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Conferences, Lectures, & Seminars
Events for November

  • Infectious Disease Forecasting: Methods, Lessons, and Opportunities

    Tue, Nov 02, 2021 @ 10:00 AM - 11:00 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Ajitesh Srivastava, Research Assistant Professor/Ming Hsieh Department of Computer and Electrical Engineering

    Talk Title: Infectious Disease Forecasting: Methods, Lessons, and Opportunities

    Abstract: After more than a year, COVID-19 continues to disrupt our lives. Efforts have been underway since the beginning to understand the epidemiological situation and generate short-term forecasts and long-term scenario projections to drive public health decisions. These efforts, called "hubs" are collaborations between government agencies and multiple universities. In this talk, I will discuss the lessons learned from my participation in several such efforts in modeling and projection of COVID-19, and the resulting research opportunities. I will also present my methodology which has evolved over time to now incorporate dynamics of multiple competing variants, vaccination behavior, age-specific contact matrices, and waning immunity. A key feature of the approach is that it avoids overfitting by splitting the model into independent linear regression problems. An additional advantage is that the runtime is low. As an example, learning the model and generating case, death, and hospitalization forecasts for 56 regions of the US, each with around 25 variants and 5 age groups, takes ~20s on a 2-core desktop. This also enables fast scenario projections, where even for each scenario multiple runs are needed to incorporate uncertainty in hyper-parameters and human behavior. This may not be the last pandemic we will face, and therefore the research does not end with COVID-19. In fact, the extensive data-collection, monitoring, and forecasting during this epidemic sets the stage for more impactful research in preparedness for future epidemics.

    Biography: Dr. Ajitesh Srivastava is a Research Assistant Professor at the Ming Hsieh Department of Computer and Electrical Engineering. He obtained his PhD in Computer Science at the University of Southern California in 2018. His research interests include network science, modeling, and machine learning applied to epidemics, social good, social networks, and systems. He collaborates with teams around the world, the CDC, and the ECDC for infectious disease forecasting and scenario projections. He is a DARPA Grand Challenge Winner (2014) on predicting the spread of Chikungunya virus.

    Host: Dr. Richard M. Leahy, Chair, Ming Hsieh Department of Electrical and Computer Engineering (Systems)

    Webcast: https://usc.zoom.us/j/91552972911?pwd=VG5DczVLdk9vQllBK2ZQT2l3dUJuQT09

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

    WebCast Link: https://usc.zoom.us/j/91552972911?pwd=VG5DczVLdk9vQllBK2ZQT2l3dUJuQT09

    Audiences: Everyone Is Invited

    Contact: Mayumi Thrasher

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  • CAIS Seminar: Itai Ashlagi (Stanford University) - Designing school choice for Diversity in San Francisco Unified School District

    Tue, Nov 02, 2021 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Dr. Itai Ashlagi, Stanford University

    Talk Title: Designing school choice for Diversity in San Francisco Unified School District

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

    Abstract: In December 2018, the Board of Education of San Francisco Unified School District (SFUSD) passed a resolution for developing a student assignment system for elementary schools, which seeks to improve diversity, transparency, and equal access to quality schools.

    This follows an increasing trend towards segregation in the last two decades despite the diversity in the district. In this talk I will describe ongoing research, building on tools from Optimization and Economics, that supported SFUSD towards a new student assignment system to achieve these goals.

    This is based on joint work with Max Allman, Irene Lo and Kaleigh Mentzer


    Register in advance for this webinar at:

    https://usc.zoom.us/webinar/register/WN_Fmg9g80OTcazDrCONyD4YA

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

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Itai Ashlagi is an Associate Professor at the Stanford University Management Science & Engineering Department. He is interested in market design. His work influenced the practice of kidney exchange, for which he has become a Franz Edelman Laureate.


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

    Webcast: https://usc.zoom.us/webinar/register/WN_Fmg9g80OTcazDrCONyD4YA

    Location: Online - Zoom Webinar

    WebCast Link: https://usc.zoom.us/webinar/register/WN_Fmg9g80OTcazDrCONyD4YA

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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  • ISE 651 - Epstein Seminar

    Tue, Nov 02, 2021 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Dmitriy Drusvyatskiy, Associate Professor, Dept. of Mathematics, University of Washington

    Talk Title: Stochastic Optimization Under Distributional Shifts

    Host: Dr. Meisam Razaviyayn

    More Information: November 2, 2021.pdf

    Location: Zoom/Online

    Audiences: Everyone Is Invited

    Contact: Grace Owh

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  • CS Colloquium: Lisa Soros (Cross Labs) - Designing Open-Ended Algorithms via Artificial Life

    Tue, Nov 02, 2021 @ 03:30 PM - 04:50 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Lisa Soros, Cross Labs

    Talk Title: Designing Open-Ended Algorithms via Artificial Life

    Series: Computer Science Colloquium

    Abstract: Most algorithms implemented in computers are designed to converge in a finite amount of time. Yet, some of the most powerful generative processes in the natural world (such as evolution) have been running for millions or billions of years. Is it possible to create algorithms that generate interesting and complex artifacts on the same scale as natural evolution? This talk will give an introduction to research on the synthesis and simulation of living systems, also known as Artificial Life. It will focus primarily on the challenge of open-ended evolutionary processes, which may pave the way for open-ended artificial intelligence.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Lisa Soros is a Postdoctoral Research Fellow at Cross Labs, which is a hybrid academic-industrial research institute based in Kyoto, Japan and dedicated to studying natural and artificial intelligence. Her research interests broadly include evolutionary computation, artificial life, and video game AI. She is a graduate of the Evolutionary Complexity Research Group at the University of Central Florida and completed her dissertation, "Necessary Conditions for Open-Ended Evolution" in 2018. Since then, she has been an Assistant Professor at Champlain College in Burlington, Vermont and a Postdoctoral Researcher at the Game Innovation Lab at New York University.


    Host: Stefanos Nikolaidis

    Location: Seeley Wintersmith Mudd Memorial Hall (of Philosophy) (MHP) - 101

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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

    Wed, Nov 03, 2021 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Yan Gu, Department of Mechanical Engineering at the University of Massachusetts Lowell

    Talk Title: Dynamic Modeling, Hybrid Filtering, and Robust Control of Legged Robot Locomotion on Dynamic Rigid Surfaces

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

    Abstract: Legged robots have the potential to assist humans with a wide range of real-world tasks in dynamic, unstructured environments, such as search and rescue on disaster sites, monitoring of natural resources, home assistance, and delivery and courier services. They can navigate natural and built environments prohibitively challenging for wheeled or tracked robots and adapt to human environments without significant modifications of existing facilities (e.g., ladders, stairs, and narrow passageways). While legged locomotion on stationary (even or uneven) surfaces has been extensively studied, legged locomotion on a dynamic rigid surface (DRS), which is a rigid surface that moves in the inertial frame, remains a new robot functionality that has not been tackled. This new functionality will empower legged robots to perform high-risk tasks such as shipboard firefighting and fire suppression as well as disinfection on moving public transportation vehicles to help contain the spread of infectious diseases. Yet, enabling reliable DRS locomotion presents substantial challenges due to the high complexity of the hybrid, time-varying robot dynamics. In this talk, Dr. Yan Gu will present the latest research progress from her group in tackling the challenges associated with the modeling, state estimation, and control of DRS locomotion.

    Biography: Dr. Yan Gu received her B.S. degree in Mechanical Engineering from Zhejiang University (China) in June 2011 and her Ph.D. degree in Mechanical Engineering from Purdue University in August 2017. She joined the Department of Mechanical Engineering at the University of Massachusetts Lowell (UML) as an Assistant Professor in September 2017. Her research focuses on nonlinear control and hybrid systems with application to legged robots. Her long-term research goal is to realize provably safe and autonomous legged locomotion in dynamic, complex environments. She has received the NSF CAREER Award, the Frederick N. Andrews Fellowship at Purdue University, and the Chu Kochen Scholarship at Zhejiang University. Her research on legged locomotion has been funded by NSF, ONR, ARL, and Verizon's 5G Lab and reported by various media such as Boston Globe, CNET, Robotics Business Review, and NPR.

