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Events for the 2nd week of March

  • CAIS Seminar: Patrick Fowler - Equity in Data-Driven Policies

    Mon, Mar 07, 2022 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Patrick Fowler,

    Talk Title: Equity in Data-Driven Policies

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

    Abstract: Dr. Fowler will present work investigating group fairness in algorithmic decision-making. The team uses administrative records on homeless service delivery to demonstrate inherent tradeoffs in fairness that depend on the operationalization of equity. The findings inform data-driven policy-making in homelessness and social services broadly.

    Register in advance for this webinar at:

    https://usc.zoom.us/webinar/register/WN_b3XxZm-rRfibw54-40F-UA

    After registering, attendees will receive a confirmation email containing information about joining the webinar.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Dr. Patrick Fowler's research centers on homelessness prevention and the negative consequences of homelessness on youth, families, and communities. His recent research focuses on homelessness among youth aging out of foster care and child maltreatment prevention among families experiencing homelessness.

    Using linked administrative data, Dr. Fowler designs and tests big data applications to improve the fairness and efficiency of homelessness services delivery. He employs a complex systems approach to create developmentally appropriate and culturally tailored responses to homelessness.


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

    Webcast: https://usc.zoom.us/webinar/register/WN_b3XxZm-rRfibw54-40F-UA

    Location: Online - Zoom Webinar

    WebCast Link: https://usc.zoom.us/webinar/register/WN_b3XxZm-rRfibw54-40F-UA

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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  • Abbott Coffee Chats with Viterbi Students┬á(On-Campus)

    Mon, Mar 07, 2022 @ 05:00 PM - 06:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Abbott Coffee Chats with Viterbi Students (On-Campus)

    This is a Viterbi-specific On-Campus session!

    Date & Time: Monday, March 7th, 5-6 pm
    Location: RTH 211

    Details: RSVP in Viterbi Career Gateway. RSVP required, space is limited. Your RSVP is a commitment to attend. The event is targeted towards professional development and networking for Viterbi engineering students. Pre-packaged snacks will be provided.

    Abbott Attendees Will Include:
    Nicole Hill, Manufacturing Engineer
    Dean Khan, Senior Design/Product Development
    Engineer Tyler Smith, Supervisor Production

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

    Audiences: Everyone Is Invited

    Contact: RTH 218 Viterbi Career Connections

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  • ECE Seminar: Rethinking Hardware for Cryptography, Security, and Privacy

    Tue, Mar 08, 2022 @ 10:00 AM - 11:00 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Daniel Moghimi, Computer Science and Engineering, UC San Diego

    Talk Title: Rethinking Hardware for Cryptography, Security, and Privacy

    Abstract: Modern computers run on top of complex processors, but complexity is the worst enemy of security. Scientists and engineers have consistently tried to develop secure software systems for decades. However, my work shows that new classes of vulnerabilities in complicated processors can break the security guarantees provided by software systems, cryptographic protocols, and privacy technologies. In this talk, I will give an overview of my work on discovering, evaluating, and mitigating such vulnerabilities. First, I will talk about side-channel attacks on cryptographic implementations. Second, I will discuss vulnerabilities at the microarchitecture level. Finally, I highlight my future work on improving security and privacy through automated testing for hardware vulnerabilities and hardware-software co-design.

    Biography: Daniel Moghimi (https://moghimi.org) is a postdoctoral fellow in Computer Science and Engineering at UCSD. Previously, he received his MS.c in CS and Ph.D. in ECE from Worcester Polytechnic Institute. He develops new techniques and tools to discover new classes of vulnerabilities in hardware, evaluate their impact on software, particularly cryptography, and defend against these vulnerabilities. His work has improved the security of commodity processors and cryptographic products used by billions of users worldwide. Several of his publications have been covered by the news media such as Forbes, Wired, and The Register.

    Host: Dr. Salman Avestimehr, avestime@usc.edu

    Webcast: https://usc.zoom.us/j/96000769674?pwd=ZzJXNmgyNTY1dmo4c21sWXZpSjFuQT09

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

    WebCast Link: https://usc.zoom.us/j/96000769674?pwd=ZzJXNmgyNTY1dmo4c21sWXZpSjFuQT09

    Audiences: Everyone Is Invited

    Contact: Mayumi Thrasher

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  • CS Colloquium: Fei Miao (University of Connecticut) - Learning, Optimization and Control for Efficiency and Security of Cyber-Physical Systems

    Tue, Mar 08, 2022 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Fei Miao, University of Connecticut

    Talk Title: Learning, Optimization and Control for Efficiency and Security of Cyber-Physical Systems

    Series: CS Colloquium

    Abstract: Ubiquitous sensing enables large-scale multi-source data of cyber-physical systems (CPS) collected in real-time and poses both challenges and opportunities for a paradigm-shift to data-driven CPS. For instance, how to capture the complexity and analyze the dynamical state information from data, and make decisions to improve safety, efficiency and security of the networked CPS is still challenging. In this talk, we present our research that integrates optimization, machine learning, control, and game theory to address these challenges, including theoretical contributions, algorithmic design, and experimental validations. We first present data-driven distributionally robust optimization (DRO) methods for CPS efficiency, with application on smart city resource allocation. We design algorithms to construct the uncertainty sets of the model prediction based on spatial temporal data. We prove the computationally tractable forms or equivalent convex optimization forms of the DRO problems to guarantee the worst-case expected cost of real-time decisions. We show the improvement of autonomous mobility-on-demand (AMoD) service fairness and efficiency based on large-scale dataset. Second, we summarize our research contribution for CPS security. We mainly present a hybrid state stochastic game model to guarantee the worst-case cost of the system, and a proved suboptimal algorithm to calculate the mixed policies. Finally, based on our active awarded projects, we briefly discuss future research directions on robust multi-agent reinforcement learning and data-driven robust optimization based decision-making, to address CPS safety, efficiency, and security challenges.

