CSE 520 Colloquium/eScience seminar – Thursday, November 8, 3:30 pm, EEB-105

Hello,

Please join CSE 520 Colloquium and eScience Institute on Thursday, November
8, 3:30 pm in EEB-105. Refreshments will be provided.

*Emily Fox** (UW, Statistics)*

Emily Fox is an Assistant Professor in the Department of Statistics at the
University of Washington, having joined in 2012 from a prior position at
the Wharton Department of Statistics, University of Pennsylvania. From
2009-2011 she was a postdoc in the Duke Statistical Science Department, and
received her S.B., M.Eng., E.E. and Ph.D. in EECS at MIT. Her doctoral
thesis was awarded the 2009 Leonard J. Savage Thesis Award in Applied
Methodology and the 2009 MIT EECS Jin-Au Kong Outstanding Doctoral Thesis
Prize. Her research interests include Bayesian nonparametrics, Bayesian
dynamic modeling and time series analysis. The work emphasizes methodology
for high-dimensional, sparsely sampled data with applications in
neuroscience, health monitoring, and finance, amongst others.

*Bayesian Dynamic Modeling: Sharing Information Across Time and Space*

* *

In this talk we will highlight some of the benefits and challenges
associated with harnessing the temporal structure present in many datasets.
We focus on Bayesian dynamic modeling approaches, and in particular, the
idea of sharing information across time and "space", where space
generically refers to the dimensions of the time series. We exploit
nonparametric and hierarchical models to capture repeated patterns in time
and similar structure in space, enabling the modeling of complex and
high-dimensional time series. Applications of such approaches are quite
diverse, and in this talk we will demonstrate this by touching upon our
work in the tasks of speaker diarization, analyzing human motion, detecting
changes in volatility of stock indices, parsing EEG, word classification
from MEG, and predicting rates of violent crimes in DC and influenza rates
in the US.

*Upcoming Seminars:*

* November 14, 4 PM (EE303)

*Ian Gorton * (PNNL)

Velo: A Knowledge Management Framework for Modeling and
Simulation

* November 28, 4 PM (EE303)

*Andrew White * (UW, Chemical Engineering)

Using computational approaches to mimic nature and the
pursuit of blood resistant biomaterials

* December 5, 4 PM (EE303)

*Christos Kozanitis * (UW, Chemical Engineering)

Querrying the genome with GQL

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