    Host: Pierluigi Nuzzo and Feifei Qian

    Webcast: https://usc.zoom.us/webinar/register/WN_p5OEJlPxQlakO4hqovuGEQ

    Location: Online

    WebCast Link: https://usc.zoom.us/webinar/register/WN_p5OEJlPxQlakO4hqovuGEQ

    Audiences: Everyone Is Invited

    Contact: Talyia White

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  • AME Seminar

    Wed, Nov 03, 2021 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Canceled,

    Talk Title: Canceled

    Abstract: Dear all, due to the speaker having a family emergency, the November 3 seminar has been canceled.

    Host: AME Department

    Audiences: Everyone Is Invited

    Contact: Tessa Yao

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  • Astani Department of Civil and Environmental Engineering Seminar

    Thu, Nov 04, 2021 @ 11:00 AM - 12:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Mitul Luhar, USC Aerospace and Mechanical Engineering

    Talk Title: TBA

    Abstract: TBA

    Host: Dr. Felipe de Barros

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

    Audiences: Everyone Is Invited

    Contact: Evangeline Reyes

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  • The Next Billion Dollar Opportunity: Transforming Healthcare Through Viterbi Innovation

    Thu, Nov 04, 2021 @ 04:00 PM - 05:00 PM

    Viterbi School of Engineering Alumni

    Conferences, Lectures, & Seminars


    Speaker: Gaurav Sukhatme, Ellis Meng and Krishna Nayak, Professors of USC Viterbi

    Talk Title: VIP Bay Area

    Abstract: USC Viterbi is revolutionizing healthcare through biomedical research and transferring technology to industry.

    Join us to hear from Gaurav Sukhatme, Fletcher Jones Foundation Endowed Chair in Computer Science and Amazon Scholar (2020-2021), Professor Ellis Meng, Vice Dean of Technology, Innovation and Entrepreneurship and Shelly and Ofer Nemirovsky Chair in Convergent Bioscience and Krishna Nayak, Professor of Electrical and Computer Engineering and Biomedical Engineering, as they discuss current developments in research and collaborations between the USC Viterbi School of Engineering and Keck School of Medicine of USC and transferring tech to market.

    Space is limited. Zoom link will be provided upon completion of registration.

    Host: USC Viterbi Innovation Partners Bay Area Executive Committee

    More Info: https://usc.zoom.us/webinar/register/WN_QCK8QEpIRjSekypqXxr8tA

    Audiences: Everyone Is Invited

    Contact: Kristy Ly

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  • Advanced Manufacturing Seminar

    Fri, Nov 05, 2021 @ 11:00 AM - 12:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Shreyes N. Melkote, Georgia Institute of Technology

    Talk Title: A Digital Apprentice for Machining Chatter Detection: Application of Learning from Human Demonstration

    Abstract: Regenerative chatter in machining operations such as milling is a common process anomaly that limits productivity and part quality. Traditional approaches for addressing this anomaly include chatter avoidance methods based on off-line dynamic stability analysis, and on-line chatter detection and suppression through real-time sensing and control. Chatter avoidance methods require specialized knowledge and skills for dynamic system identification and suffer from uncertainty in the stability boundary identification. On-line chatter detection methods tend to suffer from a high number of false positives and cannot always reliably detect chatter before part/machine damage occurs. Consequently, manufacturers often rely on the auditory and cognitive abilities of experienced human operators to monitor and control the machining process. This talk will present recent work that is inspired by learning from human demonstration frameworks to enable effective milling chatter detection via human-machine interaction, which facilitates knowledge transfer from an experienced operator to a Digital Apprentice consisting of an audio sensor, a learnable skill primitive for chatter detection, and a human-machine interface. Experimental results evaluating the effectiveness of this approach for chatter detection will be presented and discussed.

    Biography: Dr. Shreyes N. Melkote holds the Morris M. Bryan Professorship in Advanced Manufacturing Systems in the George W. Woodruff School of Mechanical Engineering at Georgia Tech. He serves as Associate Director of the Georgia Tech Manufacturing Institute and as Executive Director of the Novelis Innovation Hub at Georgia Tech. Dr. Melkotes current research interests are in robotic manufacturing, science of precision material removal processes, novel surface enhancement methods, and data-driven methods for cyber manufacturing. His research in these areas is actively supported by industry and government sponsors. He is a Fellow of the ASME, SME, and CIRP.

    Host: Center for Advanced Manufacturing

    More Info: Registration Link: https://usc.zoom.us/webinar/register/WN_iOnvGwluSO-vDE5VsyYzTQ

    Audiences: Everyone Is Invited

    Contact: Tessa Yao

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  • CS Distinguished Lecture: Michael Bronstein (Imperial College London / Twitter) - Geometric Deep Learning: from Euclid to drug design

    Tue, Nov 09, 2021 @ 11:00 AM - 12:20 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Michael Bronstein, Imperial College London / Twitter

    Talk Title: Geometric Deep Learning: from Euclid to drug design

    Series: Computer Science Distinguished Lecture Series

    Abstract: For nearly two millennia, the word "geometry" was synonymous with Euclidean geometry, as no other types of geometry existed. Euclid's monopoly came to an end in the 19th century, where multiple examples of non-Euclidean geometries were shown. However, these studies quickly diverged into disparate fields, with mathematicians debating the relations between different geometries and what defines one. A way out of this pickle was shown by Felix Klein in his Erlangen Programme, which proposed approaching geometry as the study of invariants or symmetries using the language of group theory. In the 20th century, these ideas have been fundamental in developing modern physics, culminating in the Standard Model.

    The current state of deep learning somewhat resembles the situation in the field of geometry in the 19h century: On the one hand, in the past decade, deep learning has brought a revolution in data science and made possible many tasks previously thought to be beyond reach -” including computer vision, playing Go, or protein folding. At the same time, we have a zoo of neural network architectures for various kinds of data, but few unifying principles. As in times past, it is difficult to understand the relations between different methods, inevitably resulting in the reinvention and re-branding of the same concepts.

    Geometric Deep Learning aims to bring geometric unification to deep learning in the spirit of the Erlangen Programme. Such an endeavour serves a dual purpose: it provides a common mathematical framework to study the most successful neural network architectures, such as CNNs, RNNs, GNNs, and Transformers, and gives a constructive procedure to incorporate prior knowledge into neural networks and build future architectures in a principled way.

    In this talk, I will overview the mathematical principles underlying Geometric Deep Learning on grids, graphs, and manifolds, and show some of the exciting and groundbreaking applications of these methods in the domains of computer vision, social science, biology, and drug design.

    (based on joint work with J. Bruna, T. Cohen, P. Veličković)

    Register in advance for this webinar at:

    https://usc.zoom.us/meeting/register/tJAodeitqTwjHNLVLccoIBCb3Ngtx0rHF1TR

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

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Michael Bronstein is a professor at Imperial College London, where he holds the Chair in Machine Learning and Pattern Recognition, and Head of Graph Learning Research at Twitter. Michael received his PhD from the Technion in 2007. He has held visiting appointments at Stanford, MIT, and Harvard, and has also been affiliated with three Institutes for Advanced Study (at TUM as a Rudolf Diesel Fellow (2017-2019), at Harvard as a Radcliffe fellow (2017-2018), and at Princeton as a short-time scholar (2020)). Michael is the recipient of the Royal Society Wolfson Research Merit Award, Royal Academy of Engineering Silver Medal, five ERC grants, two Google Faculty Research Awards, and two Amazon AWS ML Research Awards. He is a Member of the Academia Europaea, Fellow of IEEE, IAPR, BCS, and ELLIS, ACM Distinguished Speaker, and World Economic Forum Young Scientist. In addition to his academic career, Michael is a serial entrepreneur and founder of multiple startup companies, including Novafora, Invision (acquired by Intel in 2012), Videocites, and Fabula AI (acquired by Twitter in 2019).


