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Events for the 1st week of November

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

    Mon, Oct 29, 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!

    RSVP

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

    Audiences: Everyone Is Invited

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    Contact: Rebecca Kinnon

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  • Seminars in Biomedical Engineering

    Mon, Oct 29, 2018 @ 12:30 PM - 01:50 PM

    Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Joseph Cocozza, PhD, USC, Department of Ophthalmology

    Talk Title: New program in biomedical area

    Host: Qifa Zhou

    Location: Olin Hall of Engineering (OHE) - 122

    Audiences: Everyone Is Invited

    Contact: Mischalgrace Diasanta

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  • PhD Defense - Caitlyn Clabaugh

    Mon, Oct 29, 2018 @ 01:00 PM - 03:00 PM

    Computer Science

    University Calendar


    Title: Human-Robot Learning: Computational Personalization For Socially Assistive Robotics

    Time: 01:00 PM on Monday, October 29th, 2018
    Location: RTH 406

    Ph.D. Candidate: Caitlyn Clabaugh

    Committee:
    Prof. Maja Matarić
    Prof. Gaurav Sukhatme
    Prof. Gisele Ragusa

    Abstract:

    Socially assistive robotics (SAR) seeks to support human care and development through long-term, socially co-present interaction, supplementing the efforts of clinicians and educators. One primary objective in SAR is the personalization or tailoring of interaction to meet the unique and evolving abilities, preferences, and needs of individuals. This dissertation proposes a theoretical framework for human-robot learning (HRL) to enable computational personalization.

    HRL is formalized as a hierarchical decision-making problem, wherein the robot selects actions to maximize an individual's psychosocial state and progress toward some assistive goal. The framework groups SAR actions into abstract categories based on theories from psychology and linguistics. Actions within each category are selected by a local policy or controller. The controllers themselves are activated by a meta-controller, an overarching heuristic or algorithm that controls the flow of the intervention. In this way, the framework hierarchically decomposes the large state-action spaces of SAR into more tractable subspaces for computational personalization.

    The proposed framework was instantiated as an individualized SAR intervention for early childhood math. To validate the framework and its instantiation, a short-term study was conducted with typically developing children in a general preschool classroom. The data collected informed iterative design and computational personalization, culminating in a long-term, in-home SAR intervention for children with autism spectrum disorder (ASD). In this context, individualization was framed as a reinforcement learning problem, adapting the SAR's instruction and feedback to each child over many interactions.

    The fully autonomous SAR system was deployed for month-long interventions in the homes of ten children with ASD. The single-subject study found that the SAR system successfully individualized its instruction and feedback to each child participant over time. Additionally, all participants showed improvement in their mathematics skills and long-term retention of intervention content, demonstrating the quality of the individualization. This research designed, developed, and deployed a novel, fully autonomous, long-term, in-home, individualized SAR intervention for children with diverse needs. As a broader contribution, this dissertation formalizes the problem of HRL and offers a validated, theoretical framework to inform future research at the intersection of artificial intelligence and human-machine interaction.

    Location: 406

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

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  • Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series

    Mon, Oct 29, 2018 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Amir Rahmani, NASA Jet Propulsion Laboratory

    Talk Title: Swarm Autonomy and a New Era of Space Exploration

    Abstract:
    Teams and swarms of autonomous robots and spacecraft hold the promise to change the way some missions are designed and provide new mission opportunities. Monolithic systems can be traded for a swarm of interconnected and coordinating assets. Swarm robotics has reached a level of maturity that can be reliably fielded. NASA's Jet Propulsion Laboratory has long enjoyed leadership in spacecraft formation flying and swarm robotics. This talk will present an overview of JPL's multi-agent autonomy tasks and technologies, including our multi-mission multi-agent autonomy architecture, as well as a number of multi-robot motion-planning tools developed at JPL.


    Biography: Dr. Amir Rahmani has a Ph.D. from University of Washington in aeronautics and astronautics and was an assistant professor of aerospace engineering at the University of Miami prior to joining JPL. He has over a decade research experience in distributed space systems, formation flying, as well as swarm robotics. He is the NASA Small Business Technology Transfer (STTR) subtopic manager for coordination and control of swarm of space vehicles.

