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Events for the 2nd week of March

  • MESA College and Career Day

    Sat, Mar 07, 2020 @ 09:00 AM - 01:00 PM

    Viterbi School of Engineering K-12 STEM Center

    Receptions & Special Events


    Enrolled students in the USC MESA program at partner middle and high schools will work on exciting team-based projects. These projects culminate in the annual MESA Day competitions hosted at the local, regional, and state levels.

    MESA students will:

    -Apply mathematics, science, and engineering principles to academic contests, and over time, develop their mastery of these academic skills.

    -Build self-esteem and confidence through preparation, participation, and access to relevant real-world STEM challenges.

    -Be part of the maker and creator movement that encourages problem-solving in a framework fostering creativity, critical thinking, collaboration, and communication skills.

    Audiences: Middle and high school students

    Posted By: Darin Gray/Viterbi K-12 STEM Center

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  • Viterbi's Day of Service

    Sat, Mar 07, 2020 @ 09:00 AM - 02:00 PM

    Viterbi School of Engineering Alumni

    Student Activity


    We would like to invite all of our Viterbi family to join us at Viterbi Day of Service on Saturday, March 7, 2020. Last Fall, we had 63 volunteers which consisted of students, faculty, and staff. By joining Viterbi Day of Service, you will be able to volunteer for a service project arranged by USCs Friends and Neighbors Day. We hope you will join to help make a difference in our local communities.

    For more information on project descriptions, please visit: https://campusactivities.usc.edu/volunteer/register/.

    To sign-up for a project, register here: https://usccampusactivities.wufoo.com/forms/qb8f9s6141lovj/.
    After registering, volunteers receive a confirmation email 2-5 days before, with details about their placement, check-in time, and location. Times vary for different projects, so please read your confirmation email.

    Viterbi Day of Service is sponsored by the Undergraduate Programs and Women in Engineering Office and the Viterbi Impact Program (VIP). VIP participants play a vital role in the community as they work as partners with local schools and organizations. VIP volunteers are undergraduate engineering students committed to a semester or more of volunteering.

    We hope you will join us in making this Day of Service a long-standing tradition at Viterbi.

    If you have any questions please contact Myra Fernandez, Associate Director of Undergraduate Programs and Women in Engineering, Viterbi Admission and Student Engagement at, myrafern@usc.edu.

    Location: Ronald Tutor Campus Center (TCC) -

    Audiences: Everyone Is Invited

    Posted By: Kristy Ly

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  • SHINE DAY

    Sat, Mar 07, 2020 @ 12:00 PM - 02:00 PM

    Viterbi School of Engineering K-12 STEM Center

    Workshops & Infosessions


    SHINE DAY is open to program alumni and people interested in learning more about the USC Viterbi Summer High School Intensive in Next-Generation Engineering (SHINE) program, hosted by the Viterbi K-12 STEM Center. SHINE is designed for high-achieving, college-bound high school students. Selected students participate in research labs alongside world-renowned USC faculty and Ph.D. students.


    Schedule:

    2019 SHINE Poster Session, 12:00-1:00 pm: 2019 SHINE alumni present research from their time in the 2019 SHINE program. Open to the public.

    2020 Intro Session, 1:00-2:00 pm: SHINE applicants and prospective families gather for some refreshments and an introduction to SHINE.

    Before the event, USC Viterbi K-12 STEM Center is hosting a private SHINE alumni reunion brunch from 10:30-11:45 am (for SHINE alumni and families only). Alumni, please RSVP if you can attend.


    To learn more about SHINE, visit: https://viterbik12.usc.edu/shine/

    To RSVP, please fill out the SHINE DAY RSVP form.

    For questions about SHINE or SHINE DAY, email k12stem1@usc.edu

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

    Audiences: Everyone Is Invited

    Posted By: Dr. Katie Mills

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  • CS Colloquium: Lili Su (MIT) - Learning with Distributed Systems: Adversary-Resilience and Neural Networks

    Mon, Mar 09, 2020 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Lili Su, MIT

    Talk Title: Learning with Distributed Systems: Adversary-Resilience and Neural Networks

    Series: CS Colloquium

    Abstract: In this talk, I will first talk about how to secure Federated Learning (FL) against adversarial faults.
    FL is a new distributed learning paradigm proposed by Google. The goal of FL is to enable the cloud (i.e., the learner) to train a model without collecting the training data from users' mobile devices. Compared with traditional learning, FL suffers serious security issues and several practical constraints call for new security strategies. Towards quantitative and systematic insights into the impacts of those security issues, we formulated and studied the problem of Byzantine-resilient Federated Learning. We proposed two robust learning rules that secure gradient descent against Byzantine faults. The estimation error achieved under our more recently proposed rule is order-optimal in the minimax sense.