    Host: Mukund Raghothaman

    Webcast: https://usc.zoom.us/meeting/register/tJAodeitqTwjHNLVLccoIBCb3Ngtx0rHF1TR

    Location: Online - Zoom Webinar

    WebCast Link: https://usc.zoom.us/meeting/register/tJAodeitqTwjHNLVLccoIBCb3Ngtx0rHF1TR

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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  • Photonics Seminar Series

    Tue, Nov 09, 2021 @ 01:30 PM - 02:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Alireza Marandi, Caltech

    Talk Title: Integrated Nonlinear Photonics: New Opportunities in the Nanometer and Femtosecond Scales

    Series: Photonics Seminar

    Host: Electrical and Computer Engineering: Wade Hsu, Mercedeh Khajavikhan, Michelle Povinelli, Constantine Sideris, and Wei Wu

    More Info: https://usc.zoom.us/j/91808071892?pwd=VUwyK3NSNW5rSzVLQzFKSGdPc05yUT09

    Webcast: https://usc.zoom.us/j/91808071892?pwd=VUwyK3NSNW5rSzVLQzFKSGdPc05yUT09

    More Information: Photonics Seminar _Alireza Marandi 11-9-21.pdf

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

    WebCast Link: https://usc.zoom.us/j/91808071892?pwd=VUwyK3NSNW5rSzVLQzFKSGdPc05yUT09

    Audiences: Everyone Is Invited

    Contact: Jennifer Ramos/Electrophysics

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  • ISE 651 - Epstein Seminar

    Tue, Nov 09, 2021 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Lin Xiao, Research Scientist, Facebook AI Research (FAIR)

    Talk Title: Fast Convergence of Exact Policy Gradient Methods

    Host: Dr. Meisam Razaviyayn

    More Information: November 9, 2021.pdf

    Location: Zoom/Online

    Audiences: Everyone Is Invited

    Contact: Grace Owh

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

    Wed, Nov 10, 2021 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Bardh Hoxha, Toyota Research Institute of North America (TRINA) in Ann Arbor, Michigan

    Talk Title: Verification and Control for Autonomous Cyber-Physical Systems

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

    Abstract: As Cyber-Physical Systems are becoming more autonomous, there is an increasing need for methods that ensure safety and reliability. In this talk, we present requirements-based approaches that can be used for automated testing, monitoring, and control synthesis of CPS. The methods utilize ideas from three important areas in CPS research: formal methods, machine learning, and control theory. We illustrate our methods on problems from the automotive industry.


    Biography: Bardh Hoxha is Senior Principal Scientist at Toyota Research Institute of North America (TRINA) in Ann Arbor, Michigan. His research interests include the development of practical testing and verification methods for autonomous Cyber-Physical Systems (CPS). His research draws from areas such as formal methods, logics, control theory and machine learning. Bardh has published over three dozen papers on these methods to top level journals and conferences. Previously, Bardh was an assistant professor in the Computer Science Department at Southern Illinois University. Prior to that, he completed his PhD in Computer Science at Arizona State University, where he received the Outstanding CS PhD student award. His thesis focused on simulation-based methods for testing CPS using formal requirements.

    Host: Pierluigi Nuzzo

    Webcast: https://usc.zoom.us/webinar/register/WN_p5OEJlPxQlakO4hqovuGEQ

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

    WebCast Link: https://usc.zoom.us/webinar/register/WN_p5OEJlPxQlakO4hqovuGEQ

    Audiences: Everyone Is Invited

    Contact: Talyia White

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  • AME Seminar

    Wed, Nov 10, 2021 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dimitri Papamoschou, UC Irvine

    Talk Title: Development of a Linear Surface-Based Model for the Jet Noise Source

    Abstract: The seminar will discuss an effort to formulate an elementary physical model for the jet noise source that can be used for practical prediction of aircraft noise. Although the present analysis is confined to a round single-stream jet, the basic principles can be extended to more complex configurations. The model is defined on a radiator surface at the rotational/irrotational boundary of the jet on which the footprint of the vortical eddies, including their convective speed, is captured. The models building block at a given frequency is a linear pressure event with random origin and random helical mode. The probability density function for the event's axial origin is derived from the statistics of coherent structures in shear layers. The distribution for the helical mode is currently empirical and driven by the need to match the polar directivity of sound emission in the far field. The generic form of the event is a self-similar wavepacket with convective speed based on the mean centerline velocity and shape parameters determined by least-squares matching of the far-field sound pressure level at a wide range of frequencies and polar angles. Initial results indicate that the model reproduces, in a qualitative sense, key statistics of the jet acoustic field, including the near-field space-time correlation, the broadening of the far-field spectral density with increasing polar angle from the jet axis, and the coherence between the near and far fields. For the latter, the analysis indicates that the rapid decline in the coherence with increasing polar angle is primarily due to the randomness of the event's axial origin.

    Biography: Dimitri Papamoschou is a professor of mechanical and aerospace engineering at University of California, Irvine (UCI). He received his PhD in Aeronautics at Caltech. His research interests include compressible turbulence, jet and fan aeroacoustics, and advanced noise source imaging methods. In jet aeroacoustics, he has shown the potential for noise reduction by asymmetric distortion of the jet velocity field, a concept that has led to several patents. He has also developed low-cost predictive methods for this type of noise reduction based on a special formulation of the acoustic analogy. At UCI he has served in various administrative roles, including department chair, associate dean, and interim dean. He is a Fellow of the American Institute of Aeronautics and Astronautics (AIAA) and recipient of the 2017 AIAA Aeroacoustics Award. He serves as an associate editor of the AIAA Journal.

    Host: AME Department

    More Info: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09

    Webcast: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09

    Location: Seaver Science Library (SSL) - 202

    WebCast Link: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09

    Audiences: Everyone Is Invited

    Contact: Tessa Yao

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  • Astani Civil and Environmental Engineering Seminar

    Thu, Nov 11, 2021 @ 11:00 AM - 12:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Honorable Robert L Sumwalt, Former Chairman, National Transportation Safety Board

    Talk Title: From Design to Disaster

    Abstract: Please see attached abstract, bio and a photo.

    Host: Dr. Najmedin Meshkati

    Webcast: Zoom: https://usc.zoom.us/j/996-8004-9945 Meeting ID:99680049945 Passcode: 905716

    More Information: Hon R. Sumwalt_abstract-bio-photo.pdf

    Location: Zoom Meeting

    WebCast Link: Zoom: https://usc.zoom.us/j/996-8004-9945 Meeting ID:99680049945 Passcode: 905716

    Audiences: Everyone Is Invited

    Contact: Evangeline Reyes

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

    Thu, Nov 11, 2021 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Inigo Incer, University of California, Berkeley

    Talk Title: The Algebra of Contracts

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

    Abstract: Contract-based design has been proposed as a formal design methodology to support compositional design in industry. Assume-guarantee (AG) contracts are formal specifications consisting of two trace properties: (i) assumptions made on the environment and (ii) responsibilities imposed on the object under specification when the environment behaves according to the contract's assumptions. In this talk, we will first discuss all algebraic operations known on AG contracts, and the applications of these operations in engineering design. As there are many formal design attributes, such as secure information flow, that cannot be expressed with trace properties or AG contracts, we will then discuss the theory of hypercontracts, which enables us to carry out assume-guarantee reasoning in complex systems using arbitrary hyperproperties.

    Biography: Inigo Incer is a doctoral candidate at UC Berkeley advised by Alberto Sangiovanni-Vincentelli. He is interested in all aspects of cyber-physical systems, emphasizing AI and formal methods that support their compositional design and analysis. Before pursuing a PhD, Inigo was an IC designer in Austin. His work has been supported by a UC Berkeley Chancellor's Fellowship and by NSF and DARPA grants.

    Host: Pierluigi Nuzzo

    Webcast: https://usc.zoom.us/webinar/register/WN_p5OEJlPxQlakO4hqovuGEQ

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

    WebCast Link: https://usc.zoom.us/webinar/register/WN_p5OEJlPxQlakO4hqovuGEQ

    Audiences: Everyone Is Invited

    Contact: Talyia White

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  • CS Colloquium: Jerry Mendel (USC) - Explainable Ai (XAI) for Rule-Based Fuzzy Systems

    Thu, Nov 11, 2021 @ 03:30 PM - 04:50 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Jerry Mendel, Emeritus Professor of Electrical Engineering, University of Southern California

    Talk Title: Explainable Ai (XAI) for Rule-Based Fuzzy Systems

    Series: Computer Science Colloquium

    Abstract: There is a sentiment in the fuzzy community that fuzzy rules would be of great value in XAI because such rules use words (which are modeled as fuzzy sets) and so they lend themselves naturally to XAI. This talk challenges that sentiment, in a constructive way. It explains why it is not valid to explain the output of Mamdani or TSK fuzzy systems using IF-THEN rules, but that it is valid to explain the output of such fuzzy systems as an association of the antecedents of a small subset of the original larger set of rules, using a phrase such as "These linguistic antecedents are symptomatic of this output". It also describes a novel multi-step approach to obtain such a small subset of rules for fuzzy systems, how Linguistic Approximation can be used to express the antecedent membership functions (the symptoms) linguistically, and a method for estimating the quality of linguistic explanations.

