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Events for March 28, 2018

  • Undergraduate Fall Registration Begins

    Wed, Mar 28, 2018

    Viterbi School of Engineering Student Affairs

    University Calendar


    Audiences: Everyone Is Invited

    Contact: Sheryl Koutsis

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  • Meet USC: Admission Presentation, Campus Tour, and Engineering Talk

    Wed, Mar 28, 2018

    Viterbi School of Engineering Undergraduate Admission

    University Calendar


    This half day program is designed for prospective freshmen (HS juniors and younger) 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!

    RSVP

    Location: Ronald Tutor Campus Center (TCC) - USC Admission Office

    Audiences: Prospective Freshmen (HS Juniors and Younger) & Family Members

    Contact: Viterbi Admission

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  • EE Seminar: Statistical Interference of Properties of Distribution: Theory, Algorithms, and Applications

    Wed, Mar 28, 2018 @ 10:30 AM - 11:30 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Jiantao Jiao, Stanford University

    Talk Title: Statistical Interference of Properties of Distribution: Theory, Algorithms, and Applications

    Abstract: Modern data science applications - ranging from graphical model learning to image registration to inference of gene regulatory networks - frequently involve pipelines of exploratory analysis requiring accurate inference of a property of the distribution governing the data rather than the distribution itself. Notable examples of properties include Shannon entropy, mutual information, Kullback-Leibler divergence, and total variation distance, among others.

    This talk will focus on recent progress in the performance, structure, and deployment of near-minimax-optimal estimators for a large variety of properties in high-dimensional and nonparametric settings. We present general methods for constructing information theoretically near-optimal estimators, and identify the corresponding limits in terms of the parameter dimension, the mixing rate (for processes with memory), and smoothness of the underlying density (in the nonparametric setting). We employ our schemes on the Google 1 Billion Word Dataset to estimate the fundamental limit of perplexity in language modeling, and to improve graphical model and classification tree learning. The estimators are efficiently computable and exhibit a "sample size boosting" phenomenon, i.e., they attain with n samples what prior methods would have needed n log(n) samples to achieve.

    Biography: Jiantao Jiao is a Ph.D. student in the Department of Electrical Engineering at Stanford University. He received the B.Eng. degree in Electronic Engineering from Tsinghua University, Beijing, China in 2012, and the M.Eng. degree in Electrical Engineering from Stanford University in 2014. He is a recipient of the Presidential Award of Tsinghua University and the Stanford Graduate Fellowship. He was a semi-plenary speaker at ISIT 2015 and a co-recipient of the ISITA 2016 Student Paper Award. He co-designed and co-taught the graduate course EE378A (Statistical Signal Processing) at Stanford University in 2016 and 2017, with his advisor Tsachy Weissman. His research interests are in statistical machine learning, high-dimensional and nonparametric statistics, information theory, and their applications in medical imaging, genomics, and natural language processing. He is a co-founder of Qingfan (www.qingfan.com), an online platform that democratizes technical training and job opportunities for anyone with access to the internet.

    Host: Salman Avestimehr, avestimehr@gmail.com

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

    Audiences: Everyone Is Invited

    Contact: Mayumi Thrasher

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  • Computer Science General Faculty Meeting

    Wed, Mar 28, 2018 @ 12:00 PM - 02:00 PM

    Thomas Lord Department of Computer Science

    Receptions & Special Events


    Bi-Weekly regular faculty meeting for invited full-time Computer Science faculty only. Event details emailed directly to attendees.