    Host: Mihailo Jovanovic, mihailo@usc.edu

    More Info: http://csc.usc.edu/seminars/2018Fall/rahmani.html

    More Information: 18.10.29_Amir_Rahmani_NASA_Seminar.pdf

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

    Audiences: Everyone Is Invited

    Contact: Brienne Moore

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  • The Best of Both Worlds: Social Agents that Leverage Feelings of Rapport and Anonymity

    Mon, Oct 29, 2018 @ 05:00 PM - 06:30 PM

    Viterbi School of Engineering Student Organizations

    Conferences, Lectures, & Seminars


    Speaker: Gale M. Lucas, Research Assistant Professor at USC's ICT

    Talk Title: The Best of Both Worlds: Social Agents that Leverage Feelings of Rapport and Anonymity

    Series: AAAI@USC Lecture Series

    Abstract: This talk presents research comparing social agents to both non-social machines and humans. Social agents have the potential to build rapport like humans (which non-social machines cannot do), but do so while assuring anonymity (which humans cannot do). In this way, they may offer the "best of both worlds" in terms of encouraging users to share personal information and disclose honestly, as well as feel comfortable in situations where they would otherwise be afraid of being negatively evaluated. This has implications for user design and offers possibilities for future research.

    Biography: Gale M. Lucas is a Research Assistant Professor at University of Southern California's Institute for Creative Technologies (ICT). After earning her PhD from Northwestern University, she completed her post-doctoral work at ICT, where she established a research program in the areas of Affective Computing and Human-Computer Interaction. Her line of work in affective and personality computing focuses on models predicting mental health, perceptions of trust and emotion in real-world situations. Her work in HCI is centered around understanding how various social factors affect trust in agents and robots.

    RSVP: https://goo.gl/forms/uLy23v8sHqz9ZRj72

    Host: AAAI at USC

    More Info: https://goo.gl/forms/uLy23v8sHqz9ZRj72

    Location: John Stauffer Science Lecture Hall (SLH) - 200

    Audiences: Everyone Is Invited

    Contact: AAAI at USC

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  • Epstein Institute Seminar - ISE 651

    Tue, Oct 30, 2018 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Gino Lim, Professor and Dept. Chair, University of Houston

    Talk Title: Drone-aided Healthcare Delivery for Patients with Chronic Diseases in Rural Areas and Uncertain Battery Duration

    Host: Professor Julie Higle

    More Information: October 30, 2018.pdf

    Location: Ethel Percy Andrus Gerontology Center (GER) - 206

    Audiences: Everyone Is Invited

    Contact: Grace Owh

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  • CS Distinguished Lecture: Nina Balcan (CMU) - Data Driven Algorithm Design

    Tue, Oct 30, 2018 @ 03:30 PM - 04:50 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Nina Balcan, Carnegie Mellon University

    Talk Title: Data Driven Algorithm Design

    Series: Computer Science Distinguished Lecture Series

    Abstract: Data driven algorithm design for combinatorial problems is an important aspect of modern data science and algorithm design. Rather than using off the shelf algorithms that only have worst case performance guarantees, practitioners typically optimize over large families of parametrized algorithms and tune the parameters of these algorithms using a training set of problem instances from their domain to determine a configuration with high expected performance over future instances. However, most of this work comes with no performance guarantees. The challenge is that for many combinatorial problems, including partitioning and subset selection problems, a small tweak to the parameters can cause a cascade of changes in the algorithm's behavior, so the algorithm's performance is a discontinuous function of its parameters.

    In this talk, I will present new work that helps put data driven combinatorial algorithm selection on firm foundations. We provide strong computational and statistical performance guarantees for several subset selection and combinatorial partitioning problems (including various forms of clustering), both for the batch and online scenarios where a collection of typical problem instances from the given application are presented either all at once or in an online fashion, respectively.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Maria Florina Balcan is an Associate Professor in the School of Computer Science at Carnegie Mellon University. Her main research interests are machine learning, computational aspects in economics and game theory, and algorithms. Her honors include the CMU SCS Distinguished Dissertation Award, an NSF CAREER Award, a Microsoft Faculty Research Fellowship, a Sloan Research Fellowship, and several paper awards. She was a program committee co-chair for the Conference on Learning Theory in 2014 and for the International Conference on Machine Learning in 2016. She is currently board member of the International Machine Learning Society (since 2011), a Tutorial Chair for ICML 2019, and a Workshop Chair for FOCS 2019.