    Register in advance for this webinar at:
    https://usc.zoom.us/webinar/register/WN_IgXrJer8SMOaS5VdwMdRFQ

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

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Jerry Mendel received the Ph.D. degree in electrical engineering from the Polytechnic Institute of Brooklyn, Brooklyn, NY. Currently, he is (since Jan. 2018) Emeritus Professor of Electrical Engineering at the University of Southern California in Los Angeles. He has published close to 600 technical papers and is author and/or co-author of 12 books. He is a Life Fellow of the IEEE, a Distinguished Member of the IEEE Control Systems Society, and a Fellow of the International Fuzzy Systems Association. He was President of the IEEE Control Systems Society in 1986, a member of the Administrative Committee of the IEEE Computational Intelligence Society for nine years, and Chairman of its Fuzzy Systems Technical Committee and the Computing With Words Task Force of that Technical Committee. Among his awards are four IEEE Transactions best paper awards, a 1984 IEEE Centennial Medal, an IEEE Third Millenium Medal, and a Fuzzy Systems Pioneer Award from the IEEE Computational Intelligence Society. According to Google Scholar (as of Sept. 9, 2021) he has 58,428 citations, an h-index of 97 and an i10-index of 310. His present research interests include: type-2 fuzzy logic systems and XAI for rule-based systems.


    Host: Mukund Raghothaman

    Webcast: https://usc.zoom.us/webinar/register/WN_IgXrJer8SMOaS5VdwMdRFQ

    Location: Online Zoom Webinar

    WebCast Link: https://usc.zoom.us/webinar/register/WN_IgXrJer8SMOaS5VdwMdRFQ

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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  • Advanced Manufacturing Seminar

    Fri, Nov 12, 2021 @ 11:00 AM - 12:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Hilmar Koerner, Air Force Research Laboratory

    Talk Title: Disruptive Technologies in Support of Agile Processes for Air Force Applications

    Abstract: Increased demand and competition require novel approaches in composite manufacturing. This includes the systematic use of machine learning and artificial intelligence tools and disruptive technologies in materials discovery, process monitoring and performance evaluation of composites. This presentation will cover examples from the Functional and Structural Materials Division of the Materials & Manufacturing Directorate of the Air Force Research Laboratory with a focus on additive manufacturing of polymer matrix composites.


    Biography: Dr. Hilmar Koerner is a research lead at the Composites Branch, Structural Materials Division, Materials and Manufacturing Directorate, Air Force Research Laboratory, Wright-Patterson Air Force Base, Dayton, Ohio. He leads a research team solving current challenges in polymer matrix composites, materials and processes, with focus on physics-based understanding of composite processing and materials discovery in high temperature thermosetting polymers. His research has made major impact in the field of high temperature polymer matrix composites for additive manufacturing. His expertise is in real-time measurements using advanced synchrotron sources of polymeric systems under highly non-equilibrium conditions.


    Host: Center for Advanced Manufacturing

    More Info: Zoom link (no registration needed): https://usc.zoom.us/j/94568980820?pwd=RzhSUFlZbXE5MWVKdGF3akZPc0Zidz09

    Audiences: Everyone Is Invited

    Contact: Tessa Yao

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  • CAIS Seminar: Erika Van Buren (First Place for Youth) - Leveraging Data Science to Individualize Extended Foster Care Services: the Youth Success Roadmap Tool

    Tue, Nov 16, 2021 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Dr. Erika Van Buren, First Place for Youth

    Talk Title: Leveraging Data Science to Individualize Extended Foster Care Services: the Youth Success Roadmap Tool

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

    Abstract: In service to a deep commitment to learning and impact, First Place for Youth -“ a service and advocacy organization dedicated to supporting transition age foster youth to achieve self-sufficiency and independence -“ leveraged several years of in-program administrative and follow-up data on youth served to conduct a precision analytics modeling process, and to develop The Youth Success Roadmap Tool (YRT). The YRT is a practitioner-centric, web-based decision-support tool that is used by direct service providers and managers to support high precision programming in the development of action plans, selection of interventions, and decisions about transition needs and timelines with individual youth, with the ultimate goal of helping all young people leave program with life sustaining, living wage employment. This seminar will discuss the findings from the original modeling, the methods utilized to generate the modeling and tool, showcase and describe how the YRT is currently being utilized to increase application of effective, individualized services and the achievement of equitable results with youth.

    Register in advance for this webinar at:

    https://usc.zoom.us/webinar/register/WN_sDAlPRaaSBCWQvZct9ZuyQ

    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. Erika Van Buren serves as the Chief Innovation Officer for First Place for Youth, where she leads evaluation, learning, and national expansion strategies for scaling First Place's influence and impact in service to older foster youth across the country. She crafts and implements the internal and external evaluation agenda for the agency, works closely with program leadership to innovate and roll-out best and evidence-supported strategies to improve practice, and conducts on-going sector building and system-capacity development activities in support of First Place's mission. With over 20 years of experience, she has cultivated expertise in the areas of community mental health and child welfare program development and evaluation, quality improvement and performance management practices and was most recently named as a member of the 11th class of Annie E. Casey Foundation Leadership Fellows.


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

    Webcast: https://usc.zoom.us/webinar/register/WN_sDAlPRaaSBCWQvZct9ZuyQ

    Location: Online Zoom Webinar

    WebCast Link: https://usc.zoom.us/webinar/register/WN_sDAlPRaaSBCWQvZct9ZuyQ

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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  • Photonics Seminar Series

    Tue, Nov 16, 2021 @ 01:30 PM - 02:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Andrei Faraon, Caltech

    Talk Title: From Metasurfaces to Volumetric meta-optics for novel device functionalities

    Series: Photonics Seminar

    Host: Electrical and Computer Engineering: Wade Hsu, Mercedeh Khajavikhan, Michelle Povinelli, Constantine Sideris, and Wei Wu

    More Info: https://usc.zoom.us/j/91808071892?pwd=VUwyK3NSNW5rSzVLQzFKSGdPc05yUT09

    Webcast: https://usc.zoom.us/j/91808071892?pwd=VUwyK3NSNW5rSzVLQzFKSGdPc05yUT09

    More Information: Photonics Seminar _Andrei Faraon 11-16-21.pdf

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

    WebCast Link: https://usc.zoom.us/j/91808071892?pwd=VUwyK3NSNW5rSzVLQzFKSGdPc05yUT09

    Audiences: Everyone Is Invited

    Contact: Jennifer Ramos/Electrophysics

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  • ISE 651 - Epstein Seminar

    Tue, Nov 16, 2021 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Elise Miller-Hooks, Professor, Dept. of Civil, Environmental, and Infrastructure Engr, George Mason University

    Talk Title: Civil Infrastructure Systems Resilience: Models and Algorithms

    Host: Prof. Jim Moore

    More Information: November 16, 2021.pdf

    Location: Zoom/Online

    Audiences: Everyone Is Invited

    Contact: Grace Owh

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  • CS Colloquium: Laurel Riek (University of California, San Diego) - Robots in clinic and in the community: supporting wellbeing and health equity

    Tue, Nov 16, 2021 @ 03:30 PM - 04:50 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Laurel Riek, University of California, San Diego

    Talk Title: Robots in clinic and in the community: supporting wellbeing and health equity

    Series: Computer Science Colloquium

    Abstract: The pandemic exacerbated inequities faced by people with disabilities and healthcare workers -” both are at high risk of adverse physical and mental health outcomes. Robots alone are not going to fix these major societal problems; however, our work explores how we can design technology to lessen the burden of systemic ableism and healthcare system stress. I will discuss several of our recent projects in acute care and community health contexts. In acute care, we are building hospital-based robots to support the clinical workforce, to support item delivery, telemedicine, and decision support. In community health, we are creating interactive and adaptive systems that aim to extend the reach of cognitive neurorehabilitative therapies, provide respite to overburdened caregivers, and explore how technology might serve as a means for mediating positive interactions during hardship. We focus on building robots that can adaptively team with and longitudinally learn from people, and personalize and tailor their behavior.