    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Biography: Fei Miao is an Assistant Professor of the Department of Computer Science & Engineering, a Courtesy Faculty of the Department of Electrical & Computer Engineering, University of Connecticut since 2017. She is also affiliated to the Institute of Advanced Systems Engineering and Eversource Energy Center. Her research interests lie in the optimization, machine learning, control, and game theory, to address safety, efficiency, and security challenges of cyber-physical systems. She received the Ph.D. degree and the Best Doctoral Dissertation Award in Electrical and Systems Engineering from the University of Pennsylvania in 2016. She received the B.S. degree majoring in Automation from Shanghai Jiao Tong University. She was a postdoc researcher at the GRASP Lab and the PRECISE Lab of Upenn from 2016 to 2017. Dr. Miao is a receipt of the NSF CAREER Award, the title of the project is "Distributionally Robust Learning, Control, and Benefits Analysis of Information Sharing for Connected and Autonomous Vehicles". Dr. Miao has also received a couple of other awards from NSF, including awards from the Smart & Autonomous Systems, the Cyber-Physical Systems, and the Smart & Connected Communities programs. She received Best Paper Award and Best Paper Award Finalist at the ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS) in 2021 and 2015, respectively.

    Host: Jyo Deshmukh

    Location: 132

    Audiences: By invitation only.

    Contact: Assistant to CS chair

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  • Navigating the Internship/Job Search Workshop (ON-CAMPUS)

    Tue, Mar 08, 2022 @ 01:00 PM - 01:30 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    THIS EVENT WILL BE HOSTED IN-PERSON, ON-CAMPUS

    Increase your knowledge on the job/internship search by attending this professional development Q&A moderated by Viterbi Career Connections staff or Viterbi employer partners.

    For more information about workshops, please visit viterbicareers.usc.edu/workshops.

    Attendance is limited to room capacity

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

    Audiences: Everyone Is Invited

    Contact: RTH 218 Viterbi Career Connections

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  • ISE 651 Epstein Seminar

    Tue, Mar 08, 2022 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Adam Elmachtoub, Associate Professor, Dept. of Industrial Engineering & Ops Research, Columbia University

    Talk Title: Contextual Optimization: Bridging Machine Learning and Operations

    Host: Dr. Phebe Vayanos

    More Information: March 8, 2022.pdf

    Location: Online/Zoom

    Audiences: Everyone Is Invited

    Contact: Grace Owh

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  • Mork Family Department Seminar - Salva Salmani-Rezaie

    Tue, Mar 08, 2022 @ 04:00 PM - 05:15 PM

    Mork Family Department of Chemical Engineering and Materials Science

    Conferences, Lectures, & Seminars


    Speaker: Salva Salmani-Rezaie, University of California, Santa Barbara

    Talk Title: Atomic Scale Understanding of Ferroelectricity and Superconductivity in SrTiO3

    Host: Professor A.Hodge

    Location: Social Sciences Building (SOS) - B46

    Audiences: Everyone Is Invited

    Contact: Heather Alexander

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  • Amazon Student Programs SDE Career Fair Series (Virtual)

    Wed, Mar 09, 2022 @ 10:00 AM - 12:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    https://app.brazenconnect.com/a/amazon-student-programs/e/xB0Ox
    For people who like to invent, there's no better place to explore opportunities than at Amazon!
    Amazon Student Programs is currently looking for interns and full-time software developers (SDEs) to come help build the future with us in 2022. Join us at the Amazon Student Programs SDE Career Fair to learn more.
    Can't wait to meet you!
    - Amazon Student Programs
    External employer-hosted events and activities are not affiliated with the USC Career Center. They are posted on Viterbi Career Connections because they may be of interest to members of the Viterbi community. Inclusion of any activity does not indicate USC sponsorship or endorsement of that activity or event. It is the participant's responsibility to apply due diligence, exercise caution when participating, and report concerns to vcareers@usc.edu

    Location: RSVP in Viterbi Career Gateway

    Audiences: Everyone Is Invited

    Contact: RTH 218 Viterbi Career Connections

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  • CS Colloquium: Christoforos Mavrogiannis (University of Washington) - Building Robots that Humans Accept

    Wed, Mar 09, 2022 @ 10:00 AM - 11:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Christoforos Mavrogiannis, University of Washington

