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Events for November
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USC Viterbi STEM Spotlight on the Department of Computer Science
Tue, Nov 03, 2015 @ 08:30 AM - 02:30 PM
USC Viterbi School of Engineering, Viterbi School of Engineering K-12 STEM Center
University Calendar
The USC Viterbi STEM Spotlight on the Department of Computer Science is organized by VAST: Viterbi Adopt-a-Student, Adopt-a-Teacher. During this day of lab tours, K-12 students from around Southern California will experience cutting-edge research in the field of computer science.
Location: Epstein Family Engineering Plaza VHE Breezeway
Audiences: K-12 Schools pre-registered
Contact: Katie Mills
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W.V.T. Rusch Engineering Honors Program Colloquium
Fri, Nov 06, 2015 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
University Calendar
Join us for a presentation by Mark Pestana, Senior Research Pilot at Flight Research Associates, Inc., titled "Flying Unmanned Aircraft: A Pilot's Perspective."
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: Ramon Borunda/Academic Services
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W.V.T. Rusch Engineering Honors Program Colloquium
Fri, Nov 13, 2015 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
University Calendar
Join us for a presentation by Eric J. Roulo, President of Roulo Consulting, Inc., titled "Preparing Yourself to Become a Highly Compensated Technical Consultant."
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: Ramon Borunda/Academic Services
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PhD Defense - Chen Sun
Mon, Nov 16, 2015 @ 02:30 PM - 04:00 PM
Thomas Lord Department of Computer Science
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PhD Defense- Chen Sun
Title: Event Detection and Recounting from Large-scale Web Videos
Committee: Ramakant Nevatia, Yan Liu, B. Keith Jenkins (external member)
Abstract:
Whether captured by smart phones, surveillance cameras or self-driving cars, videos stand out as as one of the most important and informative media in the digital world. Videos bring temporal information to the visual recognition domain, and open doors to applications such as motion analysis, tracking and event detection.
The primary goal of my research is to detect high-level events (e.g. birthday party, town hall meeting) from unconstrained web videosï¼ and to generate video recounts containing key event evidence. The ever-increasing popularity of video capturing devices and sharing websites has created a huge gap between the fast pace of video generation and our ability to index them. In response, I aim to build a semantic representation of videos with objects, actions, events and their interactions.
My PhD work mainly focuses on the following three aspects towards this goal: (1) utilize temporal information effectively; (2) extract rich semantics with moderate video annotations; (3) build connection between videos and language. In this talk, I will introduce my recent work on weakly-supervised action recognition, and automatic visual concept discovery for image description and retrieval. I will also provide a brief overview of the history and state-of-the-art methods for action and event recognition.
Location: Charles Lee Powell Hall (PHE) - 223
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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W.V.T. Rusch Engineering Honors Program Colloquium
Fri, Nov 20, 2015 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
University Calendar
Join us for a presentation by Prof. Armand R. Tanguay, Jr., from the University of Southern California, titled "An Intraocular Camera for Retinal Prostheses: Restoring Sight to the Blind."
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: Ramon Borunda/Academic Services
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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
