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Events for March 31, 2021

  • Real Talk: Careers & Internships Financial, Industrial & Systems Engineering and lnformatics Session #1

    Wed, Mar 31, 2021 @ 11:00 AM - 11:30 AM

    Viterbi School of Engineering Career Connections

    University Calendar


    Viterbi Career Connections is Real Talk with VCC to get feedback from Viterbi Students. This is a chance to meet with a Viterbi Career Ambassador to have open dialogue on your well-being and how it's impacting your career goals!. Tell them what is working for you and if there are any barriers to getting the support and resources you need to achieve your career goals. These sessions will be hosted by your peers to provide open and anonymous feedback.

    The session will last 30 minutes and VCC staff can be available after the session to answer any questions or concerns you may have to help you in your career journey.

    To Register: Viterbi Career Gateway > Events > Workshops

    Audiences: Everyone Is Invited

    Contact: RTH 218 Viterbi Career Connections

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  • Real Talk: Careers & Internships Financial, Industrial & Systems Engineering and lnformatics Session #2

    Wed, Mar 31, 2021 @ 11:00 AM - 12:00 PM

    Viterbi School of Engineering Career Connections

    University Calendar


    Viterbi Career Connections is Real Talk with VCC to get feedback from Viterbi Students. This is a chance to meet with a Viterbi Career Ambassador to have open dialogue on your well-being and how it's impacting your career goals!. Tell them what is working for you and if there are any barriers to getting the support and resources you need to achieve your career goals. These sessions will be hosted by your peers to provide open and anonymous feedback.

    The session will last 30 minutes and VCC staff can be available after the session to answer any questions or concerns you may have to help you in your career journey.

    To Register: Viterbi Career Gateway > Events > Workshops

    Audiences: Everyone Is Invited

    Contact: RTH 218 Viterbi Career Connections

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  • Computer Science General Faculty Meeting

    Wed, Mar 31, 2021 @ 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: TBD

    Audiences: Invited Faculty Only

    Contact: Assistant to CS chair

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  • Repeating EventUndergraduate Advisement Drop-in Hours

    Wed, Mar 31, 2021 @ 01:30 PM - 02:30 PM

    Thomas Lord Department of Computer Science

    Workshops & Infosessions


    Do you have a quick question? The CS advisement team will be available for drop-in live chat advisement for declared undergraduate students in our four majors during the spring semester on Tuesdays, Wednesdays, and Thursdays from 1:30pm to 2:30pm Pacific Time. Access the live chat on our website at: https://www.cs.usc.edu/chat/

    Location: Online

    Audiences: Undergrad

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    Contact: USC Computer Science

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  • Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar

    Wed, Mar 31, 2021 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Necmiye Ozay, Electrical Engineering and Computer Science, University of Michigan

    Talk Title: Safety for Autonomous Systems with Information Abundance or Scarcity

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

    Abstract: Modern autonomous systems, like self-driving cars, unmanned aerial vehicles, or robots, are equipped with advanced sensing, learning, and perception modules. On one hand these modules render the overall system more informed, possibly providing predictions into the future. On the other hand, they can be unreliable, as in the case of vision-based perception algorithms unexpectedly failing to detect the obstacles. In this talk, I will discuss some of our recent work on problems that deal with synthesizing controllers to ensure safety and invariance in the presence of information imperfections or predictions. I will show problem instances in these different information regimes when control synthesis can be achieved in a scalable way. I will also discuss how these ideas can be extended to develop algorithms for corner case generation for testing and falsification purposes.

    Biography: Necmiye Ozay received the B.S. degree from Bogazici University, Istanbul in 2004, the M.S. degree from the Pennsylvania State University, University Park in 2006 and the Ph.D. degree from Northeastern University, Boston in 2010, all in electrical engineering. She was a postdoctoral scholar at the California Institute of Technology, Pasadena between 2010 and 2013. She joined the University of Michigan, Ann Arbor in 2013, where she is currently an associate professor of Electrical Engineering and Computer Science. Dr. Ozay's research interests include hybrid dynamical systems, control, optimization and formal methods with applications in cyber-physical systems, system identification, verification & validation, autonomy and dynamic data analysis. Her papers received several awards including a Nonlinear analysis: Hybrid Systems Prize Paper Award for years 2014-2016. She has received the 1938E Award and a Henry Russel Award from the University of Michigan for her contributions to teaching and research, and five young investigator awards, including NSF CAREER.