    Talk Title: Building Robots that Humans Accept

    Series: CS Colloquium

    Abstract: Robotics has transformed sectors like manufacturing and fulfillment which now rely on robots to meet their goals. Conventionally, these robots operate in isolation from humans due to safety and efficiency considerations. Lately, there have been efforts towards bringing robots closer to humans to assist in everyday-life tasks, enhance productivity, and augment human capabilities. Despite these efforts, robotic technology has not reached widespread acceptance outside of factories; robot autonomy is often not robust, producing new problems that outweigh its benefits for users. Inspired by theories of technology acceptance, my research strives to develop highly functional, safe, and comfortable robots that humans accept. In this talk, I argue that the path towards acceptance requires imbuing robots with a deeper understanding of how users perceive and react to them. To motivate this perspective, I will share insights on robot navigation in dynamic environments, a fundamental task with many crucial applications ranging from collaborative manufacturing to warehouse automation and healthcare. I will describe a human-inspired algorithmic framework for crowd navigation, highlighting how mathematical abstractions of multiagent behavior enable safe, efficient, and positively perceived robot motion across a series of extensive empirical studies involving real robots and human subjects. Inspired by field-deployment challenges, I will then present a data-driven framework that enables robots to recover from failure via bystander help without overloading users. I will conclude with future directions on the development of shared and full robot autonomy that explicitly reasons about human perceptions to produce safe, trustworthy, and comfortable robot behavior.

    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Biography: Christoforos Mavrogiannis is a postdoctoral Research Associate in the Paul G. Allen School of Computer Science & Engineering at the University of Washington, working with Prof. Siddhartha Srinivasa. His interests lie at the intersection of robotics, human-robot interaction, and artificial intelligence. His research often draws insights from algebraic topology and dynamical systems, tools from machine learning, planning and control, and inspiration from social sciences. He is a full-stack roboticist, passionate about real-world deployment of robot systems, and extensive benchmarking with users. He has been a best-paper award finalist at the ACM/IEEE International Conference on Human-Robot Interaction (HRI), and selected as a Pioneer at the HRI and RSS conferences. He has also led open-source initiatives (Openbionics, MuSHR), for which he has been a finalist for the Hackaday Prize and a winner of the Robotdalen International Innovation Award. His work has received coverage from many media outlets including Wired, IEEE Spectrum, GeekWire, RoboHub, and the Hellenic Broadcasting Corporation. Christoforos holds M.S. and Ph.D. degrees from Cornell University, and a Diploma in mechanical engineering from the National Technical University of Athens.


    Host: Jesse Thomason

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

    Audiences: By invitation only.

    Contact: Assistant to CS chair

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  • ECE Seminar: Algebraic Neural Networks: Stability to Deformations

    Wed, Mar 09, 2022 @ 10:00 AM - 11:00 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Alejandro Parada-Mayorga, Postdoctoral Researcher, Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia

    Talk Title: Algebraic Neural Networks: Stability to Deformations

    Abstract: Convolutional architectures play a central role on countless scenarios in machine learning, and the numerical evidence that proves the advantages of using them is overwhelming. Theoretical insights have provided solid explanations about why such architectures work well. These analysis apparently different in nature, have been performed considering signals defined on different domains and with different notions of convolution, but with remarkable similarities in the final results, posing then the question of whether there exists an explanation for this at a more structural level. In this talk we provide an affirmative answer to this question with a first principles analysis introducing algebraic neural networks (AlgNNs), which rely on algebraic signal processing and algebraic signal models. In particular, we study the stability properties of algebraic neural networks showing that stability results for traditional CNNs, graph neural networks (GNNs), group neural networks, graphon neural networks, or any formal convolutional architecture, can be derived as particular cases of our results. This shows that stability is a universal property - at an algebraic level - of convolutional architectures, and this also explains why the remarkable similarities we find when analyzing stability for each particular type of architecture.

    Biography: Alejandro Parada-Mayorga (alejopm@seas.upenn.edu) received his B.Sc. and M.Sc. degrees in electrical engineering from Universidad Industrial de Santander, Colombia, in 2009 and 2012, respectively, and his Ph.D. degree in electrical engineering from the University of Delaware, Newark, 2019. Currently, he is a postdoctoral researcher at the University of Pennsylvania, Philadelphia, under the supervision of Prof. Alejandro Ribeiro. His research interests include algebraic signal processing, algebraic neural networks, graph neural networks, graph signal processing, and applications of representation theory of algebras and category theory.

    Host: Dr. Shri Narayanan, shri@ee.usc.edu

    Webcast: https://usc.zoom.us/j/92088625170?pwd=enhYNUpicEYvS0R5SEViVVBobjQ1dz09

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

    WebCast Link: https://usc.zoom.us/j/92088625170?pwd=enhYNUpicEYvS0R5SEViVVBobjQ1dz09

    Audiences: Everyone Is Invited

    Contact: Mayumi Thrasher

    OutlookiCal
  • Amazon Student Programs SDE Career Fair (Virtual)

    Wed, Mar 09, 2022 @ 11:00 AM - 12:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Amazon Student Programs SDE Career Fair (Virtual)

    Thursday, March 9, 2022 10:00 AM - 12:00 PM PST

    Register here: https://app.brazenconnect.com/a/amazon-student-programs/e/xB0Ox

    For people who like to invent, there's no better place to explore opportunities than at Amazon!