    Host: Computer Science Department

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

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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

    Wed, Oct 31, 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!

    RSVP

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

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Rebecca Kinnon

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  • Resilient Distributed Inference in Cyber-Physical Systems

    Wed, Oct 31, 2018 @ 12:00 PM - 01:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Soummya Kar, Carnegie Mellon University

    Talk Title: Resilient Distributed Inference in Cyber-Physical Systems

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

    Abstract: In applications such as large-scale cyber-physical systems (CPS) and Internet-of-Things (IoT), as the number of devices or agents continues to grow, the integrity and trustworthiness of data generated by these devices becomes a pressing issue of paramount importance. An adversary may hijack individual devices or the communication channel between devices to maliciously alter data streams. In numerous IoT applications, we deploy physical devices throughout an environment, and we are interested in using the stream of sensor measurements to make inferences about the environmental state. Due to the large-scale and distributed nature of devices and data it might be infeasible to carry out computation and decision-making in a classical centralized fashion as well as to prevent attacks and intrusions on all data sources. As a result, reactive countermeasures, such as intrusion detection schemes and resilient inference algorithms become a vital component of security in distributed IoT-type setups.

    As an alternative to traditional fusion-center based cloud setups, in this talk we focus on fog-type architectures in which devices themselves perform the necessary computations using local data and peer-to-peer information exchange with neighboring devices to make inferences about an environment. In the first part of the talk, we review distributed inference approaches and algorithms based on the consensus+innovations paradigm. We discuss performance metrics such as rates of convergence, communication complexity, and optimality. The second part of the talk focuses on recent work on secure and resilient variants of these algorithms in adversarial environments. Specifically, focusing on the case of data integrity attacks on the device network, we characterize fundamental trade-offs between resilience, quantified in terms of achievable inference performance and ability to detect intrusions and threats, and model properties such as observability and connectivity of the inter-device communication network.


    Biography: Soummya Kar received a B.Tech. in electronics and electrical communication engineering from the Indian Institute of Technology, Kharagpur, India, in May 2005 and a Ph.D. in electrical and computer engineering from Carnegie Mellon University, Pittsburgh, PA, in 2010. From June 2010 to May 2011, he was with the Electrical Engineering Department, Princeton University, Princeton, NJ, USA, as a Postdoctoral Research Associate. He is currently an Associate Professor of Electrical and Computer Engineering at Carnegie Mellon University, Pittsburgh, PA, USA. His research interests include decision-making in large-scale networked systems, stochastic systems, multi-agent systems and data science, with applications to cyber-physical systems and smart energy systems. Recent recognition of his work includes the 2016 O. Hugo Schuck Best Paper Award from the American Automatic Control Council and a 2016 Dean's Early Career Fellowship from CIT, Carnegie Mellon.

    Host: Professor Paul Bogdan

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

    Audiences: Everyone Is Invited

    Contact: Talyia White

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  • CS Tech Talk: AI for Content Creation and Interaction

    Wed, Oct 31, 2018 @ 04:00 PM - 06:20 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Dr. Lei Li & Dr. Jianchao Yang, ByteDance AI Lab

    Talk Title: AI for Content Creation and Interaction

    Abstract: In the mobile era, we are being presented an exciting opportunity to shape the way people acquire and consume information. In this talk, we will reveal the roles of AI technologies in the information consumption platforms. We will share several recent work at ByteDance AI Lab towards more efficient creation of and interaction with content. We will introduce a robot writer, Xiaomingbot, which has produced more than 60k articles since August 2016, some of them in multiple languages including English, Chinese and Portuguese. It relies on state-of-the-art representation learning for sentences and generative models from data, text, and images. We will also introduce our latest research in visual understanding of objects and scene in short videos, and how these technologies assist authors to create better content. The talk will be accompanied with interactive demos of these technologies in Tiktok(Douyin), Vigo(Huoshan), and Toutiao apps.

