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Events for the 4th week of August
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MS - Group Advisement Session
Mon, Aug 19, 2019 @ 10:00 AM - 11:40 AM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Graduate
Contact: Art Perez
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MS- Group Advisement Session
Mon, Aug 19, 2019 @ 02:00 PM - 03:40 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Graduate
Contact: Art Perez
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MS - Group Advisement Session
Tue, Aug 20, 2019 @ 10:00 AM - 11:40 AM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Mark Taper Hall Of Humanities (THH) - 201
Audiences: Graduate
Contact: Art Perez
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MS - Group Advisement Session
Tue, Aug 20, 2019 @ 02:00 PM - 03:40 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Graduate
Contact: Art Perez
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MS - Group Advisement Session
Wed, Aug 21, 2019 @ 10:00 AM - 11:40 AM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Art Perez
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MS - Group Advisement Sessions
Wed, Aug 21, 2019 @ 02:00 PM - 03:40 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Graduate
Contact: Art Perez
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MS - Group Advisement
Thu, Aug 22, 2019 @ 10:00 AM - 11:40 AM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Graduate
Contact: Art Perez
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MS - Group Advisement
Thu, Aug 22, 2019 @ 02:00 PM - 03:40 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Graduate
Contact: Art Perez
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PhD Defense - Daniel Moyer
Fri, Aug 23, 2019 @ 09:30 AM - 11:30 AM
Thomas Lord Department of Computer Science
University Calendar
PhD Candidate: Daniel Moyer
Date: Friday August 23rd, 2019
Time: 9:30 am - 11:30 am
Location: GFS 213
Committee: Greg Ver Steeg, Paul Thompson, Aram Galstyan, Aiichiro Nakano
Title:
Representation Problems in Brain Imaging
Abstract:
Diffusion weighted Magnetic Resonance Imaging (dMRI) is a imaging modality that, conditional on direction, queries the propensity for water diffusion in living tissue. These images are desirable for studying tissues with anisotropic diffusion profiles, e.g. the white matter of the human brain. I here describe two problems at the interface between diffusion imaging and computational science, as well as proposed solutions for those problems, reconciling differences between current methodology, existing theory, and practical constraints.
The first part of this thesis describes methodology from the intersection of network science and neuroscience. Previous literature has worked to estimate white matter axon bundles (fasiculi) from dMRI. Combined with segmentations of the grey matter, this leads intuitively to the construction of macro-scale brain networks, where nodes are cortical regions and edges are estimates of axonal connections. The work I present here deconstructs this progression, reconciling the inherently spatially continuous cortex with discrete network theory. The resulting model is a generalization of discrete graphs, using point process theory to create continuous interaction densities (continuum adjacency functions).
The second part of this thesis describes a method for learning representations of data that invariant under changes in specified outside factors. These can be applied to diffusion imaging data, which in particular suffers from instrument/observer biases ("site/scanner" biases). Due to the relative complexity of the domain, modelling the particular effects of each instrument may be difficult; moreover, such an approach does not generalize to unseen instruments. Instead, the described method can learn representations that are minimally informed of the imaging site. Subsequent derived data will then be at least as uninformed of the site variable.
Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 213
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