    Host: pierluigi Nuzzo, nuzzo@usc.edu

    Webcast: https://usc.zoom.us/webinar/register/WN_Qk4-7AthThudso7LXs2OiA

    Location: Online

    WebCast Link: https://usc.zoom.us/webinar/register/WN_Qk4-7AthThudso7LXs2OiA

    Audiences: Everyone Is Invited

    Contact: Talyia White

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  • Virtual Chat with Prof. Ellis Meng from Department of Biomedical Engineering

    Wed, Mar 31, 2021 @ 02:30 PM - 03:30 PM

    Viterbi School of Engineering Masters Programs

    Student Activity


    Sure, they're distinguished and renowned experts in their fields, but Viterbi faculty were once students too. Learn valuable life lessons as they share their professional and personal stories! Together, VGSA and the VASE office presents the Virtual Chat with a Professor Series! These are meant to be informal conversations that you might have with a professor after class or in the hallways. Each session is open to all Viterbi graduate students. Join in to chat with Prof. Ellis Meng!

    Audiences: Everyone Is Invited

    Contact: Juli Legat

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  • Thesis Proposal - Chi Zhang

    Wed, Mar 31, 2021 @ 03:00 PM - 04:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    Title:
    Safe Reinforcement Learning via Offline Learning


    Committee:

    Viktor Prasanna
    Bistra Dilknia
    Pau Bodgan
    Ashutosh Nayyar
    Jyo Deshmukh
    Kannan

    Abstract:

    Reinforcement Learning (RL) is a general learning paradigm to solve sequential decision making problems. They are often modeled as Markov Decision Process (MDP) or Partially Observable Markov Decision Process (POMDP). Reinforcement learning aims at learning policies that maximize the expected accumulated rewards with unknown dynamics or transition probabilities. Deep reinforcement learning (DRL) refers to using deep neural networks as a general function approximator when applying RL algorithms.
    Despite recent success of RL algorithms in robotics, games (e.g. AlphaGo), RL algorithms pose particular challenges when applied to real world settings.
    First, it often requires sufficient exploration effort to achieve a reasonable performance; such exploration is either too expensive (e.g. it takes time to gather data in real world) or forbidden due to safety constraints.
    This limits the RL algorithms in the scenarios where an accurate simulator is available.
    In this proposal, we focus on developing reinforcement learning algorithms that can ensure safety during the training phase and the deployment phase. We argue that by leveraging offline learning from a static dataset collected by existing safe policies, safety can be guaranteed.
    However, standard off-policy RL algorithms are prone to overestimations of the values of out-of-distribution (OOD) actions. This may cause the learned policies to visit unexplored and unsafe states at deployment phase. To mitigate this issue, we first mathematically show that by constraining the learned policies within the support set of the offline datasets, the state di stribution of the learned policy also lies within the support set of the offline datasets; hence safety is guaranteed.
    To constrain the learned policies within the support set, we propose i) distribution matching, and ii) model-based OOD actions generalization detection.
    We improve the existing state-of-the-art behavior regularization based approaches and propose BRAC+: Improved Behavior Regularized Actor Critic. We propose two key improvements including an analytical upper bound for the KL divergence as the behavior regularizor to reduce variance associated with sample based estimations, and gradient penalized Q update to avoid out-of-distribution (OOD) actions due to the unbounded gradient of the Q value w.r.t the OOD actions. Distribution matching is too conservative when the dataset is diverse so that the outcomes of the OOD actions can be correctly predicted. We propose to learn the inverse dynamics model as a variational auto-encoder along with the forward dynamics model. We detect OOD actions generalization by the agreement of the both models. Our approach will be evaluated on several benchmarks as well as a simulated building HVAC control testbed. We will gauge the success of our work by i) Whether the safety criteria is met. ii) The performance improvement over existing safe policies used to collect the dataset.