    Amazon Student Programs is currently looking for interns and full-time software developers (SDEs) to come help build the future with us in 2022. Join us at the Amazon Student Programs SDE Career Fair to learn more.
    Can't wait to meet you! - Amazon Student Programs

    External employer-hosted events and activities are not affiliated with the USC Career Center. They are posted on Viterbi Career Connections because they may be of interest to members of the Viterbi community. Inclusion of any activity does not indicate USC sponsorship or endorsement of that activity or event. It is the participants' responsibility to apply due diligence, exercise caution when participating, and report concerns to vcareers@usc.edu

    Location: Virtual

    Audiences: Everyone Is Invited

    Contact: RTH 218 Viterbi Career Connections

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  • Computer Science General Faculty Meeting

    Wed, Mar 09, 2022 @ 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: TBD

    Audiences: Invited Faculty Only

    Contact: Assistant to CS chair

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  • Robinhood - Resume Workshop (Virtual)

    Wed, Mar 09, 2022 @ 12:00 PM - 01:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Robinhood is on a mission to democratize finance for all. In order to make that mission a reality, we are hiring top student talent across the world! We are dedicated to building a company that represents a variety of backgrounds, perspectives, and skills.
    The University Recruiting team at Robinhood is excited to host a virtual Resume Workshop. We'll have a few of our Robinhoodies share their tips and tricks on finding the right role, preparing for interviews, and landing the job! The latter portion of the session will be focused on resume tips from one of our University Recruiters!
    sign up link: https://ripplematch.com/t/79c715c4

    The event will take place on Zoom; you'll be able to chat and ask any questions you have with the speakers and other attendees using Zoom's chat and Q+A features. Please RSVP and you will receive the Zoom link 15 minutes prior to the event. As a perk for attending, we will be raffling off Robinhood water bottles!
    We're looking forward to seeing you then!
    External employer-hosted events and activities are not affiliated with the USC Viterbi Career Connections Office. They are posted on Viterbi Career Connections because they may be of interest to members of the Viterbi community. Inclusion of any activity does not indicate USC sponsorship or endorsement of that activity or event. It is the participant's responsibility to apply due diligence, exercise caution when participating, and report concerns to vcareers@usc.edu

    Location: Virtual. Sign-up Link in the event description.

    Audiences: Everyone Is Invited

    Contact: RTH 218 Viterbi Career Connections

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  • Navigating the Internship/Job Search Workshop (ON-CAMPUS)

    Wed, Mar 09, 2022 @ 01:00 PM - 01:30 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    THIS EVENT WILL BE HOSTED IN-PERSON, ON-CAMPUS

    Increase your knowledge on the job/internship search by attending this professional development Q&A moderated by Viterbi Career Connections staff or Viterbi employer partners.

    For more information about workshops, please visit viterbicareers.usc.edu/workshops.

    Attendance is limited to room capacity

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

    Audiences: Everyone Is Invited

    Contact: RTH 218 Viterbi Career Connections

    OutlookiCal
  • Center of Autonomy and AI, Center for Cyber-Physical Systems and the Internet of Things, and Ming Hsieh Institute Seminar Series

    Wed, Mar 09, 2022 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Swarat Chaudhuri, Computer Science Department, The University of Texas at Austin

    Talk Title: Neurosymbolic Programming

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

    Abstract: I will speak about Neurosymbolic programming, an emerging research area that bridges the fields of deep learning and program synthesis. Like in classic machine learning, the goal here is to learn functions from data. However, these functions are represented as programs that can use neural modules in addition to symbolic primitives and are induced using a combination of symbolic search and gradient-based optimization. Neurosymbolic programming can offer multiple advantages over end-to-end deep learning. Programs can sometimes naturally represent long-horizon, procedural tasks that are difficult to perform using deep networks. Neurosymbolic representations are also, commonly, easier to interpret and formally verify than neural networks. The restrictions of a programming language can serve as a form of regularization and lead to more generalizable and data-efficient learning. Compositional programming abstractions can also be a natural way of reusing learned modules across learning tasks.

    In the talk, I will illustrate some of the potential benefits of research in this area. I will also categorize the main ways in which symbolic and neural learning techniques come together here. I will conclude with a discussion of the open technical challenges in the field.


    Biography: Swarat Chaudhuri (http://www.cs.utexas.edu/~swarat) is an Associate Professor of Computer Science and the director of the Trishul laboratory at UT Austin. His research lies at the interface of programming languages, logic, and machine learning. Through a synthesis of ideas from these areas, he seeks to develop a new generation of intelligent systems that are designed to be reliable, transparent, secure, and that can solve complex procedural tasks beyond the scope of contemporary AI.

    Host: Pierluigi Nuzzo

    Webcast: https://usc.zoom.us/webinar/register/WN_zyIBh_1gQLmKpMJG0GyLxw

    Location: Online

    WebCast Link: https://usc.zoom.us/webinar/register/WN_zyIBh_1gQLmKpMJG0GyLxw

    Audiences: Everyone Is Invited

    Contact: Talyia White

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  • AME Seminar

    Wed, Mar 09, 2022 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Talk Title: Data-driven discovery of governing equations with deep learning and sparse identification techniques

    Abstract: Machine learning techniques promise to offer the ultimate form of automation, particularly when applied to computational modeling and simulation. As a consequence, the computational scientist's narrative now revolves around discovering physics directly from data, with as little assumptions about the underlying physical system as possible. I briefly go over the latest attempts to accomplish this goal and focus on my recent work in combining deep learning with sparse identification of differential equations. First, I show how probability distribution function (PDF) equations can be inferred from Monte Carlo simulations for coarse-graining and closure approximations. Second, I present our latest results on discovering dimensionless groups from data, using the Buckingham Pi theorem as a constraint. And third, I go over the deep delay autoencoder algorithm that reconstructs high dimensional models from partial measurements as motivated by Takens' embedding theorem. I finally highlight the limitations of these methods and propose a few directions for future research.

