About / Bio
Background
I work at the intersection of signals & systems, controls, machine learning, and neuroengineering. I care about mathematically grounded models that stay useful when deployed in real pipelines (latency, noise, and real-world constraints).
I attended Doral Academy Charter Middle/High School from 6th to 12th Grade, where I was active in Mu Alpha Theta, Zeta Omicron, Robotics Club, and Physics-Chemistry club. During these years, I attained many different national awards, especially in competitive math and robotics. Lastly, I was fortunate enough to attend Duke Tip, Awesome Math, and MathRoots Summer Camps.
I am most passionate about neuroscience, powerbuilding, and music. Since I can remember I was passionate about music, growing up with my father playing yacht rock, prog rock and disco classics; music is now ingrained in my faily life where I ocassionally DJ and produce music. Powerbuilding is a hobby I've been interested in since high school simply as a discipline exercise. Neuroscience is the latest of my interests, especially for understanding how we can engineer solutions to biological shortcomings.
Education
University of Florida — Ph.D., Electrical & Computer Engineering (Expected 2030)
University of Florida — B.S., Electrical & Computer Engineering (2020–2025)
Doral Academy Charter — Diploma, Science Technology Engineering and Mathematics (2013–2020)
Concentration: Analysis, Signal Processing & Machine Learning
Focus
Time-series ML theory and practice for biological signals (EEG, pupillometry, imaging). I build GPU-accelerated tooling when it materially improves iteration speed, reproducibility, and experiment throughput.
Signals & Systems
Time-series ML
Neuroengineering
GPU acceleration
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