    Biography: Dr. Lei Li is Director of ByteDance AI Lab. Lei received his B.S. in Computer Science and Engineering from Shanghai Jiao Tong University (ACM class) and Ph.D. in Computer Science from Carnegie Mellon University, respectively. His dissertation work on fast algorithms for mining co-evolving time series was awarded ACM KDD best dissertation (runner up). His recent work on AI writing received 2nd-class award of WU Wenjun AI prize of China. Before Toutiao, he worked at Baidu's Institute of Deep Learning in Silicon Valley as a Principal Research Scientist. Before that, he was working in EECS department of UC Berkeley as a Post-Doctoral Researcher. He has served in the Program Committee for ICML 2014, ECML/PKDD 2014/2015, SDM 2013/2014, IJCAI 2011/2013/2016, KDD 2015/2016, 2017 KDD Cup co-Chair, KDD 2018 hands-on tutorial co-chair, and as a lecturer in 2014 summer school on Probabilistic Programming for Advancing Machine Learning. He has published over 40 technical papers and holds 3 US patents.

    Dr. Jianchao Yang is Director of ByteDance AI Lab US. Before joining ByteDance, Jianchao was a manager and principal research scientist at Snap, where he led the computer vision area. He obtained his Ph.D. degree under supervision of Prof. Thomas Huang from University of Illinois at Urbana-Champaign. He has published over 80 technical papers on top conferences and journals, which have attracted over 15k citations from the research community. He is the receipt of Best Student Paper Award in ICCV 2011. He and his collaborators are multiple winners of international competitions and challenges, including PASCAL VOC 2009, ImageNet 2014, WebVision 2017, and NTIRE Super-resolution Challenge 2018.


    Host: Xiang Ren

    Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 116

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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  • NL Seminar-Exposing Brittleness in Reading Comprehension Systems

    Thu, Nov 01, 2018 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Robin Jia, Stanford University

    Talk Title: Exposing Brittleness in Reading Comprehension Systems

    Series: Natural Language Seminar

    Abstract: Reading comprehension systems that answer questions over a context passage can often achieve high test accuracy, but they are frustratingly brittle: they often rely heavily on superficial cues, and therefore struggle on out-of-domain inputs. In this talk, I will describe our work on understanding and challenging these systems. First, I will show how to craft adversarial reading comprehension examples by adding irrelevant distracting text to the context passage. Next, I will present the newest version of the SQuAD dataset, SQuAD 2.0, which tests whether models can distinguish answerable questions from similar but unanswerable ones. Finally, I will share some observations from our recent attempts to use reading comprehension systems as a natural language interface for building other NLP systems.


    Biography: Robin Jia is a fifth-year PhD student advised by Percy Liang at Stanford University. He is an NSF Graduate Fellow, and has received Outstanding Paper and Best Short Paper Awards from EMNLP and ACL, respectively.

    Host: Xusen Yin

    More Info: http://nlg.isi.edu/nl-seminar/

    Location: Information Science Institute (ISI) - 6th Floor Conf Rm-CR# 689

    Audiences: Everyone Is Invited

    Contact: Peter Zamar

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  • CS Distinguished Lecture: Cynthia Dwork (Harvard University) - Skewed or Rescued? The Emerging Theory of Algorithmic Fairness

    Thu, Nov 01, 2018 @ 03:30 PM - 04:50 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Cynthia Dwork, Harvard University

    Talk Title: Skewed or Rescued? The Emerging Theory of Algorithmic Fairness

    Series: Computer Science Distinguished Lecture Series

    Abstract: Data, algorithms, and systems have biases embedded within them reflecting designers' explicit and implicit choices, historical biases, and societal priorities. They form, literally and inexorably, a codification of values. 'Unfairness' of algorithms - for tasks ranging from advertising to recidivism prediction - has attracted considerable attention in the popular press. The talk will discuss recent work in the nascent mathematically rigorous study of fairness in classification and scoring.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Cynthia Dwork, the Gordon McKay Professor of Computer Science at the John A. Paulson School of Engineering and Applied Sciences at Harvard, the Radcliffe Alumnae Professor at the Radcliffe Institute for Advanced Study, and an Affiliated Faculty Member at Harvard Law School, is renowned for placing privacy-preserving data analysis on a mathematically rigorous foundation. With seminal contributions in cryptography, distributed computing, and ensuring statistical validity, her most recent focus is on fairness in classification algorithms. Dwork is a member of the US National Academy of Sciences, the US National Academy of Engineering, and the American Philosophical Society, and is a Fellow of the American Academy of Arts and Sciences and of the ACM.


