Siobhán is a software engineer with a passion for machine learning, mathematical optimization, and collaboration. 

She began her career in a neuroscience laboratory at Harvard Medical School, while moonlighting as a contemporary dancer. After several years of performing and NGO management, she returned to science to join the computational intelligence renaissance. She is currently building a predictive model for a transportation startup, collaborating on swarm intelligence optimization tools, co-producing a complexity modeling immersive study experience in partnership with Slow Research Lab in Amsterdam, and completing CS graduate coursework at Stanford. 

Siobhán has published research in Brain & Cognition, Neuroreport, and Model View Culture, and presented at the Conference on Complex Systems, Conference on Cognitive Neuroscience, AlterConf, PyLadies, and Temple University. She is a member of Bay Area Women in Machine Learning and Data Science and IEEE Computational Intelligence Society (CIS), and coordinates a monthly a machine learning working group in San Francisco (ML Study Hall). 

Siobhán composes music inspired by her research, and has shared original compositions at the DeYoung Museum, Yerba Buena Center for the Arts, Women's Building, and ODC Theater. Her work has received research funding from Movement Research, San Francisco Arts Commission, Puffin Foundation, and Jerome Foundation, as well as residencies from the Santa Fe Art Institute and Playa Summer Lake.

STACK: Python, C, tensorflow, keras, sklearn, PySwarms, PyMC3, vim, AWS