    Register in advance for this webinar at:

    https://usc.zoom.us/webinar/register/WN_BxKfSOStS--ZoudxSavY7w

    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. Laurel Riek is a professor in Computer Science and Engineering at the University of California, San Diego, with a joint appointments in the Department of Emergency Medicine, and affiliated with the Contextual Robotics Institute and Design Lab. Dr. Riek directs the Healthcare Robotics Lab and leads research in human-robot teaming and health informatics, with a focus on autonomous robots that work proximately with people. Riek's current research interests include long term learning, robot perception, and personalization; with applications in acute care, neurorehabilitation, and home health. Dr. Riek received a Ph.D. in Computer Science from the University of Cambridge, and B.S. in Logic and Computation from Carnegie Mellon. Riek served as a Senior Artificial Intelligence Engineer and Roboticist at The MITRE Corporation from 2000-2008, working on learning and vision systems for robots, and held the Clare Boothe Luce chair in Computer Science and Engineering at the University of Notre Dame from 2011-2016. Dr. Riek has received the NSF CAREER Award, AFOSR Young Investigator Award, Qualcomm Research Award, and was named one of ASEE's 20 Faculty Under 40. Dr. Riek is the HRI 2023 General Co-Chair and served as the Program Co-Chair for HRI 2020, and serves on the editorial boards of T-RO and THRI.


    Host: Stefanos Nikolaidis

    Webcast: https://usc.zoom.us/webinar/register/WN_BxKfSOStS--ZoudxSavY7w

    Location: Online - Zoom Webinar

    WebCast Link: https://usc.zoom.us/webinar/register/WN_BxKfSOStS--ZoudxSavY7w

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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  • Kanso Lab seminar

    Tue, Nov 16, 2021 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Ramiro Godoy-Diana and Benjamin Thiria, PMMH lab at ESPCI Paris

    Talk Title: Fish and Fish-Like Swimming Interactions

    Abstract: The interaction between two neighboring swimmers forms the basis of the collective dynamics observed in a school of fish in nature. We will discuss different aspects of our recent work on swimmer-to-swimmer interactions, in which we have designed experiments with real fish or with simple robotic models, as well as numerical simulations, to examine the issues of swimmer synchronization, pattern formation, and energy expenditure, examining the most basic interactions between a pair of neighboring swimmers.

    Biography: TBD

    Host: Prof. Eva Kanso

    More Info: https://usc.zoom.us/j/92868857794

    Webcast: https://usc.zoom.us/j/92868857794

    Location: Olin Hall of Engineering (OHE) - 406

    WebCast Link: https://usc.zoom.us/j/92868857794

    Audiences: Everyone Is Invited

    Contact: Tessa Yao

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  • Jian Pei (Simon Fraser University) - Exact, Concise, and Consistent Data Driven Interpretation

    Tue, Nov 16, 2021 @ 03:30 PM - 04:30 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Jian Pei, Simon Fraser University

    Talk Title: Exact, Concise, and Consistent Data Driven Interpretation

    Abstract: Interpretability and explainability are at the core in our pursuit of new knowledge. At the same time, interpretation in data analytics and data mining is challenging in many ways, such as the complexity of models to be interpreted, the difficulty in knowledge elicitation, the expectation of embodying interpretation, and the need of many kinds of knowledge. In this talk, I will present our systematic research on exact, concise, and consistent data driven interpretation for database and data mining tasks. I will illustrate our principles and techniques using various application examples, including skyline queries (aka pareto optima) in databases, semantic OLAP in business intelligence, piece-wise linear neural networks in classification, and KS-tests in statistics. I will also discuss the promises and challenges of data driven interpretation for future work.

    Biography: Jian Pei is a Professor in the School of Computing Science at Simon Fraser University. His research focuses on data science, big data, data mining, database systems, and information retrieval. His expertise is in developing effective and efficient data analysis techniques for novel data intensive applications, and transferring his research results to industry products and business practice. He is recognized as a Fellow of the Royal Society of Canada (Canada's national academy), the Canadian Academy of Engineering, ACM, and IEEE. Since 2000, he has published one textbook, two monographs and over 300 research papers in refereed journals and conferences, which have been cited extensively by others. He was the editor-in-chief of the IEEE Transactions of Knowledge and Data Engineering (TKDE) in 2013-16, the chair of ACM SIGKDD in 2017-2021. He received a few prestigious awards, including the 2017 ACM SIGKDD Innovation Award, the 2015 ACM SIGKDD Service Award, the 2014 IEEE ICDM Research Contributions Award, the British Columbia Innovation Council 2005 Young Innovator Award, an IBM Faculty Award, a KDD Best Application Paper Award, and an ICDE Influential Paper Award.

    Host: Ellis Horowitz

    Location: Ronald Tutor Hall of Engineering (RTH) - 105

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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  • Jian Pei (Simon Fraser University) - Defining One Unified CS through Many Diversified Paths

    Wed, Nov 17, 2021 @ 09:00 AM - 09:45 AM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Jian Pei, Simon Fraser University

    Talk Title: Defining One Unified CS through Many Diversified Paths

    Abstract: Computer science broadly construed becomes a new dimension disruptive in higher education and research. Computer science departments face grand opportunities and challenges. Most importantly, a responsible computer science department should obligatorily take the lead to establish a university-wise unified computer science identity, including strategies, workforces, culture, and impact, and leverage and extend the rich leadership, advantages, and resources of the university. We need to ensure that the unified CS identity best contributes to building an academic learning and research environment of inclusiveness, diversity, and equity. Defining one unified CS as a new dimension in educational programs and research initiatives has to embrace many diversified paths and inclusively collaborate with many units and resources on campus and beyond. In this talk, I will share my ideas about the strategies, organization, student experience, outreach, community building, recruitment and retention, and working plan to evolve from an established leading CS department today into a powerful engine of new CS era tomorrow.

    Biography: Jian Pei is a Professor in the School of Computing Science at Simon Fraser University. His research focuses on data science, big data, data mining, database systems, and information retrieval. His expertise is in developing effective and efficient data analysis techniques for novel data intensive applications, and transferring his research results to industry products and business practice. He is recognized as a Fellow of the Royal Society of Canada (Canada's national academy), the Canadian Academy of Engineering, ACM, and IEEE. Since 2000, he has published one textbook, two monographs and over 300 research papers in refereed journals and conferences, which have been cited extensively by others. He was the editor-in-chief of the IEEE Transactions of Knowledge and Data Engineering (TKDE) in 2013-16, the chair of ACM SIGKDD in 2017-2021. He received a few prestigious awards, including the 2017 ACM SIGKDD Innovation Award, the 2015 ACM SIGKDD Service Award, the 2014 IEEE ICDM Research Contributions Award, the British Columbia Innovation Council 2005 Young Innovator Award, an IBM Faculty Award, a KDD Best Application Paper Award, and an ICDE Influential Paper Award.

    Host: Ellis Horowitz

    Location: Ronald Tutor Hall of Engineering (RTH) - 105

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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

    Wed, Nov 17, 2021 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Erika Abraham, RWTH Aachen University, Germany

    Talk Title: Analysing Hybrid Systems with HyPro

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

    Abstract: Hybrid systems are systems with mixed discrete-continuous behaviour, such as automotive systems or digitally controlled physical or chemical plants. For their analysis we are interested in solving the reachability problem, i.e. checking whether a hybrid system (model) can reach any "usafe" state during its execution. Though this problem is in general undecidable, there are different techniques that are either applicable to certain types of systems only or compute conservative approximations. In this talk we discuss available approaches with the focus on techniques implemented in our HyPro tool.

    Biography: Erika Abraham graduated at the Christian-Albrechts-University Kiel (Germany), and received her PhD from the University of Leiden (The Netherlands) for her work on the development and application of deductive proof systems for concurrent programs. Then she moved to the Albert-Ludwigs-University Freiburg (Germany), where she started to work on the development and application of SAT and SMT solvers. Since 2008 she is professor at RWTH Aachen University (Germany), with main research focus on SMT solving for real and integer arithmetic, and formal methods for probabilistic and hybrid systems.