    Host: Computer Science Department

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

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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  • VITERBI STUDENT SPEAKER SYMPOSIUM

    Thu, Nov 01, 2018 @ 05:00 PM - 07:00 PM

    Viterbi School of Engineering Student Affairs

    Workshops & Infosessions


    The Viterbi Engineering Writing Program presents the Viterbi Student Speaker Symposium! Come listen to undergraduate and graduate students speak about some of the most important issues in engineering today.
    HOPE TO SEE YOU THERE!

    Email mjt@usc.edu with any questions.

    Location: Ronald Tutor Hall of Engineering (RTH) - 211

    Audiences: Everyone Is Invited

    Contact: Helen Choi

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  • Sample Complexity of Partition Identification using Multi-armed Bandits with Applications to Nested Monte Carlo

    Fri, Nov 02, 2018 @ 02:00 AM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Prof. Sandeep Juneja, TIFR, Mumbai, India

    Talk Title: Sample Complexity of Partition Identification using multi-armed Bandits with Applications to Nested Monte Carlo

    Series: Special/Joint CPS/CommNetS Seminar

    Abstract: Given a vector of probability distributions, or arms, each of which can be sampled independently, we consider the problem of identifying the partition to which this vector belongs from a finitely partitioned universe of such vector of distributions. We study this as a pure exploration problem in multi-armed bandit settings and develop sample complexity bounds on the total mean number of samples required for identifying the correct partition with high probability. This framework subsumes well-studied problems in the literature such as finding the best arm or the best few arms. We consider distributions belonging to the single parameter exponential family and primarily consider partitions where the vector of means of arms lie either in a given set or its complement. The sets considered correspond to distributions where there exists a mean above a specified threshold, where the set is a half space and where either the set or its complement is convex. In all these settings, we characterize the lower bounds on mean number of samples for each arm. Further, we propose algorithms that can match these bounds asymptotically with decreasing probability of error. Applications of this framework may be diverse. We briefly discuss a few associated with nested Monte Carlo and its applications to finance.

    Biography: Sandeep is a Professor and Dean at the School of Technology and Computer Science in Tata Institute of Fundamental Research in Mumbai. His research interests lie in applied probability including in mathematical finance, Monte Carlo methods, multi-armed bandit based sequential decision making, and game theoretic analysis of queues. He is currently on the editorial board of Stochastic Systems. Earlier he has been on editorial boards of Mathematics of Operations Research, Management Science and ACM TOMACS.



    Host: Rahul Jain

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

    Audiences: Everyone Is Invited

    Contact: Talyia White

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  • W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM

    Fri, Nov 02, 2018 @ 01:00 PM - 01:50 PM

    USC Viterbi School of Engineering

    Conferences, Lectures, & Seminars


    Speaker: Prof. Aaron D. Ames, California Institute of Technology, Dept. of Mechanical and Civil Engineering

    Talk Title: Towards the Robots of Science Fiction

    Host: EHP and Dr. Prata

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

    Audiences: Everyone Is Invited

    Contact: Amanda McCraven

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  • Astani Civil and Environmental Engineering Seminar

    Fri, Nov 02, 2018 @ 03:00 PM - 04:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Damian Helbling, Ph.D., Cornell University

    Talk Title: Organic chemical contaminants in the aquatic environment: new tools for characterization and remediation of impacted environments

    Abstract: See attached

    Host: Dr. Daniel McCurry

    More Information: Helbling_Announcement.docx

    Location: Ray R. Irani Hall (RRI) - 101

    Audiences: Everyone Is Invited

    Contact: Evangeline Reyes

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  • Repeating EventEssentials of Composites Manufacturing

    Sat, Nov 03, 2018 @ 08:00 AM - 05:00 PM

    Executive Education

    Conferences, Lectures, & Seminars


    Abstract: Essentials of Composites Manufacturing provides a high-level overview of manufacturing science and engineering for aerospace composite structures, focusing on prepreg and liquid molding processes, including hands-on laboratory demonstrations.
    Course participants will complete a multiple-choice quiz as a knowledge assessment, available online at the end of the course. When the course and quiz have been successfully completed, participants will receive USC Continuing Education Units.

    More Info: https://viterbiexeced.usc.edu/engineering-program-areas/chemical-engineering-materials-science/essentials-composites-manufacturing/

    Audiences: Registered Attendees

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    Contact: Corporate & Professional Programs

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