Dan Shiebler is the Head of Machine Learning at Abnormal Security, where he leads a team of 40+ detection engineers building AI systems that fight cybercrime. His team has created the world’s most advanced messaging cyberattack detection system and protects many of the world’s largest companies, including 12% of the Fortune 500.
He most recently managed the Web Ads Machine Learning team at Twitter. Previously, he worked as a Staff ML Engineer at Twitter Cortex and a Senior Data Scientist at TrueMotion. Dan has also spent time in academia and his PhD at the University of Oxford focused on applications of Category Theory to Machine Learning.
He most recently managed the Web Ads Machine Learning team at Twitter. Previously, he worked as a Staff ML Engineer at Twitter Cortex and a Senior Data Scientist at TrueMotion. Dan has also spent time in academia and his PhD at the University of Oxford focused on applications of Category Theory to Machine Learning.