    Then, I will briefly talk about our recent results on neural networks, including both biological and artificial neural networks. Notably, our results on the artificial neural networks (i.e., training over-parameterized 2-layer neural networks) improved the state-of-the-art. In particular, we showed that nearly-linear network over-parameterization is sufficient for the global convergence of gradient descent.

    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Biography: Lili Su is a postdoc in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, hosted by Professor Nancy Lynch. She received a Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign in 2017, supervised by Professor Nitin H. Vaidya. Her research intersects distributed systems, learning, security, and brain computing. She was the runner-up for the Best Student Paper Award at DISC 2016, and she received the 2015 Best Student Paper Award at SSS 2015. She received UIUC's Sundaram Seshu International Student Fellowship for 2016, and was invited to participate in Rising Stars in EECS (2018). She has served on TPC for several conferences including ICDCS and ICDCN.

    Host: Leana Golubchik

    Location: Ronald Tutor Hall of Engineering (RTH) - 109

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • PhD Defense - Johnathan Mell

    Mon, Mar 09, 2020 @ 11:00 AM - 01:00 PM

    Computer Science

    University Calendar


    PhD Candidate: Johnathan Mell
    Date: Monday, March 9th, 2020
    Time: 11:00 AM - 1:00 PM
    Location: SAL 213
    Committee: Dr. Jonathan Gratch (Chair), Dr. Nate Fast, Dr. Sven Koenig

    Title: A Framework for Research in Human-Agent Negotiation


    Abstract:

    Increasingly, automated agents are interacting with humans in highly social interactions. Many of these interactions can be characterized as negotiation tasks. There has been broad research in negotiation techniques between humans (in business literatures, e.g.), as well a great deal of work in creating optimal agents that negotiate with each other. However, the creation of effective socially-aware agents requires fundamental basic research on human-agent negotiation. Furthermore, this line of enquiry requires highly customizable, fully-interactive systems that are capable of enabling and implementing human-agent interaction. Previous attempts that rely on hypothetical situations or one-shot studies are insufficient in capturing truly social behavior.

    This dissertation showcases my invention and development of the Interactive Arbitration Guide Online (IAGO) platform, which enables rigorous human-agent research. IAGO has been designed from the ground up to embody core principles gleaned from the rich body of research on how people actually negotiate. I demonstrate several examples of how IAGO has already yielded fundamental contributions towards our understanding of human-agent negotiation. I also demonstrate how IAGO has contributed to a community of practice by allowing researchers across the world to easily develop and investigate novel algorithms. Finally, I discuss future plans to use this framework to explore how humans and machines can establish enduring and profitable relationships through repeated negotiations.

    Location: Henry Salvatori Computer Science Center (SAL) - 213

    Audiences: Everyone Is Invited

    Posted By: Lizsl De Leon

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  • Spring 2020 Joint CSC@USC/CommNetS-MHI Seminar Series

    Mon, Mar 09, 2020 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Bruno Ribeiro, Purdue University

    Talk Title: Unearthing the relationship between graph neural networks and matrix factorization

    Abstract: Graph tasks are ubiquitous, with applications ranging from recommendation systems, to language understanding, to automation with environmental awareness and molecular synthesis. A fundamental challenge in applying machine learning to these tasks has been encoding (representing) the graph structure in a way that ML models can easily exploit the relational information in the graph, including node and edge features. Until recently, this encoding has been performed by factor models (a.k.a. matrix factorization embeddings), which arguably originated in 1904 with Spearman's common factors. Recently, however, graph neural networks have introduced a new powerful way to encode graphs for machine learning models. In my talk, I will describe these two approaches and then introduce a unifying mathematical framework using group theory and causality that connects them. Using this novel framework, I will introduce new practical guidelines to generating and using node embeddings and graph representations, which fixes significant shortcomings of the standard operating procedures used today.

