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Events for February 17, 2017
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Sonny Astani Department Seminar
Fri, Feb 17, 2017 @ 03:00 AM - 03:30 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Ruda Zhang, PhD Student, Sonny Astani Department of Civil and Environmental Engineering
Talk Title: Demand and Supply Distribution of Street Hailing Taxi Service
Abstract: Before the rise of taxi hailing via mobile devices, passengers and taxi drivers have no information about each others' locations. For traditional street hailing taxi services, where are the potential passengers? Where are the free taxis? Does free taxi supply match passenger demand? Using New York City taxi trip records during 2009-2013, we built and tested models to answer these questions.
Host: Roger Ghanem
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Kaela Berry
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AI Seminar - Interview Talk
Fri, Feb 17, 2017 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Jay Pujara, University of California, Santa Cruz
Talk Title: Probabilistic models for large, noisy, and dynamic data
Abstract: We inhabit a vast, uncertain, and dynamic universe. To succeed in such an environment, artificial intelligence approaches must handle massive amounts of noisy, changing evidence. My research addresses the problems of building scalable, probabilistic models amenable to online updates. To illustrate the potential of such models, I present my work on knowledge graph identification, which jointly resolves the entities, attributes, and relationships in a knowledge graph by combining statistical NLP signals and semantic constraints. Using probabilistic soft logic, a statistical relational learning framework I helped develop, I demonstrate how knowledge graph identification can scale to millions of uncertain candidate facts and tens of millions of semantic dependencies in real-world data while achieving state-of-the-art performance. My work further extends this scalability by adopting a distributed computing approach, reducing the inference time of knowledge graph identification from two hours to ten minutes. Updating large, collective models like those used for knowledge graphs with new information poses a significant challenge. I develop a regret bound for probabilistic models and use this bound to motivate practical algorithms that support low-regret updates while improving inference time over 65%. Finally, I highlight several active projects in sustainability, bioinformatics, and mobile analytics that provide a promising foundation for future research.
Biography: Jay Pujara is a postdoctoral researcher at the University of California, Santa Cruz whose principal areas of research are machine learning, artificial intelligence, and data science. He completed his PhD at the University of Maryland, College Park and received his MS and BS at Carnegie Mellon University. Prior to his PhD, Jay spent six years at Yahoo! working on mail spam detection, user trust, and contextual mail experiences, and he has also worked at Google, LinkedIn and Oracle. Jay is the author of over twenty peer-reviewed publications and has received three best paper awards for his work. He is a recognized authority on knowledge graphs, and has organized the Automatic Knowledge Base Construction (AKBC) workshop, recently presented a tutorial on knowledge graph construction, and has had his work featured in AI Magazine. For more information, visit https://www.jaypujara.org
Host: Craig Knoblock
More Info: http://webcastermshd.isi.edu/Mediasite/Play/1ed0700540864caabaedfc675e89543e1d
Location: Information Science Institute (ISI) -
Audiences: Everyone Is Invited
Contact: Kary LAU
Event Link: http://webcastermshd.isi.edu/Mediasite/Play/1ed0700540864caabaedfc675e89543e1d
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W.V.T. Rusch Engineering Honors Program Colloquium
Fri, Feb 17, 2017 @ 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 Dr. William Ballhaus, CEO of The Aerospace Corporation (retired), titled "Space Is Still a One Strike and You're Out Business."
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Ramon Borunda/Academic Services
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Munushian Keynote Lecture - William E. Moerner, Friday, February 17th at 2:00pm in GER124
Fri, Feb 17, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. William E. Moerner - Nobel Prize in Chemistry, Nobel Foundation (2014), Stanford University
Talk Title: The Story of Photonics and Single Molecules, from Early Spectroscopy in Solids, to Super-Resolution Nanoscopy in Cells and Beyond
Abstract: More than 25 years ago, low temperature experiments aimed at establishing the ultimate limits to optical storage in solids led to the first optical detection and spectroscopy of a single molecule in the condensed phase. At this unexplored ultimate limit, many surprises occurred where single molecules showed both spontaneous changes (blinking) and light-driven control of emission, properties that were also observed in 1997 at room temperature with single green fluorescent protein variants. In 2006, PALM and subsequent approaches showed that the optical diffraction limit of ~200 nm can be circumvented to achieve super-resolution fluorescence microscopy, or nanoscopy, with relatively nonperturbative visible light. Essential to this is the combination of single-molecule fluorescence imaging with active control of the emitting concentration and sequential localization of single fluorophores decorating a structure. Super-resolution microscopy has opened up a new frontier in which biological structures and behavior can be observed in live cells with resolutions down to 20-40 nm and below. Examples range from protein superstructures in bacteria to bands in actin filaments to details of the shapes of amyloid fibrils and much more. Current methods development research addresses ways to extract more information from each single molecule such as 3D position and orientation, and to assure not only precision, but also accuracy. Still, it is worth noting that in spite of all the interest in super-resolution, even in the "conventional" single-molecule tracking regime where the motions of individual biomolecules are recorded in solution or in cells rather than the shapes of extended structures, much can still be learned about biological processes when ensemble averaging is removed.
Biography: William Moerner is an American physical chemist and chemical physicist with current work in the biophysics and imaging of single molecules. He is credited with achieving the first optical detection and spectroscopy of a single molecule in condensed phases, along with his postdoc, Lothar Kador. Optical study of single molecules has subsequently become a widely used single-molecule experiment in chemistry, physics and biology. In 2014 he was awarded the Nobel Prize in Chemistry.
