Pamela Toman is interested in structure: she relishes discovering organization in a mass of information and using small blocks of meaning to build new capabilities.
Pamela works for Palo Alto Networks, building machine learning products that unearth and help remediate dangerous IT devices that no one was previously tracking. She loves that her work affects real people and systems; each Fortune 500 misconfiguration put to rest helps her sleep easier at night.
Pamela Toman graduated from the Computer Science program at Stanford University with a Masters’ specialization in artificial intelligence. Her undergraduate work focused on natural language processing; she engaged Linguistics and Computer Science at Georgetown University, where she graduated first in her school, and interned in language identification & modeling. Between undergrad and graduate school, she provided computational and quantitative analytic consulting as a data scientist at Booz Allen Hamilton and NSI, Inc., and she developed customer retention models in PySpark as a graduate intern at Allstate.
Pamela Toman served on the Board of Directors of the Vienna Wireless Society and of DC’s Different Drummers. She volunteered with the Literacy Council of Northern Virginia and her California library’s ESL book club, and she taught language, culture, and their intersection in Modern Standard Arabic and in German for multiple summers at Concordia Language Villages. She spends her free time curling with the Silicon Valley Curling Club, gardening, playing the clarinet and alto saxophone, on the amateur radio bands, reading speculative and non-fiction, and hiking in state and national parks.