    Biography: Bruno Ribeiro is an Assistant Professor in the Department of Computer Science at Purdue University. He obtained his Ph.D. at the University of Massachusetts Amherst and did his postdoctoral studies at Carnegie Mellon University from 2013-2015. His research interests are in representation learning and data mining, with a focus on sampling and modeling relational and temporal data. He received an NSF CAREER award in 2020 and the ACM SIGMETRICS best paper award in 2016.

    Host: Prof. Antonio Ortega, aortega@usc.edu

    More Info: http://csc.usc.edu/seminars/2020Spring/ribeiro.html

    More Information: 200309_Bruno Ribeiro_CSC Seminar.pdf

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

    Audiences: Everyone Is Invited

    Posted By: Brienne Moore

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  • Intro to Computer Vison with OpenCV AAAI x USC Makers

    Mon, Mar 09, 2020 @ 06:30 PM - 07:30 PM

    Viterbi School of Engineering Student Organizations

    Workshops & Infosessions


    AAAI Workshop in Collaboration with USC Makers:
    Intro to Computer Vision with OpenCV

    Computer vision is one of the hottest areas of AI research in 2020, in large part due to its massive potential to solve problems in industry. From self-driving cars and automated grocery stores to radiology and agriculture, computer vision is shaking up every corner of the industrial world. Plus, computer vision projects are super fun!

    In this workshop, you will learn the ropes of OpenCV in Python, a powerful computer vision library originally developed by Intel that is now free and open-source. OpenCV has the benefit of pre-trained machine learning models for both still images and video, allowing you to power your next project with powerful and optimized computer vision AI.

    RSVP HERE

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

    Audiences: Everyone Is Invited

    Posted By: USC AAAI

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  • ECE Seminar: Software-Hardware Systems for the Internet of Things

    Tue, Mar 10, 2020 @ 10:45 AM - 11:45 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Professor Omid Abari, School of Computer Science, University of Waterloo

    Talk Title: Software-Hardware Systems for the Internet of Things

    Abstract: Recently, there has been a huge interest in Internet of Things (IoT) systems, which bring the digital world into the physical world around us. However, barriers still remain to realizing the dream applications of IoT. One of the biggest challenges in building IoT systems is the huge diversity of their demands and constraints (size, energy, latency, throughput, etc.). For example, virtual reality and gaming applications require multiple gigabits-per-second throughput and millisecond latency. Tiny sensors spread around a greenhouse or smart home must be low-cost and batteryless to be sustainable in the long run. Today's networking technologies fall short in supporting these IoT applications with a hugely diverse set of constraints and demands. As such, they require distinct innovative solutions. In this talk, I will describe how we can design a new class of networking technologies for IoT by designing software and hardware jointly, with an understanding of the intended application. In particular, I will present two examples of our solutions. The first solution tackles the throughput limitations of existing IoT networks by developing new millimeter wave devices and protocols, enabling many new IoT applications, such as untethered high-quality virtual reality. The second solution tackles the energy limitations of IoT networks by introducing new wireless devices that can sense and communicate without requiring any batteries. I demonstrate how our solution is applicable in multiple, diverse domains such as HCI, medical, and agriculture. I will conclude the talk with future directions in IoT research, both in terms of technologies and applications.

    Biography: Omid Abari is an Assistant Professor at the University of Waterloo, School of Computer Science. He received his Ph.D. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT) in 2018. His research interests are in the area of computer networks and mobile systems, with applications to the Internet of Things (IoT). He is currently leading the Intelligent Connectivity (ICON) Lab, where his team focuses on the design and implementation of novel software-hardware systems that deliver ubiquitous sensing, communication and computing at scale. His work has been selected for GetMobile research highlights (2018, 2019), and been featured by several media outlets, including Wired, TechCrunch, Engadget, IEEE Spectrum, and ACM Tech News.


    Host: Professor Konstantinos Psounis

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

    Audiences: Everyone Is Invited

    Posted By: Mayumi Thrasher

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  • CS Colloquium: Antoine Bosselut (University of Washington) - Neuro-symbolic Representations for Commonsense Knowledge and Reasoning

    Tue, Mar 10, 2020 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Antoine Bosselut, University of Washington

    Talk Title: Neuro-symbolic Representations for Commonsense Knowledge and Reasoning

    Series: CS Distinguished Lectures

    Abstract: Situations described using natural language are richer than what humans explicitly communicate. For example, the sentence "She pumped her fist" connotes many potential auspicious causes. For machines to understand natural language, they must be able to reason about the commonsense inferences that underlie explicitly stated information. In this talk, I will present work on combining traditional symbolic knowledge and reasoning techniques with modern neural representations to endow machines with these capacities.

