At Max Planck Institute & University of Göttingen, I developed Python pipelines to process, index, and model more than 10 million time-series data points. I also built parameter-optimization frameworks to calibrate complex physical models.
Across 16 stars, I applied multiple period-search methods and detected periodic signals in 25% of the sample. I designed and validated a quantitative indicator that separated stellar activity from noise in more than 14,000 spectra across 345 stars, overturning a 50-year-old model.
I formed and led international research teams whose work resulted in 16+ peer-reviewed publications and 20+ conference presentations. I also developed automated transient and anomaly detection algorithms and mentored undergraduate and graduate students.
As a self-employed Technical Project Manager & Research Collaborator, I managed efficiency upgrades for residential solar, HVAC, and water-retention systems. Quantitative monitoring reduced grid energy consumption by 99%, HVAC energy use by 40%, water consumption by 27%, and overall carbon footprint by 45%.