He attended Washington University in St. Louis for undergraduate studies as an Alexander S. Langsdorf Engineering Fellow, and obtained three degrees: a B.S. in physics with Final Honors, a B.S. in electrical engineering with Final Honors, and an A.B. in mathematics summa cum laude in 1975. This was followed by graduate study, partially supported by a National Science Foundation Graduate Fellowship, at Cornell University in the group of Albert J. Sievers III. Here he received an M.S. degree and a Ph.D. degree in physics in 1978 and 1982, respectively.
Host: EE-Electrophysics
More Info: minghsiehee.usc.edu/about/lectures/munushian-lecture
Location: Ethel Percy Andrus Gerontology Center (GER) - 124
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: minghsiehee.usc.edu/about/lectures/munushian-lecture
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PhD Defense- Om Prasad Patri
Fri, Feb 17, 2017 @ 02:30 PM - 04:30 PM
Thomas Lord Department of Computer Science
University Calendar
Modeling and Recognition of Events from Temporal Sensor Data for Energy Applications
Ph.D. candidate: Om Prasad Patri
Friday, February 17, 2017
2:30PM, EEB 248
Abstract:
The ubiquitous nature of sensors and smart devices collecting more and more data from industrial and engineering equipment (such as pumps and compressors in oilfields or smart meters in energy grids) has led to new challenges in faster processing of temporal data to identify critical happenings (events) and respond to them. We deal with two primary challenges in processing events from temporal sensor data: (i) how to comprehensively model events and related happenings (event modeling), and (ii) how to automatically recognize event patterns from raw multi-sensor data (event recognition).
The event modeling problem is to build a comprehensive event model enabling complex event analysis across diverse underlying systems, people, entities, actions and happenings. We propose the Process-oriented Event Model for event processing that attempts a comprehensive representation of these processes, particularly those seen in modern energy industries and sensor data processing applications. This model brings together, in a unified framework, the different types of entities that are expected to be present at different stages of an event processing workflow and a formal specification of relationships between them.
Using event models in practice requires detailed domain knowledge about a variety of events based on raw data. We propose to learn this domain knowledge automatically by using recent advances in time series classification and shape mining, which provide methods of identifying discriminative patterns or subsequences (called shapelets). These methods show great potential for real sensor data as they don't make assumptions about the nature, source, structure, distribution, or stationarity of input time series, provide visual intuition, and perform fast event classification. By combining shape extraction and feature selection, we extend this temporal shape mining paradigm for processing data from multiple sensors. We present evaluation results to illustrate the performance of our approaches on real-world sensor data.
Biography:
Om Prasad Patri is a CS PhD candidate at USC advised by Prof. Viktor K. Prasanna. His interests are broadly in the areas of data science, artificial intelligence, cybersecurity and event-based systems. For his dissertation, he has worked on modeling and processing information in event-based systems and pattern mining from multivariate time series sensor data. At USC, he has been a part of the Center for Smart Interactive Oil Field Technologies (CiSoft) and the USC Data Science Lab. He has also worked on internships at NEC Labs America and Cylance Inc. He holds a Bachelors in Computer Science (2011) from the Indian Institute of Technology Guwahati and a Masters in Computer Science (2014) from USC. He is a member of the IEEE, ACM, ISSIP and SPE.
Defense Committee: Viktor K. Prasanna (chair), Iraj Ershaghi, Dennis McLeod
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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Astani Civil and Environmental Engineering Ph.D. Seminar
Fri, Feb 17, 2017 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Ruda Zhang and Pedram Oskoue , Astani Ph.D. Students
Talk Title: Demand and Supply Distribution of Street Hailing Taxi Service/ In-situ Quality Control of Scan Data for As-built Models
More Information: Astani CEE Ph.D. Seminar Abstract 2-17-2017.pdf.docx
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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Sonny Astani Department Seminar
Fri, Feb 17, 2017 @ 03:00 PM - 03:30 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Ruda Zhang, PhD Student, Sonny Astani Department of Civil and Environmental Engineering
Talk Title: Demand and Supply Distribution of Street Hailing Taxi Service
Abstract: Before the rise of taxi hailing via mobile devices, passengers and taxi drivers have no information about each others' locations. For traditional street hailing taxi services, where are the potential passengers? Where are the free taxis? Does free taxi supply match passenger demand? Using New York City taxi trip records during 2009-2013, we built and tested models to answer these questions.
Host: Roger Ghanem
More Information: Sonny Astani Department Seminar.pdf
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Kaela Berry
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ASBME Makeathon Kick Off Event
Fri, Feb 17, 2017 @ 05:55 PM - 07:00 PM
Alfred E. Mann Department of Biomedical Engineering, USC Viterbi School of Engineering
Student Activity
The Associated Students of Biomedical Engineering at the University of Southern California have recognized the need to provide students with real-life, application-based challenges to students interested in the biomedical field. This event provides students interested in biomedical related fields a hands-on opportunity to solve a real-world problem in a collaborative environment. Students are presented with a research-based challenge, and have a limited amount of time and resources to solve the challenge. By working in teams, students engage in an interdisciplinary sharing of knowledge in order to solve a time-sensitive case. During the competition, corporate representatives and graduate students act as mentors, providing feedback to students, and offering advice. Students from other universities are invited to compete to provide exposure to Viterbi-�s innovative and collaborative environment and to foster bonds with students and organizations from other schools.
Location: Ronald Tutor Campus Center (TCC) - 227
Audiences: Everyone Is Invited
Contact: Breanne Grady
