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Events for November 30, 2015
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Meet USC: Admission Presentation, Campus Tour, and Engineering Talk
Mon, Nov 30, 2015
Viterbi School of Engineering Undergraduate Admission
Receptions & Special Events
This half day program is designed for prospective freshmen and family members. Meet USC includes an information session on the University and the Admission process, a student led walking tour of campus, and a meeting with us in the Viterbi School. During the engineering session we will discuss the curriculum, research opportunities, hands-on projects, entrepreneurial support programs, and other aspects of the engineering school. Meet USC is designed to answer all of your questions about USC, the application process, and financial aid.
Reservations are required for Meet USC. This program occurs twice, once at 8:30 a.m. and again at 12:30 p.m. Please make sure to check availability and register online for the session you wish to attend. Also, remember to list an Engineering major as your "intended major" on the webform!Location: Ronald Tutor Campus Center (TCC) - USC Admission Office
Audiences: Everyone Is Invited
Contact: Viterbi Admission
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CS Seminar: Dr. Gita Sukthankar (University of Central Florida) - Data-driven Social Informatics
Mon, Nov 30, 2015 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Gita Sukthankar, University of Central Florida
Talk Title: Data-driven Social Informatics
Series: Teamcore Seminar
Abstract: Data-driven social informatics unites models derived from social science with data-driven approaches in order to model and predict population behavior patterns. It can be used to advance our understanding of human behavior, guide public policy decisions, and improve user experience with social media platforms. In this talk, I'll describe work done at UCF's Intelligent Agents Lab (http://ial.eecs.ucf.edu/) in which we use a combination of agent-based modeling, machine learning, and crowdsourcing to model human social systems. The benefits of this approach will be illustrated using three case studies: 1) predicting the influence of social norms on smoking cessation behavior, 2) tracking campus parking usage using crowdsourcing and transportation modeling, 3) learning collaboration patterns from co-authorship networks. We believe that the combination of techniques yields a more nuanced view that relying on data alone.
Biography: Dr. Gita Sukthankar is an Associate Professor and Charles N. Millican Faculty Fellow in the Department of Computer Science at the University of Central Florida, and an affiliate faculty member at UCF's Institute for Simulation and Training. She received her Ph.D. from the Robotics Institute at Carnegie Mellon and an A.B. in psychology from Princeton University. In 2009, Dr. Sukthankar was selected for the Air Force Young Investigator award, the DARPA Computer Science Study Panel, and an NSF CAREER award. Gita Sukthankar's research focuses on multi-agent systems and computational social models. She is the lead editor of the book: Plan, Activity, and Intent Recognition: Theory and Practice and currently serves on DARPA's Information Science and Technology advisory group.
Host: Teamcore Group
Location: 107
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Traffic estimation for extreme congestion events
Mon, Nov 30, 2015 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Daniel Work, University of Illinois at Urbana-Champaign
Talk Title: Traffic estimation for extreme congestion events
Host: Petros Ioannou
More Information: Work Seminar Announcement.pdf
Location: 132
Audiences: Everyone Is Invited
Contact: Shane Goodoff
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Seminars in Biomedical Engineering
Mon, Nov 30, 2015 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Andrew Hires, PhD, Assistant Professor in Neurobiology, University of Southern California
Talk Title: TBA
Biography: Samuel Andrew Hires, first studied Brain and Cognitive Sciences as an undergrad at MIT. In 2007, he received his Ph.D. in Neurosciences in the lab of Roger Tsien at UCSD where he developed genetically encoded indicators of glutamate and synaptic release. This was followed by a brief post-doc with Loren Looger at Janelia Farm where he developed the popular genetically-encoded calcium indicator G-CaMP3 with Lin Tian. He finished his post-doctoral training with Karel Svoboda studying cortical circuits governing tactile sensory processing in the mouse. In 2014, the Hires Lab opened at the University of Southern California. Link to Hires Lab: http://hireslab.org/
Host: Stanley Yamashiro, PhD
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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PhD Defense - Saima Aman
Mon, Nov 30, 2015 @ 02:00 PM - 04:00 PM
Thomas Lord Department of Computer Science, Ming Hsieh Department of Electrical and Computer Engineering
University Calendar
PhD Defense - Saima Aman
Title: Prediction Models for Dynamic Decision Making in Smart Grid
Committee: Viktor Prasanna (chair), Cauligi Raghavendra, Cyrus Shahabi
Abstract:
The widespread use of smart meters and sensors in the Smart Grid is generating large volumes of data, also designated as big data. Predictive modeling can be used to learn from this data about when peak demand periods occur to make dynamic decisions about when, by how much, and how to reduce consumption, by means of demand response (DR). While day-ahead predictions have long been used for DR, we propose dynamic demand response (D2R) that requires performing DR at a few hours- advance notice whenever necessitated by dynamic conditions such as intermittent generation from renewable energy sources. D2R is a prime example of dynamic decision making in smart grids that involves balancing supply and demand in real-time and adapting to dynamically changing conditions by automating and transforming the DR planning process.
We focus on the challenges of prediction modeling and evaluation to enable D2R. First, we address the partial data problem that arises when real-time data from sensors is only partially available at the utilities. Our proposed model learns the dependencies among time series collected from a set of sensors, and uses data from a small subset of -"influential" sensors to make accurate predictions for all sensors. The second problem we address is that of predicting reduced consumption during DR. We leverage big data on reduced consumption to learn a single ensemble model to predict reduced consumption for diverse customers over different time intervals, thus achieving high cost efficiency. Finally, we identify the limitations of existing measures for evaluating the performance of prediction models in smart grid and propose a suite of performance measures that address accuracy, reliability, and cost. We use the USC microgrid data in our experiments, and our proposed models are being used for D2R on the USC campus.
Biography:
Saima Aman is currently a Ph.D. candidate in the Computer Science Department at the University of Southern California. Her research interests are in Data Science and Artificial Intelligence. She has a M.S. in Computer Science from the University of Ottawa, Canada, and a B.Tech. in Computer Engineering from Aligarh Muslim University, India.Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Kathy Kassar
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AIChE's Annual Holiday Networking Night
Mon, Nov 30, 2015 @ 07:00 PM - 08:30 PM
Viterbi School of Engineering Student Organizations
Student Activity
Please join the American Institute of Chemical Engineers USC Chapter for an evening of hors d'oeuvre and meeting students, faculty, staff and industry representatives in Chemical Engineering. Everyone is welcome.
Date: Monday, November 30th
Time: 7:00pm to 8:30pm
Location: Parkside Performance Cafe
Please RSVP below by November 25th:
https://docs.google.com/a/usc.edu/forms/d/1GSX8fy59CY3EBZcf-mSP1c_HR86V555HDe1Nmb0rKfU/viewform?usp=send_form
Facebook Event: https://www.facebook.com/events/768936566563160/More Information: AIChE Annual Holiday Networking Night Flyer.pdf
Location: Parkside Residential Building (PRB) - Parkside Performance Cafe
Audiences: Everyone Is Invited
Contact: USC American Institute of Chemical Engineers
