Research,
Teaching,
and Technical Community.

Continuing HPAI Forecasting Research

Continuing computational epidemiology and disease-forecasting research as a fully funded USDA ARS (NACA) graduate research assistant in the CVM Department of Pathobiology and Population Medicine, advised by Dr. Isaac Jumper.

Pursuing an M.S. in Veterinary & Biomedical Science with a Computational Biology concentration, integrating machine learning methods with veterinary epidemiology and population medicine coursework.

Forward-Looking HPAI Forecasting

Developed a leakage-safe, national-scale county-month forecasting framework for H5N1 HPAI across the conterminous United States, evaluating 40 model configurations across a 74,616-forecast rolling-origin backtest and deploying outputs into an interactive biosurveillance dashboard.

National HPAI Risk Classification

Developed the initial national-scale county-level HPAI risk classification and pseudo-forecasting models that became the foundation for the forward-looking system above, achieving 75%+ balanced accuracy on highly imbalanced (~1% positive) outbreak data and presenting findings to the USDA ARS Chief Scientist and multiple National Program Leaders.

Received the Judge's Choice Award at UTA College of Engineering Innovation Day (2026) for research conducted during this internship.

AI Community Programming

Scaled OpenAI’s official Discord community to 850k+ users, supporting global user education, technical discussion, and community programming around emerging AI tools. Collaborated with multiple internal teams, supporting large-scale community initiatives connecting users, creators, and technical audiences around emerging genAI models.

Operating Systems Instruction

Supported 120+ students through office hours, review sessions, and course support for scheduling, synchronization, deadlocks, memory management, and file-system concepts.