Pamela Toman is a Sr. Principal Machine Learning Engineer at Palo Alto Networks, where she applies machine learning engineering to network security challenges. Since 2017, she has been unearthing shadow IT devices that no one was previously tracking, attributing those devices to the organizations that can remediate them, and monitoring the internet perimeters of organizations for dangerous exposures. She generates machine learning models at internet scale, builds on transport & application layer networking protocols, and has developed models across the attack surface management arm of cybersecurity. She loves that her work affects real people and systems. Each Fortune 500 misconfiguration put to rest helps her sleep easier at night. Prior to 2017, she spent nine years working on networks of human and disease data. She earned a Masters degree in Computer Science from Stanford University, where she specialized in Artificial Intelligence. Her undergraduate work focused on natural language processing. Pamela currently lives outside San Jose, California with her middle-school-music-teaching partner and their 2-year-old daughter; she loves vegetable gardening, amateur radio, speculative fiction, hiking in wine country and at the ocean, and curling.

Summits Attended: 2022 Pride

Diverse representation is a priority for us. We're proud to say that our Summit speakers are 80% queer women, 50% women of color, 25% Black & Latinx, and 15% transgender and gender nonconforming.