Eagle Scout is the highest rank in Scouting and requires sustained leadership, community service, and a capstone project. I proposed, planned, fundraised, and led the construction of custom helmet and bat racks for the baseball and softball dugouts at John Glenn High School.

• Defined scope and design; coordinated with school staff and coaches
• Raised funds, sourced materials, created a detailed bill of materials
• Scheduled and led volunteer crews; safety briefing and task breakdown
• Managed timeline and budget; delivered durable, finished racks on time

Ran a solvent screen (acetone, butanediol, ethanol, DMSO, etc.) and used %-solubility data to estimate the lignin’s Hansen parameters (δD, δP, δH). The UI then matches the estimated HSP to a solvent database to rank candidate dissolvers/blends for that particular lignin (structure varies by source, so HSPs differ). Code/data are private to Lignopure.

Prazise reads heart rate, HRV, sleep, and workouts to deliver precise training — personalized to you, not a template. It adapts sessions to recovery, explains the why, and keeps data private by design.

• Reads HR, HRV, sleep, and recent sessions; calibrates to the athlete
• Daily precision session suggestions with targets, cues, and post-run insights
• Recovery-aware adjustments after tough/breakthrough days; overtraining risk signals
• Privacy-first: encrypted at rest, deletable on request, never sold
• Device-friendly: Garmin, Polar, Suunto, Apple Health, Fitbit (planned)

Developed a climate-aware Dynamic Bayesian Decision Network (DBDN) to study how climate indicators and financial variables interact over time and influence market risk regimes. Built the full data pipeline, trained the network, and evaluated whether climate information improves regime detection and portfolio decisions relative to market-only models. Results showed that financial indicators remained the primary drivers of regime changes, while climate variables influenced markets indirectly through pricing and policy channels, contributing to smoother regime transitions and improved risk-adjusted performance.

• Integrated climate indicators (temperature anomalies, carbon prices, climate policy uncertainty) with core market variables
• Designed and trained a Dynamic Bayesian Decision Network with regime, decision, and utility nodes
• Learned and visualized directional dependency structures using DAGs
• Ran rolling-window backtests comparing climate-informed models to market-only baselines and a 60/40 portfolio