    Host: Pierluigi Nuzzo

    Webcast: https://usc.zoom.us/webinar/register/WN_p5OEJlPxQlakO4hqovuGEQ

    Location: Online

    WebCast Link: https://usc.zoom.us/webinar/register/WN_p5OEJlPxQlakO4hqovuGEQ

    Audiences: Everyone Is Invited

    Contact: Talyia White

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  • AME Seminar

    Wed, Nov 17, 2021 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Paul Kruger, Professor and Chair, Department of Mechanical Engineering, SMU

    Talk Title: Additives in Extrusion-Based Additive Manufacturing

    Abstract: Material additives in additive manufacturing (AM) can serve a variety of functions from improving the manufacturing process to adjusting material properties in the final build. This talk will discuss several uses of additives in extrusion-based additive manufacturing. The first focuses on using carbon-black-based additives in AM for silicones. Silicones have a range of desirable properties (durability, large elongation, bio-compatibility, etc.) that make them appealing for AM, but because they are thermosets, additional complexity is required to use them in AM, including in-situ curing of the material. In this work, carbon-black additives are shown to improve the print quality of silicone parts with UV-curing due to reducing disturbance of material deposition from electro-static forces, even though the concentration is too low to promote material conductivity. Carbon black is also shown to be an effective radiation absorbing agent, allowing for material heating via an infrared laser in printing of thermally-cured silicones.

    The second considers metallic micro-spheres as additives to promote electrical conductivity at sufficient concentrations to create printable electrically conductive polymer composites (ECPCs). ECPCs are useful for providing electrical connections, resistors, or other electrical functionality in printed parts. But for high conductivity, high concentrations of particles are required, making extrusion of the composite material difficult. Investigation of the rheology of these materials will be presented, using non-Newtonian silicones as a surrogate for the molten polymers during printing. The results show that the composite materials behave like power-law materials with a strong dependence on the particle concentration and the ratio of the diameter of the extrusion tube/nozzle to the mean particle diameter. For particle diameter decreasing toward 1, the flow consistency index (effective viscosity) decreases and then sharply increases as particles begin to jam within the tube. A semi-empirical model reproducing these effects will be presented.

    Stay after the seminar for a brief overview of graduate programs in Mechanical Engineering at SMU. Learn about research opportunities and unique degree programs including MS in Manufacturing Management and the direct admission PhD program.

    Biography: Paul Krueger received his B.S. in Mechanical Engineering in 1997 from the University of California at Berkeley. He received his M.S. in Aeronautics in 1998 and his Ph.D. in Aeronautics in 2001, both from the California Institute of Technology (Caltech). In 2002 he joined the Mechanical Engineering Department at Southern Methodist University (Dallas, TX) where he is currently a Professor and department chair. He is a recipient of the Rolf D. Buhler Memorial Award in Aeronautics, the Richard Bruce Chapman Memorial Award for distinguished research in Hydrodynamics, the Faculty Early Career Development (CAREER) Award from the National Science Foundation (2004), and the Ford Senior Research Fellowship from SMU (2012). His research interests include unsteady hydrodynamics and aerodynamics, vortex dynamics, bio-fluid mechanics, bio-morphic propulsion, fluid-boundary and fluid-particle interactions, and fluid processes in additive manufacturing.

    Host: AME Department

    More Info: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09

    Webcast: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09

    Location: Seaver Science Library (SSL) - 202

    WebCast Link: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09

    Audiences: Everyone Is Invited

    Contact: Tessa Yao

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  • NL Seminar-How AI-Driven Augmented Intelligence Transforms Cognitive Security and Nonproliferation

    Thu, Nov 18, 2021 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Svitlana Volkova, Pacific Northwest National Lab

    Talk Title: How AI-Driven Augmented Intelligence Transforms Cognitive Security and Nonproliferation

    Series: NL Seminar

    Abstract: REMINDER: Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you're highly encouraged to use your USC account to sign into Zoom. If you're an outside visitor, please inform nlg DASH seminar DASH host AT isi.edu beforehand so we'll be aware of your attendance and let you in.

    In this talk I will present several examples of how AI models drive augmented intelligence solutions to transform national security mission spaces focusing on cognitive security and nonproliferation. I will start with cognitive security and discuss deep learning and natural language processing models to detect, characterize, and defend against influence operations, misinformation and disinformation campaigns. Specifically, models capable of detecting information micro narratives, understanding audiences, characterizing the dynamics of the information environment, and discovering causes and effects to explain why some narratives spread and some do not. I will demo our WatchOwl analytics developed to assist decision makers with real time situational awareness, track policy compliance and characterize the information environment during COVID 19 infodemic.

    Next, I will present a suite of AI powered analytics for nonproliferation developed to detect, anticipate, and reason about proliferation expertise and capability evaluation globally by learning from massive scale unstructured dynamic real-world data. I will showcase our augmented intelligence tools for expertise search and describe how to go beyond descriptive analytics towards predictive and prescriptive intelligence. Predictive models leverage graph neural networks to anticipate future collaboration patterns, authorship behavior, and capability evolution from dynamic heterogenous graphs. Prescriptive analysis uses ensemble models for causal discovery and inference to enable counterfactual reasoning about expertise and capability development. Our AI-driven augmented intelligence aims not only to provide deeper understanding of how publicly available data could be used to detect, monitor, forecast, and potentially prevent proliferation but also discover real world examples of patterns and behavior to facilitate the investigation of potentially illicit proliferation activity.

    Biography: Dr. Svitlana Volkova is a Chief Scientist in Decision Intelligence and Analytics in the National Security Directorate of PNNL, where she is leading the labs internal Mega AI investment focusing on developing and deploying massive scale foundation AI models for science and security mission areas. Since joining PNNL in October 2015, Dr. Volkova was responsible for over 10 Million in direct sales and has served as Principal Investigator or Project Manager on more than ten internally and externally funded projects, including two DARPA and two NNSA projects focusing on advancing various aspect of Artificial Intelligence AI such as natural language processing, machine learning, deep learning, AI test and evaluation, and causal discovery and inference.

    Svitlana has authored more than 70 peer previewed conference and journal publications. She serves as senior PC member and area chair for top tier AI conferences and journals including AAAI, WWW, NeurPS, ACL, EMNLP, NAACL, ICWSM, Nature Scientific Reports, PNAS and Science Advances. In 2016, she received the prestigious National Security Directorate Author of the Year award for her outstanding number of top-tier publications in AI.

    In 2019, Dr. Volkova received the Ronald L. Brodzinski Early Career Exceptional Achievement Award for her leadership and scientific contribution to the fields of computational linguistics and computational social science. She received her PhD in Computer Science from Johns Hopkins University where she was affiliated with the Center for Language and Speech Processing and the Human Language Technology Center of Excellence.

    Host: Jon May and Thamme Gowda

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

    Webcast: https://www.youtube.com/watch?v=INmAXBXucnM

    Location: Information Science Institute (ISI) - Virtual Only

    WebCast Link: https://www.youtube.com/watch?v=INmAXBXucnM

    Audiences: Everyone Is Invited

    Contact: Pete Zamar

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  • CS Colloquium: Luis Garcia (USC ISI) - Use What You Know: Leveraging Semantics to Trust Learning-enabled Cyber-physical Systems

    Thu, Nov 18, 2021 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Luis Garcia, USC

    Talk Title: Use What You Know: Leveraging Semantics to Trust Learning-enabled Cyber-physical Systems

    Abstract: The integration of autonomous cyber-physical systems (CPS) in society that interface with humans necessitates assurances for safety, security, and privacy. Traditional CPS research thrusts in this space have typically focused on closed-loop, deterministic models with relatively low-dimensional physics. With the artificial intelligence renaissance, deep learning models have enabled the utility of large amounts of data stemming from heterogeneous, distributed, and cyber-physical Internet-of-Things (IoT) networks. We are witnessing the emergence of performant cyber-physical systems whose interactions are poorly understood and rapidly evolving despite widespread adoption. My recent research explores how a semantic understanding of a deep learning model's environment can be leveraged to not only provide guarantees but also to enhance the reasoning power of a deep learning model. Neural-symbolic approaches that combine human logic with deep learning lie at the frontier of human-machine teaming in distributed and heterogenous IoT environments. My research aims to answer the following questions: 1) How can we design neural-symbolic frameworks that are semantically conscious of their subsuming cyber-physical systems? 2) In distributed and heterogeneous IoT environments enabled with such neural-symbolic frameworks, what are the correct programming abstractions that need to be exposed to developers? 3) How can we defend against collateral safety, security, and privacy threats that will subsequently be exposed by semantically aware, sensor-rich, adaptive, and distributed heterogeneous IoT environments? This talk will provide an overview of my research with an emphasis on the latter question of safety, security, and privacy threats in this space.