    Zoom Link:

    https://usc.zoom.us/j/2488070010

    WebCast Link: https://usc.zoom.us/j/2488070010​

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

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  • AME Seminar

    Wed, Mar 31, 2021 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Joanna Austin, Caltech

    Talk Title: Hypervelocity Spherically-Blunted Cone Flows in Mars Entry Ground Testing

    Abstract: The intent to launch larger vehicles in future Mars missions increases the requirements for ground testing in the high-stagnation enthalpy environment encountered by the vehicle during the hypersonic phase of entry, descent and landing. During atmospheric entry, strong shock compression and high post-shock temperatures lead to significant chemical dissociation and vibrational excitation in the shock layer in front of a sphere-cone capsule, particularly near the stagnation region. For Mars missions, accurate thermochemical modeling of carbon dioxide, a principal component of the atmosphere with complex vibrational energy exchange, is particularly important. We examine the shock layer over sphere and spherically-blunted cone geometries through reacting Navier-Stokes simulations and experiments in two facilities capable of high-stagnation enthalpy, hypersonic flows simulating Mars planetary entry conditions: the T5 Reflected Shock Tunnel and the Hypervelocity Expansion Tube. A recently-developed unified model for sphere and sphere-cone behavior is first verified for high-stagnation enthalpy CO2 flows through simulations with thermal and chemical nonequilibrium. Shock standoff distance measurements in both facilities are in good agreement with model predictions. The need to account for the divergence of the streamlines in conical nozzles is highlighted and an existing model is extended to account for changes in shock curvature between parallel and conical flow. The contributions of vibrational and chemical nonequilibrium to the stagnation line density profile are quantified using the simulation results comparing three chemical kinetic models. Experimental measurement of fore- and aftbody MWIR radiation will also be discussed.

    Biography: Joanna Austin is Professor of Aerospace at the Graduate Aerospace Laboratories, California Institute of Technology. She received B.E. (Mechanical and Space Engineering) and B.Sc. (Mathematics) degrees from the University of Queensland, Australia, and M.S. followed by Ph.D. (2003) degrees in Aeronautics from the California Institute of Technology. Austin then joined the faculty in the Aerospace Engineering department at the University of Illinois, becoming Associate Professor and Willett Faculty Scholar, before moving back to Caltech in 2014, where she is a co-PI in the Caltech Hypersonics Group. Austin's research is focused on fundamental problems in reactive, compressible flows across a broad range of applications including hypervelocity flight, supersonic combustion and detonation, bubble dynamics, and explosive geological events.

    Host: AME Department

    More Info: https://usc.zoom.us/j/99638511716

    Webcast: https://usc.zoom.us/j/99638511716

    WebCast Link: https://usc.zoom.us/j/99638511716

    Audiences: Everyone Is Invited

    Contact: Tessa Yao

    Event Link: https://usc.zoom.us/j/99638511716

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  • Repeating EventCP2K: Running Ab Initio Molecular Dynamics Simulations

    Wed, Mar 31, 2021 @ 04:00 PM - 06:00 PM

    Information Technology Program (ITP)

    Workshops & Infosessions


    Presented by: USC Center for Advanced Research Computing

    An introduction to computational tools implemented within the CP2K program package. The most standard methods as well as some of the more advanced features will be introduced by overviews of background theory and through examples of application, while encouraging modular, flexible, and problem-oriented thinking. Recurring topics in the workshop are the scaling of algorithms, the combination of different levels of theory and of sampling, and tools and strategies for the analysis of results. This ongoing workshop is currently running on Wednesdays during the Spring 2021 semester.

    Location: Zoom

    WebCast Link: https://usc.zoom.us/meeting/register/tJYude2rrTgpE9x5UfcFT-A43bnb0bge6mXQ?_x_zm_rtaid=xZh9bx0ZQj2HvOQk_K22MQ.1617059562291.996419a413f45cbe5cd4cba5bd6ed61c&_x_zm_rhtaid=83

    Audiences: Everyone Is Invited

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    Contact: Center for Advanced Research Computing

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