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Events for December 05, 2014
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Meet USC: Admission Presentation, Campus Tour, & Engineering TalkFri, Dec 05, 2014
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. 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 visit http://www.usc.edu/admission/undergraduate/firstyear/prospective/meetusc_sw.html to check availability and make an appointment. Be sure 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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Graduate Engineering Open House 2014
Fri, Dec 05, 2014 @ 10:00 AM - 02:00 PM
Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
Graduate Engineering Open House 2014 is a Viterbi School event for students interested in pursuing their Master's degree at one of the top ranked graduate engineering institutions in the nation. We request that attendees have earned or are candidates to earn at least a Bachelor's degree in engineering, math, or hard science (such as physics, chemistry or biology).
Breakfast and lunch will be provided and there is no charge to attend the event. However, registration is required.
More information and register to attendLocation: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Students with a background in engineering, math or science are welcome to attend.
Contact: Laura Hartman
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AI SEMINAR - Towards a computational framework for how we represent other people
Fri, Dec 05, 2014 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Damian Stanley, Caltech
Talk Title: Towards a computational framework for how we represent other people
Abstract: Predicting other peoplesâ beliefs, desires, and intentions is a primary function of human cognition and is essential to thrive in our complex social world. To do this efficiently and successfully, we must form lasting representations of individuals and social groups based on information we receive through personal and vicarious experience. My research is focused on developing a computational account of the neurocognitive mechanisms through which we learn about other people, make social predictions, and are influenced by social biases. To achieve this, I employ a multidisciplinary approach, integrating a wide range of techniques from cognitive neuroscience, social psychology, neuroeconomics, computational modeling of learning and decision-making, and clinical psychology. My theoretical model of social learning and decision-making treats social group biases as a set of initial guesses (akin to Bayesian priors) that inform our social decision-making when we lack specific information about a person with whom we are interacting. Using these priors as a starting point, we form and update our mental representation of a person (as well as their social group) on the basis of observed behavior. I will present behavioral and neural data on the influence of race bias on trust estimations, as well as the computational processes through which we learn about individualsâ traits and intentions (i.e., theory of mind), and how these processes might be disrupted in individuals with social impairments (e.g. Autism Spectrum Disorder). These results suggest that while many common processes support learning about social and non-social entities, there may also exist neural computations unique to social learning.
Biography: Damian Stanley completed his Ph.D. in Neural Science at New York University in 2005, studying mid-level visual processing. In his postdoctoral work, he turned his focus toward developing a computational account of the neurocognitive processesthrough which we learn about and represent other people. In his first postdoctoral position with Elizabeth Phelps at New York University he investigated how implicit race biases influence social trust. In his current postdoctoral position, with Drs. Ralph Adolphs and John OâDoherty at Caltech, he uses computational models and model-based fMRI to characterize typical and atypical (e.g. autism spectrum disorder) social learning. This line of research is funded by an NIMH career development award (K01-MH099343).
Host: Greg Ver Steeg
Webcast: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=8d563808c16942bda353a815b33370d01dLocation: Information Science Institute (ISI) - 11th floor conference room
WebCast Link: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=8d563808c16942bda353a815b33370d01d
Audiences: Everyone Is Invited
Contact: Kary LAU
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Motion Correction and Pharmacokinetic Analysis in Dynamic Positron Emission Tomography
Fri, Dec 05, 2014 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Hassan Mohy-ud-Din, Departments of ECE, AMS, and Radiology Johns Hopkins University, MD
Talk Title: Motion Correction and Pharmacokinetic Analysis in Dynamic Positron Emission Tomography
Abstract: My talk will focus on two important aspects of Positron Emission Tomography (PET):
(i) Motion-compensation , and (ii) Pharmacokinetic analysis of dynamic PET images.
Motion-compensation in Dynamic PET Images: Dynamic PET images are degraded by inter-frame and intra-frame motion artifacts that can affect the quantitative and qualitative analysis of acquired PET data. I will present a Generalized Inter-frame and Intra-frame Motion Correction (GIIMC) algorithm that unifies in one framework the inter-frame motion correction capability of Multiple Acquisition Frames and the intra-frame motion correction feature of (MLEM)-type deconvolution methods. GIIMC employs a fairly simple but new approach of using time-weighted average of attenuation sinograms to reconstruct dynamic frames. Extensive validation studies show that GIIMC algorithm outperforms conventional techniques producing images with superior quality and quantitative accuracy.
Parametric Myocardial Perfusion PET Imaging using Physiological Clustering: We propose a novel framework of robust kinetic parameter estimation applied to absolute flow quantification in dynamic PET imaging. Kinetic parameter estimation is formulated as nonlinear least squares with spatial constraints problem where the spatial constraints are computed from a physiologically driven clustering of dynamic images, and used to reduce noise contamination. The proposed framework is shown to improve the quantitative accuracy of Myocardial Perfusion (MP) PET imaging, and in turn, has the long-term potential to enhance capabilities of MP PET in the detection, staging and management of coronary artery disease.
Biography: Hassan Mohy-ud-Din is a final year PhD student in the Department of Electrical and Computer Engineering, Johns Hopkins University, USA. He is also pursuing an MA (thesis) in Applied Mathematics and Statistics. He completed his BS in Electronics Engineering from GIK Institute of Engineering and Technology in Pakistan. His research lies at the intersection of Applied Mathematics and Medical Imaging. His work on dynamic cardiac PET imaging won the 2014 Bradley-Alavi fellowship from SNMMI and 2014 SIAM Student Travel (Hong Kong). He has presented his work at various conferences and universities and carries a teaching experience of over 9 years.
Host: Professor Richard Leahy
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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NL Seminar- Multisensory integration in a neural framework for concepts
Fri, Dec 05, 2014 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Kingson Man , USC/BCI
Talk Title: Multisensory integration in a neural framework for concepts
Series: Natural Language Seminar
Abstract: How are concepts represented in the brain? When we hear the ringing of a bell, or watch a bell swinging back and forth, is there a shared "BELL" pattern of neural activity in our brains? Philosophers have debated the nature of concepts for centuries, but recent technical advances have allowed neuroscientists to make contributions to this topic. The combination of functional neuroimaging and machine learning has allowed us to examine distributed patterns of activity in the human brain to decode what they represent about the world, and to what level of abstraction. I describe our recent findings that revealed a hierarchical organization of multisensory information integration, leading to representations that generalize across different sensory modalities. I will also discuss our work on the social function of concepts, which enables the communication of similar thoughts and associations between individuals.
Biography: I am a research associate at the Brain and Creativity Institute of the University of Southern California. I earned my Ph.D. at USC, mentored by Antonio Damasio. I am interested in the general problem of consciousness, and in particular how different sensations are bound together by the brain into a unified experience of the world.
Host: Aliya Deri and Kevin Knight
More Info: http://nlg.isi.edu/nl-seminar/
Webcast: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=56056025433c402fa77a297e7b2e24381dLocation: Information Science Institute (ISI) - 6th Flr Conf Rm # 689, Marina Del Rey
WebCast Link: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=56056025433c402fa77a297e7b2e24381d
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