    Biography: Joseph Bakarji is currently a postdoctoral fellow in the department of mechanical engineering at the University of Washington, working with Steven Brunton and Nathan Kutz. He received his PhD in 2020 from Stanford University where he developed multiscale stochastic models for granular materials and data-driven closure models for uncertainty quantification. Joseph received the Henry J. Ramey, Jr. and the Frank G. Miller fellowship awards in 2018 and 2020 respectively. His current research focuses on combining deep learning and sparse identification methods, to discover interpretable physical models in complex systems from data.

    More Info: https://usc.zoom.us/j/93987337017?pwd=MWd2dXBSL1FaR1RPaHNscjJ1NW80UT09

    Webcast: https://usc.zoom.us/j/93987337017?pwd=MWd2dXBSL1FaR1RPaHNscjJ1NW80UT09

    Location: James H. Zumberge Hall Of Science (ZHS) - 252

    WebCast Link: https://usc.zoom.us/j/93987337017?pwd=MWd2dXBSL1FaR1RPaHNscjJ1NW80UT09

    Audiences: Everyone Is Invited

    Contact: Tessa Yao

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  • ECE Seminar: A Variegated Study of 5G Services: Challenges, Opportunities, and Application Innovations

    Thu, Mar 10, 2022 @ 10:00 AM - 11:00 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Feng Qian, Associate Professor, Department of Computer Science and Engineering, University of Minnesota - Twin Cities

    Talk Title: A Variegated Study of 5G Services: Challenges, Opportunities, and Application Innovations

    Abstract: 5G is expected to support sub-millisecond latency as well as throughput of up to 20 Gbps -- a 100x improvement compared to 4G/LTE. However, there exists a vacuum in understanding how 5G performs "in the wild" and whether it can fulfill its promises. In this talk, I will describe our research thrust of 5G networks since early 2019, when Minneapolis became one of the first two U.S. cities that received commercial 5G deployment. Over the past 3 years, we have experimented with more than 100 TB of 5G data and traveled more than 8,000 km for drive tests. Our studies revealed a complete landscape of 5G across several key dimensions -- network performance, power characteristics, mobility management, application quality-of-experience (QoE), to name a few, with their critical tradeoffs quantitatively revealed. I will then talk about our development of a learning-based framework for accurate 5G performance prediction, and how we innovate emerging applications such as virtual/mixed reality (VR/MR) to improve their QoE on 5G networks.

    Biography: As an experimental networking and system researcher, I design, engineer, deploy, evaluate real network systems, and make them yield real-world impact. I am particularly interested in mobile systems, AR/VR, mobile networking, wearable computing, real-world system measurements.

    I received my Ph.D. from EECS at University of Michigan in 2012. I am honored to receive several awards including the AT&T Key Contributor Award (2014), NSF CRII Award (2016), Google Faculty Award (2016), ACM CoNEXT Best Paper Award (2016,2018), AT&T VURI Award (2017), NSF CAREER Award (2018), Trustees Teaching Award (2018), DASH-IF Excellence Award (2019), Cisco Research Award (2021), and ACM SIGCOMM Best Student Paper Award (2021). Some of my research prototypes such as mobile Application Resource Optimizer (ARO) have been commercialized and are widely used in academia and industry.

    Host: Dr. Konstantinos Psounis, kpsounis@usc.edu

    Webcast: https://usc.zoom.us/j/93770414634?pwd=SlBFL0JwL3QwR0RjK1p5bVMyM3duQT09

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

    WebCast Link: https://usc.zoom.us/j/93770414634?pwd=SlBFL0JwL3QwR0RjK1p5bVMyM3duQT09

    Audiences: Everyone Is Invited

    Contact: Mayumi Thrasher

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  • Astani Department of Civil and Environmental Engineering Seminar

    Thu, Mar 10, 2022 @ 01:30 PM - 01:30 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Michael Gomez, Ph.D., University of Washington

    Talk Title: Bio-cementation Soil Improvement for the Mitigation of Earthquake-induced Soil Liquefaction

