Select a calendar:
Filter August Events by Event Type:
SUNMONTUEWEDTHUFRISAT
Events for August 30, 2022
-
New & Continuing MS Student Group Advising Session (CSCI/DSCI)Tue, Aug 30, 2022 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Workshops & Infosessions
If you are a New or Continuing MS student in the Computer Science Department or Data Science Program and have any questions or need assistance, please join us for today's optional group advising session via zoom. Access instructions will be sent to students directly. Note: D-clearance is not granted during advisement sessions. All requests for d-clearance must go through the myViterbi portal.
Location: Zoom
Audiences: Graduate
Contact: USC Computer Science
-
CS Undergraduate Live Chat Drop-in Advisement
Tue, Aug 30, 2022 @ 01:30 PM - 02:30 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
CS Advisors will be available on Tuesdays/Wednesdays/Thursdays this fall from 1:30pm to 2:30pm to assist undergraduates in our four majors (CSCI, CSBA, CSGA, and CECS) via Live Chat. Access the live chat through our website at https://cs.usc.edu/chat
Location: Live Chat on Website
Audiences: Undergrad
Contact: USC Computer Science
-
New & Continuing MS Student Group Advising Session (CSCI/DSCI)
Tue, Aug 30, 2022 @ 03:30 PM - 04:30 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
If you are a New or Continuing MS student in the Computer Science Department or Data Science Program and have any questions or need assistance, please join us for today's optional group advising session via zoom. Access instructions will be sent to students directly. Note: D-clearance is not granted during advisement sessions. All requests for d-clearance must go through the myViterbi portal.
Location: Zoom
Audiences: Graduate
Contact: USC Computer Science
-
PhD Defense - Kuang Liu
Tue, Aug 30, 2022 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Candidate: Kuang Liu
Title: Simulation and Machine Learning at Exascale
Zoom ID:
994 8935 4140 (pass code: 722332)
Committee:
Aiichiro Nakano
Rajiv K. Kalia
Priya Vashishta
Abstract:
Machine learning (ML) is revolutionizing scientific research, by utilizing its ever-growing capability of knowledge discovery from massive simulation data. With the recent arrival of exascale computer, new opportunities and challenges are emerging to maximize the synergy between exaFLOPS supercomputers and ML-boosted computational science. This thesis addresses two important and intertwined problems: (i) developing efficient billion-core parallel algorithms for scientific simulations, and (ii) designing domain-specific deep neural networks for scientific data analysis. To achieve these goals, I have designed a series of algorithms with specific focus on molecular dynamics simulations and protein folding as archetypal scientific applications. Specific contributions include: (i) communication-minimizing shift-collapse algorithm for n-tuple computation on central processing units; (ii) tuple-decomposition for graphics processing unit (GPU) acceleration of n-tuple computation; (iii) graph neural network (GNN) to classify different crystalline phases; and (iv) multiscale neural network to predict protein contact map.
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
