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Events for October 25, 2023
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PhD Thesis Defense - John Francis
Wed, Oct 25, 2023 @ 10:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Thesis Proposal - John Francis
Committee Members: Mike Zyda, Carl Kesselman, Jernej Barbic, Scott Fraser, Kate White
Title: Neural Network Integration of Multiscale and Multimodal Cell Imaging Using Semantic Parts
Abstract: The structural modeling of cells can be accomplished by integrating images of cellular morphology from multiple scales and modalities using a parts based approach. In this thesis, we demonstrate a method for combining the statistical distribution of structures from x-ray tomography and fluorescence microscopy using neural networks to predict the localization of high resolution components in low resolution modalities by using the single cell as a shared unit of transferLocation: Michelson Center for Convergent Bioscience (MCB) - 102
Audiences: Everyone Is Invited
Contact: Melissa Ochoa
Event Link: https://usc.zoom.us/j/5585232420?pwd=QmZSRXI4NkdiMWtXWnp2Q2Q3N1pSdz09
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.
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PhD Thesis Defense - Georgios Papadimitriou
Wed, Oct 25, 2023 @ 11:00 AM - 01:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Thesis Defense - Georgios Papadimitriou
Committee Members: Ewa Deelman (chair), Viktor Prasanna, Aiichiro Nakano
Title: Cyberinfrastructure Management For Dynamic Data Driven Applications
Abstract: Computational science today depends on complex, data intensive applications operating on datasets from a variety of scientific instruments. These datasets may be huge in volume, may have high velocity or both, raising a major challenge of how scientists can analyze these datasets. On the other hand, workflows processing these datasets might need to respond to changes in the processing load e.g, increases in data flow, in order to maintain a steady and predictable turnaround time.
In this thesis we present our efforts to improve the performance of these data intensive application systems. We develop new tools that extend the functionality offered by the CI, and we provide a methodology to capture end to end performance statistics of the data intensive workflows. Additionally, we evaluate how the choices during the acquisition and configuration of resources affect the performance of the data intensive workflows. Finally, we answer the fundamental question of how scientists can manage the CI and apply policies that can help their applications meet their constraints .e.g, turn around time, by avoiding network degradation. We develop methodologies that take place during the planning phase of the workflows, and can reduce their peak network requirements. We also develop active approaches that can be applied and reduce the per workflow network requirements during their execution, using a workflow ensemble manager and application aware software defined flows.
Location: Henry Salvatori Computer Science Center (SAL) - 213
Audiences: Everyone Is Invited
Contact: Melissa Ochoa
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Computer Science General Faculty Meeting
Wed, Oct 25, 2023 @ 12:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
Receptions & Special Events
Bi-Weekly regular faculty meeting for invited full-time Computer Science faculty only. Event details emailed directly to attendees.
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Invited Faculty Only
Contact: Assistant to CS Chair
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.