    Abstract: Recent advances in bio-mediated soil improvement technologies have highlighted the potential of natural biological-chemical reactions in the soil subsurface to enable mitigation of infrastructure damage resulting from natural hazards such as earthquakes. Bio-mediated geotechnical solutions leverage the capabilities of microorganisms already existing in the geotechnical subsurface to generate a diverse range of products, which can dramatically improve the engineering behavior of soils. One such technology, Microbially Induced Calcite Precipitation (MICP), is an environmentally conscious soil improvement technique that can improve the geotechnical properties of granular soils through the precipitation of calcite. The biogeochemical process offers an environmentally-conscious alternative to traditional brute-force mechanical and Portland cement based ground improvement methods, by utilizing natural microbial enzymatic activity to induce calcite precipitation on soil particle surfaces and at particle contacts. The resulting bio-cementation affords improvements in soil shear strength, initial shear stiffness, and liquefaction resistance, while reducing soil hydraulic conductivity and porosity. Although MICP has been demonstrated extensively at the laboratory scale, critical gaps remain in our understanding of this technology with respect to up-scaling the process to field-scale, understanding the engineering behavior of (bio-)cemented geomaterials, and evaluating material permanence. This presentation will provide a brief introduction to MICP and highlight results from several recent experiments completed at centimeter- and meter- scales aimed at: (1) developing the MICP process for field-scale deployment including techniques for the stimulation of indigenous microorganisms, management of ammonium by-products, and improvement of cementation spatial uniformity and extent, (2) characterizing the liquefaction resistance of bio-cemented geomaterials including triggering and post-triggering responses, and (3) systematically exploring the effect of treatment conditions and environmental factors on resulting material mineralogy and long-term

    Biography: Mike Gomez is an Assistant Professor in the department of Civil and Environmental Engineering at the University of Washington. Mike joined UW in March 2017 after completing his Ph.D. at the University of California, Davis. His research focuses on leveraging natural chemical and biological processes in soils to develop sustainable bio-mediated geotechnical ground improvement technologies. In particular, Mike research has focused on the strengthening of loose and weak granular soils through a bio-mediated calcite precipitation process known as Microbially Induced Calcite Precipitation (MICP). Mike additional research interests include advanced laboratory and in-situ testing, naturally cemented and aged geomaterials, reactive transport modeling, clay surface chemistry, and non-destructive measurements for site characterization and subsurface reaction monitoring, among other topics.



    Host: Dr. Chukwuebuka Nweke

    Webcast: https://usc.zoom.us/j/91873923659 Meeting ID: 918 7392 3659 Pass: 975701

    Location: ZOOM MEETING

    WebCast Link: https://usc.zoom.us/j/91873923659 Meeting ID: 918 7392 3659 Pass: 975701

    Audiences: Everyone Is Invited

    Contact: Evangeline Reyes

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  • DEI Committee Meeting

    Thu, Mar 10, 2022 @ 02:00 PM - 03:00 PM

    Computer Science

    Receptions & Special Events


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

    Audiences: Invited Faculty Only

    Contact: Assistant to CS chair

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  • Nike X Ready Player One - INSIDIOUS Hackathon (Virtual)

    Thu, Mar 10, 2022 @ 04:00 PM - 08:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    INSIDIOUS is a hackathon training event brought to you by Nike's Corporate Information Security team.
    You will compete in a safe, sandboxed environment where you will seek out and take advantage of vulnerabilities in a real application.
    Please note: Students MUST RSVP through the external registration form in order to participate.
    https://nike.recsolu.com/app/collect/event/__QzR_-rdu5ni0xFGqKEVA
    The course includes instructor-led training to review how the code should be written securely, followed by an awards ceremony with prizes to celebrate the top hackers.
    This event will offer you the opportunity to show your growing skillset off to some of Nike's choice recruiting members.
    The event will be virtual and hosted on Zoom, and we have 4 sessions you can select from:
    March 3rd, 2022
    Afternoon session: 4:00-8:00 PM EST
    March 10th, 2022
    Afternoon session: 4:00-8:00 PM EST

    Access to a computer is required.
    External employer-hosted events and activities are not affiliated with the USC Viterbi Career Connections Office. They are posted on Viterbi Career Connections because they may be of interest to members of the Viterbi community. Inclusion of any activity does not indicate USC sponsorship or endorsement of that activity or event. It is the participant's responsibility to apply due diligence, exercise caution when participating, and report concerns to vcareers@usc.edu

    Location: Virtual. RSVP Link in the event description.

    Audiences: Everyone Is Invited

    Contact: RTH 218 Viterbi Career Connections

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  • Mork Family Department Seminar - Miaofang Chi

    Thu, Mar 10, 2022 @ 04:00 PM - 05:15 PM

    Mork Family Department of Chemical Engineering and Materials Science

    Conferences, Lectures, & Seminars


    Speaker: Miaofang Chi, Center for Nanophase Materials Sciences at Oak Ridge National Laboratory

    Talk Title: Emerging Scanning Transmission Electron Microscopy (STEM) for Energy Materials Research

    Host: Professor A.Hodge

    Location: Kaprielian Hall (KAP) - 147

    Audiences: Everyone Is Invited

    Contact: Heather Alexander

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  • CS Colloquium: David Held (Carnegie Mellon University) - Perceptual Robot Learning

    Thu, Mar 10, 2022 @ 05:00 PM - 06:20 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: David Held, Carnegie Mellon University

    Talk Title: Perceptual Robot Learning

    Series: Computer Science Colloquium

    Abstract: *New time: 5:00-6:20PM*

    Robots today are typically confined to interact with rigid, opaque objects with known object models. However, the objects in our daily lives are often non-rigid, can be transparent or reflective, and are diverse in shape and appearance. One reason for the limitations of current methods is that computer vision and robot planning are often considered separate fields. I argue that, to enhance the capabilities of robots, we should design state representations that consider both the perception and planning algorithms needed for the robotics task. I will show how we can develop novel perception and planning algorithms to assist with the tasks of manipulating cloth, articulated objects, and transparent and reflective objects. By thinking about the downstream task while jointly developing perception and planning algorithms, we can significantly improve our progress on difficult robots tasks.