    First, I will describe COMET, an approach for learning commonsense knowledge about unlimited situations and concepts using transfer learning from language to knowledge. Second, I will demonstrate how these neural knowledge representations can dynamically construct symbolic graphs of contextual commonsense knowledge, and how these graphs can be used for interpretable, generalized reasoning. Finally, I will discuss current and future research directions on conceptualizing NLP as commonsense simulation, and the impact of this framing on challenging open-ended tasks such as story generation.

    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Biography: Antoine Bosselut is a PhD Student at the University of Washington advised by Professor Yejin Choi, and a student researcher at the Allen Institute for Artificial Intelligence. His research focuses on building systems for commonsense knowledge representation and reasoning that combine the strengths of modern neural and traditional symbolic methods. He was also a student researcher on the Deep Learning team at Microsoft Research from 2017 to 2018. He is supported by an AI2 Key Scientific Challenges award.

    Host: Xiang Ren

    Location: Olin Hall of Engineering (OHE) - 132

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • Microwave Inverse Imaging Meets Deep Learning

    Tue, Mar 10, 2020 @ 11:00 AM - 12:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Uday Khankhoje, Electrical Engineering at the Indian Institute of Technology Madras

    Talk Title: Microwave Inverse Imaging Meets Deep Learning

    Abstract: In this talk, I will start by motivating the area of inverse microwave imaging -- an area that brings together electromagnetics, signal processing, and data analytics. The objective here is to infer the electrical properties of an object by studying how it scatters electromagnetic fields -- all without making contact, i.e. remotely. The applications are diverse, from breast cancer imaging to microwave remote sensing. At the heart of this problem lies a challenging ill-posed nonlinear optimization problem. I will describe some of the contemporary methods of solving this problem and highlight the challenges faced. Subsequently, I will present some of our recent methods and results, where we have significantly pushed the state of the art by incorporating deep neural networks into existing physics-based algorithms.

    Biography: Uday Khankhoje is an Assistant Professor of Electrical Engineering at the Indian Institute of Technology Madras, Chennai, India, since 2016. He received a B.Tech. degree from the Indian Institute of Technology Bombay, Mumbai, India, in 2005, an M.S. and PhD. degrees from the California Institute of Technology (Caltech), Pasadena, USA, in 2010, all in Electrical Engineering. He was a Caltech Postdoctoral Scholar at the Jet Propulsion Laboratory (NASA/Caltech) from 2011-2012, a Postdoctoral Research Associate in the Department of Electrical Engineering at the University of Southern California, Los Angeles, USA, from 2012-2013, and an Assistant Professor of Electrical Engineering at the Indian Institute of Technology Delhi from 2013-2016. His research interests are in the area of computational electromagnetics and its applications to remote sensing and inverse imaging.



    Host: Prof. Constantine Sideris, csideris@usc.edu

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

    Audiences: Everyone Is Invited

    Posted By: Talyia White

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  • ISE 651 - Epstein Seminar

    Tue, Mar 10, 2020 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Satish Kumar Thittamaranahalli (T. K. Satish Kumar) , USC ISI

    Talk Title: Compiling Weighted Constraint Satisfaction Problems to Minimum Weighted Vertex Cover Problems

    Host: Prof. Maged Dessouky

    More Information: March 10, 2020.pdf

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

    Audiences: Everyone Is Invited

    Posted By: Grace Owh

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  • ECE Seminar: Compiler and Runtime Systems for Homomorphic Encryption and Graph Analytics

    Wed, Mar 11, 2020 @ 10:45 AM - 11:45 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Roshan Dathathri, PhD candidate, Dept of CS, University of Texas at Austin

    Talk Title: Compiler and Runtime Systems for Homomorphic Encryption and Graph Analytics

    Abstract: Distributed and heterogeneous architectures are tedious to program because devices such as CPUs, GPUs, FPGAs, and TPUs provide different programming abstractions and may have disjoint memories, even if they are on the same machine. In this talk, I present compiler and runtime systems that make it easier to develop efficient programs for privacy-preserving computation and graph analytics applications on such architectures.