    Location: Ronald Tutor Hall of Engineering (RTH) - 526

    Audiences: Invited Faculty Only

    Contact: Assistant to CS chair

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  • Aerospace and Mechanical Engineering Seminar

    Wed, Mar 28, 2018 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: David Lentink, Assistant Professor, Department of Mechanical Engineering, Stanford University

    Talk Title: Avian Inspired Design

    Abstract: Many organisms fly in order to survive and reproduce. My lab focusses on understanding bird flight to improve flying robots - because birds fly further, longer, and more reliable in complex visual and wind environments. I use this multidisciplinary lens that integrates biomechanics, aerodynamics, and robotics to advance our understanding of the evolution of flight more generally across birds, bats, insects, and autorotating seeds. The development of flying organisms as an individual and their evolution as a species are shaped by the physical interaction between organism and surrounding air. The organism's architecture is tuned for propelling itself and controlling its motion. Flying animals and plants maximize performance by generating and manipulating vortices. These vortices are created close to the body as it is driven by the action of muscles or gravity, then are 'shed' to form a wake (a trackway left behind in the fluid). I study how the organism's architecture is tuned to utilize these and other aeromechanical principles to compare the function of bird wings to that of bat, insect, and maple seed wings. The experimental approaches range from making robotic models to training birds to fly in a custom-designed wind tunnel as well as in visual flight arenas - and inventing methods to 3D scan birds and measure the aerodynamic force they generate - nonintrusively - with a novel aerodynamic force platform. The studies reveal that animals and plants have converged upon the same solution for generating high lift: A strong vortex that runs parallel to the leading edge of the wing, which it sucks upward. Why this vortex remains stably attached to flapping animal and spinning plant wings is elucidated and linked to kinematics and wing morphology. While wing morphology is quite rigid in insects and maple seeds, it is extremely fluid in birds. I will show how such 'wing morphing' significantly expands the performance envelope of birds during flight, and will dissect the mechanisms that enable birds to morph better than any aircraft can. Finally, I will show how these findings have inspired my students to design new flapping and morphing aerial robots.

    Biography: Professor Lentink's multidisciplinary lab studies biological flight, in particular bird flight, as an inspiration for engineering design. http://lentinklab.stanford.edu He has a BS and MS in Aerospace Engineering (Aerodynamics, Delft University of Technology) and a PhD in Experimental Zoology cum laude (Wageningen University). During his PhD he visited the California institute of Technology for 9 months to study insect flight. His postdoctoral training at Harvard was focused on studying birds. Publications range from technical journals to cover publications in Nature and Science. He is an alumnus of the Young Academy of the Royal Netherlands Academy of Arts and Sciences, recipient of the Dutch Academic Year Prize, the NSF CAREER award and he has been recognized in 2013 as one of 40 scientists under 40 by the World Economic Forum.

    Host: Department of Aerospace and Mechanical Engineering

    Location: Seaver Science Library (SSL) - 150

    Audiences: Everyone Is Invited

    Contact: Ashleen Knutsen

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  • CAIS Seminar: Dr. Mayank Kejriwal (USC Information Sciences Institute) - Building Knowledge Graphs for Social Good

    Wed, Mar 28, 2018 @ 04:00 PM - 05:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Dr. Mayank Kejriwal, USC Information Sciences Institute

    Talk Title: Building Knowledge Graphs for Social Good

    Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series

    Abstract: Illicit activities like human trafficking and narcotics have a significant Web footprint. In this talk, I will introduce and talk about building knowledge graphs (KG), a powerful means of representing and reasoning over knowledge using intelligent algorithms, to combat such problems for social good. I will also introduce a KG-centric system called DIG, developed in our group, that is currently being used by more than 100 US law enforcement agencies to combat human trafficking.

    This lecture satisfies requirements for CSCI 591: Research Colloquium


    Biography: Dr. Mayank Kejriwal is a researcher at the USC Information Sciences Institute. His research on knowledge graphs, currently funded under both DARPA and IARPA, has been published in multiple interdisciplinary ACM, IEEE, Springer and Elsevier venues. He is authoring a textbook on knowledge graphs (MIT Press) with Pedro Szekely and Craig Knoblock.


    Host: Milind Tambe

    Location: Mark Taper Hall Of Humanities (THH) - 102

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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