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Events for November 28, 2018

  • Repeating EventMeet USC: Admission Presentation, Campus Tour, and Engineering Talk

    Wed, Nov 28, 2018

    Viterbi School of Engineering Undergraduate Admission

    University Calendar

    This half day program is designed for prospective freshmen (HS seniors 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!


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

    Audiences: Everyone Is Invited

    View All Dates

    Posted By: Rebecca Kinnon

  • Computer Science General Faculty Meeting

    Wed, Nov 28, 2018 @ 12:00 AM - 02:00 PM

    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

    Posted By: Assistant to CS chair

  • Decentralized Signal Processing and Distributed Control for Collaborative Autonomous Sensor Networks

    Wed, Nov 28, 2018 @ 12:00 PM - 01:00 PM

    Ming Hsieh Department of Electrical Engineering

    Conferences, Lectures, & Seminars

    Speaker: Ryan Alan Goldhahn & Priyadip Ray, Lawrence Livermore National Laboratory

    Talk Title: Decentralized Signal Processing and Distributed Control for Collaborative Autonomous Sensor Networks

    Series: Center for Cyber-Physical Systems and Internet of Things

    Abstract: Collaborative autonomous sensor networks have recently been used in many applications including inspection, law enforcement, search and rescue, and national security. They offer scalable, low-cost solutions which are robust to the loss of multiple sensors in hostile or dangerous environments. While often comprised of less capable sensors, the performance of a large network can approach the performance of far more capable and expensive platforms if nodes are effectively coordinating their sensing actions and data processing. This talk will summarize work to date at LLNL on distributed signal processing and decentralized optimization algorithms for collaborative autonomous sensor networks, focusing on ADMM-based solutions for detection/estimation problems and sequential and/or greedy optimization solutions which maximize submodular functions such as mutual information.

    Biography: Ryan Goldhahn holds a Ph.D. in electrical engineering from Duke University with a focus in statistical and model-based signal processing. Ryan joined the NATO Centre for Maritime Research and Experimentation (CMRE) as a researcher in 2010 and later as the project lead for an effort to use multiple unmanned underwater vehicles (UUVs) to detect and track submarines using multi-static active sonar. In this work he developed collaborative autonomous behaviors to optimally reposition UUVs to improve tracking performance without human intervention. He led several experiments at sea with submarines from multiple NATO nations. At LLNL Ryan has continued to work and lead projects in collaborative autonomy and model-based and statistical signal processing in various applications. He has specifically focused on decentralized detection/estimation/tracking and optimization algorithms for autonomous sensor networks.

    Priyadip Ray received a Ph.D. degree in electrical engineering from Syracuse University in 2009. His Ph.D. dissertation received the Syracuse University All-University Doctoral Prize. Prior to joining LLNL, Dr. Ray was an assistant professor at the Indian Institute of Technology (IIT), Kharagpur, India where he supervised a research group of approximately 10 scholars in the areas of statistical signal processing, wireless communications, optimization, machine learning and Bayesian non-parametrics. Prior to this he was a research scientist with the Department of Electrical and Computer Engineering at Duke University. Dr. Ray has published close to 40 research articles in various highly-rated journals and conference proceedings and is also a reviewer for leading journals in the areas of statistical signal processing, wireless communications and data science. At LLNL, Dr. Ray has been the PI/Co-I on multiple LDRDs as well as a DARPA funded research effort in the areas of machine learning for healthcare and collaborative autonomy.

    Host: Paul Bogdan

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Posted By: Talyia White

  • AME Seminar

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

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars

    Speaker: Heather Culbertson, USC

    Talk Title: Can You Feel It? Haptics for Realism and Virtual Communication

    Abstract: The haptic (touch) sensations felt when interacting with the physical world create a rich and varied impression of objects and their environment. Humans can a gather significant amount of information through touch with their environment, allowing them to assess object properties and qualities, dexterously handle objects, and communicate social cues and emotions. However, humans are spending significantly more time in the virtual world and are increasingly interacting with people and objects through a digital medium. Unfortunately, digital interactions remain unsatisfying and limited, representing the human as having only two sensory inputs: visual and auditory.

