About me

Hi, I’m Dan Shiebler. I like math, history podcasts, fantasy novels, riding my bicycle, and traveling. I live in NYC.

Today I work as the Head of Machine Learning at Abnormal Security. I lead our team of 40+ detection engineers building AI systems that fight cybercrime. We deploy probabilistic models over realtime aggregates, neural network/tree-based classifiers over tabular data, and large language models (LLMs) over raw data. Our system is the world’s most advanced messaging cyberattack detection system. We protect many of the world’s largest companies.

Previously, I managed the Web Ads Machine Learning team at Twitter. Before that I worked as a Staff ML Engineer at Twitter Cortex and a Senior Data Scientist at TrueMotion.

I’ve also spent some time in Academia. My PhD at the University of Oxford focused on applications of Category Theory to Machine Learning (advised by Jeremy Gibbons and Cezar Ionescu). Before that I worked as a Computer Vision Researcher at the Serre Lab.

I Tweet @dshieble and my linkedin and github are usually somewhat up-to-date.