    Register in advance for this webinar at:
    https://usc.zoom.us/webinar/register/WN_X9bmT5afSU2gjC03nttQHg

    After registering, attendees will receive a confirmation email containing information about joining the webinar.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: David Held is an assistant professor at Carnegie Mellon University in the Robotics Institute and is the director of the RPAD lab: Robots Perceiving And Doing. His research focuses on perceptual robot learning, i.e. developing new methods at the intersection of robot perception and planning for robots to learn to interact with novel, perceptually challenging, and deformable objects. David has applied these ideas to robot manipulation and autonomous driving. Prior to coming to CMU, David was a post-doctoral researcher at U.C. Berkeley, and he completed his Ph.D. in Computer Science at Stanford University. David also has a B.S. and M.S. in Mechanical Engineering at MIT. David is a recipient of the Google Faculty Research Award in 2017 and the NSF CAREER Award in 2021.


    Host: Stefanos Nikolaidis

    Webcast: https://usc.zoom.us/webinar/register/WN_X9bmT5afSU2gjC03nttQHg

    Location: Online - Zoom Webinar

    WebCast Link: https://usc.zoom.us/webinar/register/WN_X9bmT5afSU2gjC03nttQHg

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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  • Repeating EventGrammar Tutorials

    Fri, Mar 11, 2022 @ 10:00 AM - 12:00 PM

    Viterbi School of Engineering Student Affairs

    Workshops & Infosessions


    INDIVIDUAL GRAMMAR TUTORING FOR VITERBI UNDERGRADUATE AND GRADUATE STUDENTS

    Meet one-on-one with Viterbi faculty, build your grammar skills, and take your writing to the next level!

    Viterbi faculty from the Engineering in Society Program (formerly the Engineering Writing Program) will help you identify and correct recurring grammatical errors in your academic writing, cover letters, resumes, articles, presentations, and dissertations.
    Bring your work, and let's work together to clarify your great ideas!

    Contact helenhch@usc.edu with questions.




    Location: Zoom

    Audiences: Graduate and Undergraduate Students

    View All Dates

    Contact: Helen Choi

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  • ECE Seminar: Optics, Sensors & AI: Next-Generation Computational Imaging

    Fri, Mar 11, 2022 @ 10:00 AM - 11:00 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Vivek Boominathan, Postdoctoral Research Associate, Department of Electrical and Computer Engineering, Rice University

    Talk Title: Optics, Sensors & AI: Next-Generation Computational Imaging

    Abstract: Rapidly growing machine learning techniques such as deep learning have produced powerful computer vision algorithms. However, these algorithms usually apply to images and videos captured with traditional camera designs that have been principally unchanged for decades. Furthermore, real-world applications such as robotics, autonomous navigation, augmented/virtual reality, human-computer interaction, biomedical, and IoT need systems that adhere to fundamental constraints such as size, weight, power, and privacy. These fundamental constraints cannot be addressed by a software-only solution but demand a joint hardware-software solution. In my talk, I will present end-to-end computational imaging systems that execute "computation" at all stages of a physical vision system, from optics to sensors to algorithms. Novel optics such as diffractive and metamaterial optics provide new dimensions of light manipulation, while novel sensors such as SPADs offer new dimensions in light transduction. I will highlight algorithms and AI to explore these new dimensions and accessible nanofabrication techniques to realize novel optics and sensors. I will show applications from photographic 3D imaging to in vivo 3D imaging, achieved using compact coded aperture systems and ultraminiature lensless imaging systems. I will conclude by describing how my works set the stage for designing next-generation imaging systems for various future applications such as biomedical imaging, robotics, IoT, and human-computer interaction.

    Biography: Dr. Vivek Boominathan is a postdoctoral research associate in the Department of Electrical and Computer Engineering at Rice University. He received his Ph.D. in 2019, advised by Prof. Ashok Veeraraghavan, and co-advised by Prof. Jacob Robinson and Prof. Richard Baraniuk. His research interests lie at the intersection of computer vision, machine learning, applied optics, and nanofabrication. His contributions have appeared in a broad spectrum of venues such as Science Advances, Nature BME, IEEE journals, optics journals, vision conferences, and circuits conferences. He has also published a review article, in Optica, around his Ph.D. topic of lensless imaging. His work has been covered by news media such as EurekAlert, NPR, Phys.org, and NDTV India. He has co-organized a tutorial on Computational Imaging and Machine Learning in CVPR 2019 and has served as the publication co-chair for ICCP since 2020. More details can be found at https://vivekboominathan.com/.


