I’m a musician, as well as a machine learning scientist and engineer with 5 years of industry experience training AI models and deploying them to production.

I have made a career out of applying statistical and deep learning techniques to detect threats such as knives and guns in CCTV video and electromagnetic sensor data. I have experience with deep residual networks, tree-based models, transformer models (link), anomaly detection, A-B testing, hypothesis testing, and vector embeddings for NLP (link).

Interestingly enough, I have seen success in my current field in part because of the large overlap between audio processing and electromagnetic signal processing. Techniques such as filtering, resampling, gating, and spectrogram analysis have wide applications in both fields and allow me to leverage learnings from my music hobby in my data science work.