    Fully Homomorphic Encryption (FHE) refers to a set of encryption schemes that allow computations on encrypted data without requiring a secret key. Recent cryptographic advances have pushed FHE into the realm of practical applications. However, programming these applications remains a huge challenge, as it requires cryptographic domain expertise to ensure correctness, security, and performance. I present CHET, a domain-specific optimizing compiler, that is designed to make the task of programming neural network inference applications using FHE easier. CHET automates many laborious and error prone programming tasks including encryption parameter selection to guarantee security and accuracy of the computation, determining efficient data layouts, and performing scheme-specific optimizations. Our evaluation of CHET on a collection of popular neural networks shows that CHET-generated programs outperform expert-tuned ones by an order of magnitude.

    Applications in several areas like machine learning, bioinformatics, and security need to process and analyze very large graphs. Distributed clusters are essential in processing such graphs in reasonable time. I present a novel approach to building distributed graph analytics systems that exploits heterogeneity in processor types, partitioning policies, and programming models. The key to this approach is Gluon, a domain-specific communication-optimizing substrate. Programmers write applications in a shared-memory programming system of their choice and interface these applications with Gluon using a lightweight API. Gluon enables these programs to run on heterogeneous clusters and optimizes communication in a novel way by exploiting structural and temporal invariants of graph partitioning policies. Systems built using Gluon outperform previous state-of-the-art systems and scale well up to 256 CPUs and 64 GPUs.

    Biography: Roshan is a Ph.D. candidate advised by Prof. Keshav Pingali in the University of Texas at Austin. He works on domain-specific programming languages, compilers, and runtime systems that make it easy to develop efficient sparse computation and privacy-preserving computation on large-scale distributed clusters, while utilizing heterogeneous architectures. He has built programming systems for distributed and heterogeneous graph analytics and privacy-preserving neural network inferencing. He received his masters from Indian Institute of Science advised by Prof. Uday Bondhugula, where he worked on automatic parallelization of affine loop nests for distributed and heterogeneous architectures.

    Host: Professor Massoud Pedram

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

    Audiences: Everyone Is Invited

    Posted By: Mayumi Thrasher

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  • CS Colloquium: Jesse Thomason (University of Washington) - Language Grounding with Robots

    Wed, Mar 11, 2020 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Jesse Thomason, University of Washington

    Talk Title: Language Grounding with Robots

    Series: CS Colloquium

    Abstract: We use language to refer to objects like "toast", "plate", and "table" and to communicate requests such as "Could you make breakfast?" In this talk, I will present work on computational methods to tie language to physical, grounded meaning. Robots are an ideal platform for such work because they can perceive and interact with the world. I will discuss dialog and learning strategies I have developed to enable robots to learn from their human partners, similar to how people learn from one another through interaction. I will present methods enabling robots to understand language referring expressions like "the heavy, metallic mug", the first work showing that it is possible to learn to connect words to their perceptual properties in the visual, tactile, and auditory senses of a physical robot. I will also present benchmarks and models for translating high-level human language like "put the toast on the table" that imply latent, intermediate goals into executable sequences of agent actions with the help of low-level, step-by-step language instructions. Finally, I will discuss how my work in grounded language contributes to NLP, robotics, and the broader goals of the AI community.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.

    Biography: Jesse Thomason is a postdoctoral researcher at the University of Washington working with Luke Zettlemoyer. He received his PhD from the University of Texas at Austin with Raymond Mooney. His research focuses on language grounding and natural language processing applications for robotics (RoboNLP). Key to this work is using dialog with humans to facilitate both robot task execution and learning to enable lifelong improvement of robots' language understanding capabilities. He has worked to encourage and promote work in RoboNLP through workshop organization at both NLP and robotics conference venues.

    Host: Stefanos Nikolaidis

    Location: Ronald Tutor Hall of Engineering (RTH) - 109

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • Computer Science General Faculty Meeting

    Wed, Mar 11, 2020 @ 12:00 PM - 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

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  • AME Laufer Lecture - CANCELLED

    Wed, Mar 11, 2020 @ 12:00 PM - 02:00 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Howard A. Stone, Princeton

    Abstract: This event has been cancelled.

