Julia Christina Costacurta
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PhD Candidate
Stanford University |
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Julia is a PhD candidate in Electrical Engineering at Stanford, advised by Scott Linderman. Her research area is computational neuroscience, and she’s specifically curious about the ways that statistical models can help us understand and uncover structure in the rich datasets present in neuroscience. Outside of research and teaching Julia enjoys reading, sewing, and rock climbing. |
Workshop: Exploring Hidden Markov Models
June 29; 11:00am - 12:00pm, PST
June 29; 11:00am - 12:00pm, PST
Hidden Markov Models (HMMs) are used to describe and analyze sequential data in a wide range of fields, including handwriting recognition, protein folding, and computational finance. In this workshop, we will cover the basics of how HMMs are defined, why we might want to use one, and how to implement an HMM in Python. This workshop might be of particular interest to attendees from May 25’s “Intro to Markov Chains and Bayesian Inference” session. Introductory background in probability, statistics, and linear algebra is assumed.