    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Join Zoom Meeting
    https://usc.zoom.us/j/99126118128?pwd=YytHUzJzSWxObVdpOFphdG9KVDVvZz09

    Meeting ID: 991 2611 8128

    Biography: Luis Garcia joined USC ISI's Networking and Cybersecurity Division as a Research Computer Scientists in June 2020. He was previously a Postdoctoral Scholar in the Networked and Embedded Systems Laboratory (NESL) in the University of California, Los Angeles (UCLA) Electrical and Computer Engineering Department since 2018. His research interests include the safety and security of learning-enabled cyber-physical systems, malware analysis and reverse engineering, industrial control system security and verification, as well as broad interests in novel applications of machine learning. He obtained his Ph.D. in Computer Engineering with a Cyber Security track working on the safety and security of cyber-physical industrial control systems at Rutgers University in 2018.

    Host: Greg Ver Steeg

    Audiences: Everyone Is Invited

    Contact: Cherie Carter

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  • Advanced Manufacturing Seminar

    Fri, Nov 19, 2021 @ 10:00 AM - 11:30 AM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Michael C. McAlpine, University of Minnesota

    Talk Title: 3D Printing Active Electronic & Optoelectronic Devices

    Abstract: The ability to three-dimensionally pattern semiconducting electronic and optoelectronic materials could provide a transformative approach to creating active electronic devices without the need for a cleanroom or conventional microfabrication facilities. This could enable the generation of active electronics on-the-fly, using only source inks and a portable 3D printer to realize electronics anywhere, anytime, including directly on the body. Indeed, interfacing active devices with biology in 3D could impact a variety of fields, including
    biomedical devices, regenerative biomedicines, bioelectronics, smart prosthetics, and human-machine interfaces. Developing the ability to 3D print various classes of materials possessing distinct properties will enable the freeform generation of active electronics in unique functional, interwoven architectures. Yet,
    achieving seamless integration of these diverse materials via 3D printing is a significant challenge which requires overcoming discrepancies in material properties in addition to ensuring that all of the materials are compatible with the 3D printing process. We will present a strategy for three-dimensionally integrating diverse classes of materials using a custom-built 3D printer to fully create fully 3D printed device components built around active electronics. As a proof of concept, we have 3D printed quantum dot-based light-emitting diodes (QD-LEDs), polymer-based photodiodes on curvilinear surfaces, and hybrid devices over large scales with high yield. These results represent a critical step toward the 3D printing of high performance, active electronic materials and devices.

    Biography: Michael C. McAlpine is the Kuhrmeyer Family Chair Professor of
    Mechanical Engineering at the University of Minnesota. He received a B.S. (2000) in Chemistry with honors from Brown University, and a Ph.D. (2006) in Chemistry from Harvard University. His current research is focused on 3D printing functional materials & devices for biomedical applications, with recent breakthroughs in 3D printed deformable sensors and 3D printed bionic eyes (one of National Geographics 12 Innovations that will Revolutionize the Future of Medicine). He has received several awards for this work, including the Presidential Early Career Award for Scientists and Engineers (PECASE), and the National Institutes of Health Directors New Innovator Award.

    Host: Center for Advanced Manufacturing

    More Info: Please register for this webinar at: https://usc.zoom.us/webinar/register/WN_NUYrOOwrSf63AxH9mp7Nvw

    Webcast: Please register for this webinar at: https://usc.zoom.us/webinar/register/WN_NUYrOOwrSf63AxH9mp7Nvw

    WebCast Link: Please register for this webinar at: https://usc.zoom.us/webinar/register/WN_NUYrOOwrSf63AxH9mp7Nvw

    Audiences: Everyone Is Invited

    Contact: Tessa Yao

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  • CILQ Internal Faculty Seminar

    Fri, Nov 19, 2021 @ 12:00 PM - 01:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Urbashi Mitra, Professor/USC

    Talk Title: Latent Privacy via a Secret Block Structure

    Abstract: Physical layer security approaches have often used the hardness of blind deconvolution to achieve privacy when transmitting signals over unknown wireless channels. Herein, we exploit the communication channel in a new way to provide a layer of privacy. In particular, we take advantage of the fact that it has been shown that exact recovery of block-sparse signals via linear measurements is achievable under conditions where classical compressed sensing would probably fail. We exploit this result to propose a novel private communication framework where secrecy is achieved by transmitting instances of an unidentifiable compressed sensing problem over a public channel. The legitimate receiver can attempt to overcome this ill-posedness by leveraging secret knowledge of a block structure that was used to encode the transmitter's message. We study the privacy guarantees of this communication protocol in a variety of cases with the goal of understanding how often we need to refresh the shared secret between transmitter and intended receiver. Additionally, we propose an algorithm for an eavesdropper to learn the block structure via the method of moments and highlight the privacy benefits of this framework through numerical experiments.

    Host: CILQ

    Webcast: https://usc.zoom.us/j/92417517950?pwd=WUkycy90cndVQko5R3RhQ1U3STBDdz09

    Location: via zoom

    WebCast Link: https://usc.zoom.us/j/92417517950?pwd=WUkycy90cndVQko5R3RhQ1U3STBDdz09

    Audiences: Everyone Is Invited

    Contact: Corine Wong

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  • Ming Hsieh Institute Seminar Series on Integrated Systems

    Fri, Nov 19, 2021 @ 02:00 PM - 03:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Mayank Raj, Senior Design Manager, Xilinx Inc.

    Talk Title: Design of a High-Speed Hybrid Integrated Si-Photonic Optical Link

    Host: Mike Chen, Hossein Hashemi, Manuel Monge, Constantine Sideris

    More Information: MHI IS Seminar - Mayank Raj_Flyer.pdf

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

    Audiences: Everyone Is Invited

    Contact: Jenny Lin

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  • ***NO ISE 651, Epstein Seminar - Thanksgiving Recess***

    Tue, Nov 23, 2021 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Audiences: Everyone Is Invited

    Contact: Grace Owh

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  • CS Colloquium: Tapomayukh Bhattacharjee (Cornell University) - Leveraging Physical Interactions to Enable Robotic Assistive Care

    Tue, Nov 23, 2021 @ 03:30 PM - 04:50 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Tapomayukh Bhattacharjee, Cornell University

    Talk Title: Leveraging Physical Interactions to Enable Robotic Assistive Care

    Series: Computer Science Colloquium

    Abstract: How do we build robots that can assist people with mobility limitations with activities of daily living? To successfully perform these activities, a robot needs to be able to physically interact with humans and objects in unstructured human environments. In the first part of my talk, I will show how a robot can use multimodal sense of touch such as force and thermal sensing to infer properties of these physical interactions using data-driven methods and physics-based models. In the second part of the talk, I will show how a robot can leverage these properties to perform one such activity of daily living- feeding. Successful robot-assisted feeding depends on reliable bite acquisition of hard-to-model deformable food items and easy bite transfer. Using insights from human studies, I will showcase algorithms and technologies that leverage multiple sensing modalities to perceive varied food item properties and determine successful strategies for bite acquisition and transfer. Using feedback from all the stakeholders, I will show how we built an autonomous robot-assisted feeding system that uses these algorithms and technologies and deployed it in the real world that fed real users with mobility limitations.


    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Tapomayukh "Tapo" Bhattacharjee is an Assistant Professor in the Department of Computer Science at Cornell University where he directs the EmPRISE Lab (https://emprise.cs.cornell.edu/). He completed his Ph. D. in Robotics from Georgia Institute of Technology and was an NIH Ruth L. Kirschstein NRSA postdoctoral research associate in Computer Science & Engineering at the University of Washington. He wants to enable robots to assist people with mobility limitations with tasks for daily living and he believes that allowing efficient and safe physical interactions between robots and their immediate environments is the key. His work spans the fields of human-robot interaction, haptic perception, and robot manipulation.


