

From 2017 to 2022 I completed a Ph.D at UCLA, where I focused on creating computational models that could explain neural functions. Through my work, I gained foundational knowledge of statistics and machine learning from the neuroscientific perspective, and I continued refining my skills in handling large and complex datasets.

My intention for the next long-term chapter of my life is to bring my skills and knowledge to industry.