Applied Machine Learning | Time-Series Modeling
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I’m an applied machine learning practitioner interested in building models that provide an edge over uncertainty
My work focuses on time-series modeling, probabilistic forecasting, and real-world decision systems, problems where demand, risk, or behavior evolve over time and must be modeled under uncertainty.
Recently I’ve been developing forecasting and probabilistic modeling projects in Python, exploring areas such as sequential prediction, calibration, and demand modeling. I’m particularly interested in systems where machine learning directly influences decisions, such as pricing, forecasting, and resource allocation.
SWE Intern – HGW LLC, June 2022 - August 2022
Data Annotation Fellow – Handshake AI 2025 - present
B.S. Computer Science & Audio Production, MTSU 2025