    Host: Stefanos Nikolaidis

    Location: Seeley Wintersmith Mudd Memorial Hall (of Philosophy) (MHP) - 101

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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  • Astani Civil and Environmental Engineering Seminar

    Tue, Nov 30, 2021 @ 11:00 AM - 12:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Adam Simpson, Ph.D. Candidate, Stanford University

    Talk Title: Predicting Initial Transformation of Food-Based Bio-Polymers and -Molecules During Food Disinfection

    Abstract: Foodborne pathogenic outbreaks still occur 100x more frequently than waterborne pathogenic outbreaks from municipal/community water supplies in the US, despite the passing of the Food Safety Modernization Act of 2011. To kill pathogens, food packaging facilities must treat fruits, vegetables, and meats with high dosages of chemical sanitizers-”most frequently free chlorine-”for ready-to-eat and triple washed foods. Food chemists and engineers have looked to water disinfection byproduct research to predict and measure contaminants (i.e., trihalomethanes, haloacetic acids and chlorates) formed in food disinfection washwaters as potential chemical exposures to consumers. However, my research demonstrates that this is fundamentally incorrect as the boundary conditions of food disinfection and water disinfection processes
    are incongruent. First, I will introduce current food disinfection processing techniques and conditions and compare with water disinfection to encourage a new way to predict initial transformation products formed during food disinfection. Second, I will demonstrate the formation of chlorotyrosines isolated inside of chlorine washed spinach and lettuce in comparison to volatile disinfection byproducts isolated in the washwater to prove where true toxic exposure risks are. Third, I will introduce a new class of food-based disinfection byproducts measured inside of chlorine treated vegetables, namely fatty acid chlorohydrins,and compare the cumulative toxic potencies of these chlorine treated vegetables to a poor-quality water at EPA regulated limits to demonstrate the relative magnitude of these exposures. I will end the seminar with a glance of my future research involving this uncharted field.


    Biography: Adam Simpson is a PhD candidate at Stanford University, in the Civil and Environmental Engineering Department advised by Professor William Mitch. His research involves using organic chemistry and complex analytical chemistry techniques to synthesize and isolate new classes of food-based disinfection
    byproducts that are toxic and affect most consumers. To advance his depth of knowledge and experience with postharvest crop treatment, he is also undergoing a stint at the United States Department of Agriculture-”Agricultural Research Service in Parlier, California, where he is also advised by the
    Environmental Chemist, Dr. Spencer Walse. His work has been supported by multiple fellowships including a Stanford Graduate Fellowship, a National Science Foundation Graduate Research Fellowship, and a Diversifying Academia, Recruiting Excellence Fellowship. He will receive his PhD in Civil and Environmental
    Engineering in May-2022 and received his M.S. degree in Civil and Environmental Engineering from Stanford University, and B.S. degree in Chemical Engineering from Carnegie Mellon University. Beingpassionate about diversifying academia, Adam is also a science communicator through his YouTube Channel, where he aims to humanize academia with a focus on Science, Technology, Engineering, and Math Education, while uplifting underrepresented voices. With an ambition of being a tenure-track assistant
    professor of Civil and Environmental Engineering-”he hopes to continue his work to make a more inclusive
    academia.

    Host: Dr. Daniel McCurry

    Webcast: https://usc.zoom.us/j/94682875854 Meeting ID: 946 8287 5854 Passcode: 090068

    Location: Michelson Center for Convergent Bioscience (MCB) - 102

    WebCast Link: https://usc.zoom.us/j/94682875854 Meeting ID: 946 8287 5854 Passcode: 090068

    Audiences: Everyone Is Invited

    Contact: Evangeline Reyes

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  • Photonics Seminar Series

    Tue, Nov 30, 2021 @ 01:30 PM - 02:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Juliet Gopinath, University of Colorado Boulder

    Talk Title: Nonlinear Integrated Optics and Microscopy

    Series: Photonics Seminar

    Host: Electrical and Computer Engineering: Wade Hsu, Mercedeh Khajavikhan, Michelle Povinelli, Constantine Sideris, and Wei Wu

    More Info: https://usc.zoom.us/j/91808071892?pwd=VUwyK3NSNW5rSzVLQzFKSGdPc05yUT09

    Webcast: https://usc.zoom.us/j/91808071892?pwd=VUwyK3NSNW5rSzVLQzFKSGdPc05yUT09

    More Information: Photonics Seminar _Julie Gopinath 11-30-21.pdf

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

    WebCast Link: https://usc.zoom.us/j/91808071892?pwd=VUwyK3NSNW5rSzVLQzFKSGdPc05yUT09

    Audiences: Everyone Is Invited

    Contact: Jennifer Ramos/Electrophysics

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  • ISE 651 - Epstein Seminar

    Tue, Nov 30, 2021 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Xunyu Zhou, Professor, Dept. of Industrial Engineering and Operations Research, Columbia

    Talk Title: Policy Evaluation, Policy Gradient, and Actor-Critic Learning in Continuous Time and Space: Theory and Algorithms

    Host: Dr. Renyuan Xu

    More Information: November 30, 2021.pdf

    Location: Zoom/Online

    Audiences: Everyone Is Invited

    Contact: Grace Owh

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  • CS Colloquium: Konstantinos Karydis (University of California, Riverside) - Online mobile robot motion planning under uncertainty in unknown environments

    Tue, Nov 30, 2021 @ 03:30 PM - 04:50 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Konstantinos Karydis, University of California, Riverside

    Talk Title: Online mobile robot motion planning under uncertainty in unknown environments

    Series: Computer Science Colloquium

    Abstract: Mobile robot motion planning under uncertainty is a challenging yet rewarding foundational robotics research problem with extensive applications across domains including intelligence, surveillance and reconnaissance (ISR), remote sensing, and precision agriculture. One important challenge is operation in unknown environments where planning decisions need to be made at run-time. In this talk we discuss recent results to address online motion planning in unknown environments. We consider two specific cases: 1) How to achieve resolution-complete field coverage considering the non-holonomic mobility constraints in commonly-used vehicles (e.g., wheeled robots) without prior information about the environment? 2) How to develop resilient, risk-aware and collision-inclusive planning algorithms to enable (collision-resilient) mobile robots to deliberately choose when to collide with locally-sensed obstacles to improve some motion planning metrics (e.g., total time to reach a goal).

    To this end, we have proposed a hierarchical, hex-decomposition-based coverage planning algorithm for unknown, obstacle-cluttered environments. The proposed approach ensures resolution-complete coverage, can be tuned to achieve fast exploration, and plans smooth paths for Dubins vehicles to follow at constant velocity in real-time. Our approach can successfully trade-off between coverage and exploration speed, and can outperform existing online coverage algorithms in terms of total covered area or exploration speed according to how it is tuned. Further, we have introduced new sampling- and search-based online collision-inclusive motion planning algorithms for impact-resilient robots, that can explicitly handle the risk of colliding with the environment and can switch between collision avoidance and collision exploitation. Central to the planners' capabilities is a novel joint optimization function that evaluates the effect of possible collisions using a reflection model.
    This way, the planner can make deliberate decisions to collide with the environment if such collision is expected to help the robot make progress toward its goal. To make the algorithm online, we present state expansion pruning techniques that can significantly reduce the search space while ensuring completeness.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Dr. Karydis is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of California, Riverside (UCR). Before joining UCR, he worked as a Post-Doctoral Researcher in Robotics in GRASP Lab, which is part of the Department of Mechanical Engineering and Applied Mechanics at the University of Pennsylvania (Penn). His work was supported by Dr. Vijay Kumar, Professor and Nemirovsky Family Dean of Penn Engineering. He completed his doctoral studies in the Department of Mechanical Engineering at the University of Delaware, under the guidance of Prof. Herbert Tanner and Prof.
    Ioannis Poulakakis.


    Host: Stefanos Nikolaidis

    Location: Seeley Wintersmith Mudd Memorial Hall (of Philosophy) (MHP) - 101

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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