    Host: Dr. Shri Narayanan, shri@ee.usc.edu

    Webcast: https://usc.zoom.us/j/96039656028?pwd=RnVxeGx3aEZ3RTNsTW5PajFWakN2Zz09

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

    WebCast Link: https://usc.zoom.us/j/96039656028?pwd=RnVxeGx3aEZ3RTNsTW5PajFWakN2Zz09

    Audiences: Everyone Is Invited

    Contact: Mayumi Thrasher

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  • CS Colloquium: Harsha V. Madhyastha (University of Michigan) - Inter-connecting society across space and time

    Fri, Mar 11, 2022 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Harsha V. Madhyastha, University of Michigan

    Talk Title: Inter-connecting society across space and time

    Series: CS Colloquium

    Abstract: Thanks to the Internet and a range of services that have been developed to take advantage of it -- web, email, social media, instant messaging, etc. -- being in the same place at the same time is no longer a requirement for all of us to share information with each other. Instead, we are able to store our ideas, opinions, and observations on services which enable others to access this information later from anywhere in the world.

    In this talk, I will discuss my group/s work over the past several years to address some of the fundamental challenges faced by the providers of such global-scale services. I will provide examples of two broad research thrusts: 1) enabling cost-effective development and deployment of geo-distributed services, and 2) optimizing the availability and performance of client-service interactions. I will also briefly discuss my ongoing research in facilitating
    information exchange in domains such as web archival, federated learning, and 3D printing.


    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Biography: Harsha V. Madhyastha is an Associate Professor in CSE at the University of Michigan. His research broadly spans the areas of distributed systems and
    networking. Two of his papers have received the IRTF's Applied Networking Research Prize, and he has also co-authored award papers at OSDI, NSDI, and IMC. He has received multiple Google Faculty Research awards, a NetApp Faculty Fellowship, a Facebook Faculty Award, and an NSF CAREER award.


    Host: Barath Raghavan

    Audiences: By invitation only.

    Contact: Assistant to CS chair

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  • ECE-EP Seminar - Quntao Zhuang, Friday, March 11th at 2pm in EEB 248

    Fri, Mar 11, 2022 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Quntao Zhuang, University of Arizona

    Talk Title: Quantum Information Processing: From Fundamentals to Applications

    Abstract: Quantum physics has changed the way we understand nature, and also the way we process information. Starting from the fundamental questions raised a century ago, we have now entered an era of quantum engineering. In this talk, I will introduce our recent results on quantum sensing and communication. Quantum sensing utilizes quantum effects such as coherence, squeezing and entanglement to boost measurement sensitivity. I will summarize the paradigm of distributed quantum sensing, which utilizes multi-partite entanglement to boost the measurement of an arbitrary function of local network parameters, generalizing the famous Heisenberg limit of quantum sensing; distributed quantum sensing has a wide range of applications, including dark matter search in different platforms and quantum machine learning. Then, I will briefly present our recent results on quantum radar and quantum spectroscopy. Finally, I will introduce our works on quantum communication. Claude Shannon established the famous classical capacity of communication channels---the ultimate rate at which classical physics allows us to communicate. Quantum physics has made things more interesting. To begin with, I will introduce our recent works in breaking the Shannon capacity for the first time, by utilizing quantum entanglement; Next, I will briefly summarize works on quantum information transmission, including quantum transduction and quantum repeaters.

    Biography: Quntao Zhuang is an assistant professor in ECE and Optical Sciences at University of Arizona. He joined university of Arizona in 2019 after a brief postdoc at University of California, Berkeley. He got his PHD in physics from MIT in 2018. He received the NSF CAREER award in 2022, DARPA Young Faculty Award and Craig M. Berge Dean's Fellow in 2020.

    Host: ECE-Electrophysics

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

    Audiences: Everyone Is Invited

    Contact: Marilyn Poplawski

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  • PhD Thesis Proposal - Aaron Chan

    Fri, Mar 11, 2022 @ 03:00 PM - 05:00 PM

    Computer Science

    University Calendar


    PhD Candidate: Aaron Chan

    Title: Generating and Utilizing Machine Explanations for Trustworthy NLP

    Time: Friday, March 11, 3:00PM-5:00PM PST

    Committee: Xiang Ren, Robin Jia, Jesse Thomason, Bistra Dilkina, Morteza Dehghani

    Abstract:
    Neural language models (NLMs) have achieved remarkable success on a wide range of natural language processing (NLP) tasks. However, NLMs sometimes exhibit undesirable behavior, which can be difficult to resolve due to NLMs' opaque reasoning processes. Such a lack of transparency poses serious concerns about NLMs' trustworthiness in high-stakes decision-making.

    This motivates the use of machine explanations to automatically interpret how NLMs make decisions. In my thesis proposal, I argue that building human trust in NLP systems requires being able to: (A) generate machine explanations for NLM behavior faithfully and plausibly, and (B) utilize machine explanations to improve language model decision-making.

    First, I introduce a framework for optimizing machine explanations w.r.t. both faithfulness and plausibility, without compromising the NLM's task performance. Second, I present an algorithm for regularizing NLMs via machine explanations, in order to improve NLM task performance. Third, I discuss using limited human-in-the-loop feedback on machine explanations to further improve NLMs' generalization ability.

    Zoom Link: https://usc.zoom.us/j/99570395469?pwd=OE9IMnhLOU5oSmRCYzFiUWdMZ1BuZz09

    WebCast Link: https://usc.zoom.us/j/99570395469?pwd=OE9IMnhLOU5oSmRCYzFiUWdMZ1BuZz09

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

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