    Host: AME Department

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

    Audiences: Everyone Is Invited

    Posted By: Tessa Yao

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  • POSTPONED- Internship/Job Search Open Forum

    Wed, Mar 11, 2020 @ 01:00 PM - 02:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Will be rescheduled virtually at a later date.

    For more information about Labs & Open Forums, please visit viterbicareers.usc.edu/workshops.

    Location: Ronald Tutor Hall of Engineering (RTH) -

    Audiences: All Viterbi

    Posted By: RTH 218 Viterbi Career Connections

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  • *CANCELLED* CAIS Seminar: Rediet Abebe (Harvard University) - Mechanism Design for Social Good

    Wed, Mar 11, 2020 @ 04:15 PM - 05:15 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Rediet Abebe, Harvard University

    Talk Title: Mechanism Design for Social Good

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

    Abstract: Algorithmic and artificial intelligence techniques show immense potential to deepen our understanding of socioeconomic inequality and inform interventions designed to improve access to opportunity. Interventions aimed at historically under-served communities are made particularly challenging by the fact that disadvantage and inequality are multifaceted, notoriously difficult to measure, and reinforced by feedback loops in underlying structures.

    In this talk, we develop algorithmic and computational techniques to address these issues through two types of interventions: one in the form of allocating scarce societal resources and another in the form of improving access to information. We examine the ways in which techniques from algorithms, discrete optimization, and network and computational science can combat different forms of disadvantage, including susceptibility to income shocks, social segregation, and disparities in access to health information. We discuss current practice and policy informed by this work and close with a discussion of an emerging research area -- Mechanism Design for Social Good (MD4SG) -- around the use of algorithms, optimization, and mechanism design to address this category of problems.


    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Rediet Abebe is a Junior Fellow at the Harvard Society of Fellows and will be receiving her Ph.D. in computer science from Cornell University in 2019. Her research is broadly in the fields of algorithms and AI, with a focus on equity and social good concerns. As part of this research agenda, she co-founded Mechanism Design for Social Good (MD4SG), a multi-institutional, interdisciplinary research initiative working to improve access to opportunity for historically disadvantaged communities. This initiative has active participants from over 100 institutions in 20 countries and has been supported by Schmidt Futures, the MacArthur Foundation, and the Institute for New Economic Thinking.

    Abebe currently serves on the NIH Advisory Committee to the Director Working Group on AI, tasked with developing a comprehensive report to the NIH leadership. She was recently named one of 35 Innovators Under 35 by the MIT Technology Review and honored in the 2019 Bloomberg 50 list as a "one to watch." Her work has been covered by outlets including Forbes, the Boston Globe, and the Washington Post. In addition to her research, she also co-founded Black in AI, a non-profit organization tackling diversity and inclusion issues in AI. Her research is deeply influenced by her upbringing in her hometown of Addis Ababa, Ethiopia.


    Host: USC Center for Artificial Intelligence in Society (CAIS)

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

    Audiences: Everyone Is Invited

    Posted By: Computer Science Department

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  • POSTPONED- Behavioral Interview Workshop with Veeva Systems

    Wed, Mar 11, 2020 @ 06:30 PM - 08:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Learn more about what employers look for and how to best brand yourself so you stand out from the competition during the interview process! We will focus on one's personal brand, networking and how to ensure you are remembered when you leave the meeting or interview.

    Veeva Systems is a leader in cloud-based software for the global life sciences industry. Veeva is dedicated to building careers of new university graduates. Generation Veeva is a program focused on your professional development, providing mentors, workshops, and career path planning.

    Opportunities available for students majoring in: Computer Science, Computer Engineering, and any software development related major. Open to all Bachelors, Masters and PhD students.

    To learn more about our Generation Veeva Program, visit our website at: https://www.veeva.com/generationveeva/

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

    Audiences: Everyone Is Invited

    Posted By: RTH 218 Viterbi Career Connections

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  • *CANCELLED* CAIS Seminar: Meredith Gore - Wildlife Trafficking in the Anthropocene: Conservation, Crime & Communities

    Thu, Mar 12, 2020 @ 09:45 AM - 10:45 AM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Meredith Gore, PhD

    Talk Title: Wildlife Trafficking in the Anthropocene: Conservation, Crime & Communities

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

    Abstract: Levels of unsustainable and illegal natural resource exploitation have escalated in scope, scale, and severity. Illegal over-harvest of plant and animal species occurs around the world and poses risks to species, ecosystems, and people. Beyond the risk of species loss, overexploitation represents stolen natural resources, is associated with corruption and insecurity, human rights abuses, and regional destabilization in some of the world's most vulnerable developing nations. This presentation will discuss conservation criminology-”an interdisciplinary and applied science for understanding risks to global natural resources.


    Biography: Dr. Meredith Gore is a conservation social scientist leveraging concepts of risk to enhance understanding of human-environment relationships. Her scholarship is designed to build evidence for action. The majority of her scientific inquiry can be described as convergence research on conservation issues such as wildlife trafficking, illegal logging, fishing and mining. She received her PhD in Natural Resource Policy and Management from Cornell University, MA in Environment and Resource Policy from George Washington University, and BA in Anthropology and Environmental Studies from Brandeis University. She's a MSU Global Research Academy Fellow, National Academies of Sciences Jefferson Science Fellow, US Department of State Embassy Science Fellow and Emerging Wildlife Conservation Leader.


    Host: USC Center for Artificial Intelligence in Society (CAIS)

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

    Audiences: Everyone Is Invited

    Posted By: Computer Science Department

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  • CS Colloquium: Ludwig Schmidt (UC Berkeley) - Do ImageNet Classifiers Generalize to ImageNet?

    Thu, Mar 12, 2020 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Ludwig Schmidt, UC Berkeley

    Talk Title: Do ImageNet Classifiers Generalize to ImageNet?

    Series: CS Colloquium

    Abstract: Progress on the ImageNet dataset seeded much of the excitement around the machine learning revolution of the past decade. In this talk, we analyze this progress in order to understand the obstacles blocking the path towards safe, dependable, and secure machine learning.

    First, we will investigate the nature and extent of overfitting on ML benchmarks through reproducibility experiments for ImageNet and other key datasets. Our results show that overfitting through test set re-use is surprisingly absent, but distribution shift poses a major open problem for reliable ML.

    In the second part, we will focus on a particular robustness issue, known as adversarial examples, and develop methods inspired by optimization and generalization theory to address this issue. We conclude with a large experimental study of current robustness interventions that summarizes the main challenges going forward.

    This lecture satisfies requirements for CSCI 591: Research Colloquium


    Biography: Ludwig Schmidt is a postdoctoral researcher at UC Berkeley working with Moritz Hardt and Ben Recht. Ludwig's research interests revolve around the empirical and theoretical foundations of machine learning, often with a focus on making machine learning more reliable. Before Berkeley, Ludwig completed his PhD at MIT under the supervision of Piotr Indyk. Ludwig received a Google PhD fellowship, a Microsoft Simons fellowship, a best paper award at the International Conference on Machine Learning (ICML), and the Sprowls dissertation award from MIT.

    Host: Haipeng Luo

    Location: Olin Hall of Engineering (OHE) - 132

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • Astani Civil and Environmental Engineering Seminar

    Thu, Mar 12, 2020 @ 03:00 PM - 04:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Larry Rossen, Professor Emeritus of Psychology Department, California State University, Dominguez Hill

    Talk Title: WE ARE FACING AN ATTENTION CRISIS: WHAT IS DRIVING OUR DISTRACTED MINDS?

    Abstract: See attached abstract.


    Host: Dr. Burcin Becerik-Gerber

    More Information: Larry Rossen-Abstract_3-12-2020.pdf

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

    Audiences: Everyone Is Invited

    Posted By: Evangeline Reyes

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  • POSTPONED- Internship/Job Search Open Forum

    Thu, Mar 12, 2020 @ 04:00 PM - 05:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Will be rescheduled virtually at a later date.

    For more information about Labs & Open Forums, please visit viterbicareers.usc.edu/workshops.

    Location: Ronald Tutor Hall of Engineering (RTH) -

    Audiences: All Viterbi

    Posted By: RTH 218 Viterbi Career Connections

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  • **LOCATION CHANGE**CS Colloquium: Ioannis Panageas (SUTD) - Depth-width trade-offs for ReLU networks via Sharkovsky's theorem

    Thu, Mar 12, 2020 @ 04:00 PM - 05:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Ioannis Panageas, Singapore University of Technology and Design

    Talk Title: Depth-width trade-offs for ReLU networks via Sharkovsky's theorem

    Series: CS Colloquium

    Abstract: Understanding the representational power of Deep Neural Networks (DNNs) and how their structural properties (e.g., depth, width, type of activation unit) affect the functions they can compute, has been an important yet challenging question in deep learning and approximation theory. In a seminal paper, Telgarsky highlighted the benefits of depth by presenting a family of functions (based on simple triangular waves) for which DNNs achieve zero classification error, whereas shallow networks with fewer than exponentially many nodes incur constant error. Even though Telgarsky's work reveals the limitations of shallow neural networks, it does not inform us on why these functions are difficult to represent and in fact he states it as a tantalizing open question to characterize those functions that cannot be well-approximated by smaller depths. In this talk, we will point to a new connection between DNNs expressivity and Sharkovsky's Theorem from dynamical systems, that enables us to characterize the depth-width trade-offs of ReLU networks for representing functions based on the presence of generalized notion of fixed points, called periodic points (a fixed point is a point of period 1). Motivated by our observation that the triangle waves used in Telgarsky's work contain points of period 3 - a period that is special in that it implies chaotic behavior based on the celebrated result by Li-Yorke - we will give general lower bounds for the width needed to represent periodic functions as a function of the depth. Technically, the crux of our approach is based on an eigenvalue analysis of the dynamical system associated with such functions.

    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Biography: Ioannis Panageas is an Assistant Professor at Information Systems Department of SUTD since September 2018. Prior to that he was a MIT postdoctoral fellow working with Constantinos Daskalakis. He received his PhD in Algorithms, Combinatorics and Optimization from Georgia Institute of Technology in 2016, a Diploma in EECS from National Technical University of Athens (summa cum laude) and a M.Sc. in Mathematics from Georgia Institute of Technology. His work lies on the intersection of optimization, probability, learning theory, dynamical systems and algorithms. He is the recipient of the 2019 NRF fellowship for AI (analogue of NSF CAREER award).

    URL Website: https://panageas.github.io/

    Host: Shaddin Dughmi

    Location: Ronald Tutor Hall of Engineering (RTH) - 115

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • Port of Los Angeles - Conflict, Commerce, and the Flight for Control - Book Launch and Lecture

    Thu, Mar 12, 2020 @ 06:30 PM - 07:30 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Geraldine Knatz, PhD, Professor of the Practice of Policy and Engineering at USC

    Talk Title: Port of Los Angeles - Conflict, Commerce, and the Flight for Control - Book Launch and Lecture

    Abstract: With years of research, 200 maps and images, Knatz shapes and insightful story of the Port of Los Angeles, from its early entrepreneurs to the city's business and political leadership, and the inevitable conflicts that arose between them. Power moves disguised as bureaucratic banalities, jurisdictional feuds, and outright warfare - it is all here.

    Host: .

    More Information: Knatz Book Launch and Lecture.jpg

    Location: Ralph And Goldy Lewis Hall (RGL) - 101

    Audiences: Everyone Is Invited

    Posted By: Salina Palacios

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  • Grammar Tutoring

    Fri, Mar 13, 2020 @ 10:00 AM - 12:00 PM

    Viterbi School of Engineering Student Affairs

    Workshops & Infosessions


    Undergraduate and graduate Viterbi students are welcome to sign up for grammar help with an Engineering Writing Program professor! Bring your writing and we'll work together to identify areas for improvement!

    Sign up here: http://bit.ly/grammaratUSC

    Please note that Friday, March 13 tutorials will be held via ZOOM. More details are on the sign up sheet above.

    Location: ZOOM

    Audiences: Graduate and Undergraduate Students

    Posted By: Helen Choi

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  • Repeating EventGrammar Tutoring

    Fri, Mar 13, 2020 @ 10:00 AM - 12:00 PM

    Viterbi School of Engineering Student Affairs

    Workshops & Infosessions


    INDIVIDUAL GRAMMAR TUTORIALS
    Need help refining your grammar skills in your academic and professional writing? Meet one-on-one with professors from the Engineering Writing Program, work together on your grammar skills, and take your writing to the next level!

    ALL VITERBI UNDERGRADUATE AND GRADUATE STUDENTS WELCOME!
    Sign up here: http://bit.ly/grammaratUSC

    All sessions will be via Zoom.

    Questions? Contact helenhch@usc.edu

    Location: ZOOM

    Audiences: Graduate and Undergraduate Students

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    Posted By: Helen Choi

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