    This talk will focus on the investigation of haptic devices and rendering algorithms to provide humans with touch feedback when communicating through a computer. I will present a background on the sense of touch and illustrate how we can leverage this knowledge to design haptic devices and rendering systems that allow the human to virtually communicate in a natural and intuitive way. I will then discuss our work in creating realistic haptics in virtual reality through both data-driven modeling and novel haptic hardware.

    Biography: Heather Culbertson is a WiSE Gabilan Assistant Professor of Computer Science and Aerospace and Mechanical Engineering at the University of Southern California where she directs the Haptics Robotics and Virtual Interaction (HaRVI) Lab. Previously, she was a research scientist in the Department of Mechanical Engineering at Stanford University. She received her PhD in the Department of Mechanical Engineering and Applied Mechanics (MEAM) at the University of Pennsylvania in 2015, a MS degree in MEAM at the University of Pennsylvania in 2013 and earned a BS degree in mechanical engineering at the University of Nevada, Reno in 2010. She is currently serving as the Vice-Chair for Information Dissemination for the IEEE Technical Committee on Haptics. Her awards include a citation for meritorious service as a reviewer for the IEEE Transactions on Haptics, Best Paper at UIST 2017, and the Best Hands-On Demonstration Award at IEEE World Haptics 2013.

    Host: Julian Domaradzki

    More Info: https://ame.usc.edu/seminars/

    Location: Seaver Science Library (SSL) - 150

    Audiences: Everyone Is Invited

    Posted By: Tessa Yao

  • CS Distinguished Lecture: Rodney Allen Brooks (MIT, iRobot, Rethink) - Steps Towards Super Intelligence

    Wed, Nov 28, 2018 @ 05:00 PM - 06:20 PM

    Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Rodney Allen Brooks, MIT, iRobot, Rethink

    Talk Title: Steps Towards Super Intelligence

    Series: CS Distinguished Lectures

    Abstract: In his 1950 paper "Computing Machinery and Intelligence" Alan Turing estimated that sixty people working for fifty years should be able to program a computer (running at 1950 speed) to have human level intelligence. AI researchers have spent orders of magnitude more effort than that and are still not close. Why has AI been so hard and what are the problems that we might work on in order to make real progress to human level intelligence, or even the super intelligence that many pundits believe is just around the corner? This talk will discuss those steps we can take, what aspects we really still do not have much of a clue about, what we might be currently getting completely wrong, and why it all could be centuries away. Importantly the talk will make distinctions between research questions and barriers to technology adoption from research results, with a little speculation on things that might go wrong (spoiler alert: it is the mundane that will have the big consequences, not the Hollywood scenarios that the press and some academics love to talk about).

    This lecture satisfies requirements for CSCI 591: Research Colloquium.

    Biography: Rodney Brooks earned Bachelors and Masters degrees in pure mathematics from Flinders University in South Australia. In 1977 he joined the Artificial Intelligence Lab at Stanford graduating with a PhD in computer science in 1981. After post-docs at Carnegie Mellow and MIT, and a faculty position back at Stanford he joined the MIT faculty at the Artificial Intelligence Laboratory there in 1984. He worked in computer vision, robotics, and artificial life. He became director of the AI Lab in 1997 and in 2003 he founded the Computer Science and Artificial Intelligence Lab, CSAIL, which is the largest lab at MIT with over 1,000 members. Along the way he started a software company in silicon valley, a boutique robotics venture capital fund, the company iRobot which has delivered tens of millions of home cleaning robots and many thousand ground robots to the US military, and more recently spent 10 years developing collaborative robots for manufacturing at Rethink Robotics. He retired from MIT In 2010, and currently advises companies large and small, including Toyota and their autonomous driving efforts. He is a member of the NAE and a Fellow of the American Academy of Arts and Sciences, and of the IEEE, ACM, AAAS, and AAAI. He writes at rodneybrooks.com/blog.

    Host: Maja Mataric

    Location: Henry Salvatori Computer Science Center (SAL) - 101

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair