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Conferences, Lectures, & Seminars
Events for November
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Six Sigma Black BeltTue, Nov 01, 2022 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Abstract: USC Viterbi School of Engineering's Six Sigma Black Belt for Process Improvement, offered in partnership with the Institute of Industrial and Systems Engineers, allows professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality. As a USC Six Sigma Black Belt, you will be equipped to support and champion a Six Sigma implementation in your organization. To earn the USC Six Sigma Black Belt Certificate, you will be required to pass the Institute of Industrial and Systems Engineer's Black belt exam (administered on the final day of the course).
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
Audiences: Registered Attendees
Contact: Corporate and Professional Programs
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Photonics Seminar - Aydogan Ozcan, Tuesday, November 1 at 1:30pm in EEB 248
Tue, Nov 01, 2022 @ 01:30 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Aydogan Ozcan, UCLA
Talk Title: Diffractive Optical Networks & Computational Imaging Without a Computer
Series: Photonics Seminar Series
Abstract: I will discuss diffractive optical networks designed by deep learning to all-optically implement various complex functions as the input light diffracts through spatially-engineered surfaces. These diffractive processors designed by deep learning have various applications, e.g., all-optical image analysis, feature detection, object classification, computational imaging and seeing through diffusers, also enabling task-specific camera designs and new optical components for spatial, spectral and temporal beam shaping and spatially-controlled wavelength division multiplexing. These deep learning-designed diffractive systems can broadly impact (1) all-optical statistical inference engines, (2) computational camera and microscope designs and (3) inverse design of optical systems that are task-specific. In this talk, I will give examples of each group, enabling transformative capabilities for various applications of interest in e.g., autonomous systems, defense/security, telecommunications as well as biomedical imaging and sensing.
Biography: Dr. Aydogan Ozcan is the Chancellor's Professor and the Volgenau Chair for Engineering Innovation at UCLA and an HHMI Professor with the Howard Hughes Medical Institute, leading the Bio- and Nano-Photonics Laboratory at UCLA School of Engineering and is also the Associate Director of the California NanoSystems Institute. Dr. Ozcan is elected Fellow of the National Academy of Inventors (NAI), holds>55 issued/granted patents, and is the author of one book and the co-author of >950 peer-reviewed publications in major scientific journals and conferences. Dr. Ozcan is the founder and a member of the Board of Directors of Lucendi Inc., Hana Diagnostics, Pictor Labs, as well as Holomic/Cellmic LLC, which was named a Technology Pioneer by The World Economic Forum in 2015. Dr. Ozcan is also a Fellow of the American Association for the Advancement of Science (AAAS), the International Photonics Society (SPIE), the Optical Society of America (OSA), the American Institute for Medical and Biological Engineering (AIMBE), the Institute of Electrical and Electronics Engineers (IEEE), the Royal Society of Chemistry (RSC), the American Physical Society (APS) and the Guggenheim Foundation, and has received major awards including the Presidential Early Career Award for Scientists and Engineers, International Commission for Optics (ICO) Prize, Joseph Fraunhofer Award & Robert M. Burley Prize (Optica), Biophotonics Technology Innovator Award (SPIE), Rahmi M. Koc Science Medal, International Photonics Society Early Career Achievement Award (SPIE), Army Young Investigator Award, NSF CAREER Award, NIH Director's New Innovator Award, Navy Young Investigator Award, IEEE Photonics Society Young Investigator Award and Distinguished Lecturer Award, National Geographic Emerging Explorer Award, National Academy of Engineering The Grainger Foundation Frontiers of Engineering Award and MIT's TR35 Award for his seminal contributions to computational imaging, sensing and diagnostics. Dr. Ozcan is also listed as a Highly Cited Researcher by Web of Science, Clarivate.
Host: Mercedeh Khajavikhan
More Information: Aydogan Ozcan Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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**No Epstein Institute - ISE 651 Seminar - Due to Rechtin Lecture on 11.3.22**
Tue, Nov 01, 2022 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Location: Ethel Percy Andrus Gerontology Center (GER) - GER 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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Hosting Outreach Events & Reporting Service/Outreach Hours
Tue, Nov 01, 2022 @ 05:00 PM - 06:30 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Join us for a workshop to learn about the requirements for hosting outreach events with minors and how to report service/outreach hours on EngageSC. A representative from the Office of Youth Protection & Programming will be joining us to give an overview of USC’s youth protection policy, requirements, and event registration process. Please ensure that you have access to EngageSC as an “Officer” before the meeting to access the “Service Hours” feature for your organization. For any questions related to service/outreach projects please contact Noe Mora at nmora@usc.edu for assistance.
Location: Online Event
Audiences: Everyone Is Invited
Contact: Noe Mora
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Six Sigma Black Belt
Wed, Nov 02, 2022 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Abstract: USC Viterbi School of Engineering's Six Sigma Black Belt for Process Improvement, offered in partnership with the Institute of Industrial and Systems Engineers, allows professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality. As a USC Six Sigma Black Belt, you will be equipped to support and champion a Six Sigma implementation in your organization. To earn the USC Six Sigma Black Belt Certificate, you will be required to pass the Institute of Industrial and Systems Engineer's Black belt exam (administered on the final day of the course).
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
Audiences: Registered Attendees
Contact: Corporate and Professional Programs
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Virtual seminar Causal Dependencies in Multivariate Time Series
Wed, Nov 02, 2022 @ 10:00 AM - 11:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Sunil Kumar Vuppala, Director, Data Science, Ericsson
Talk Title: Causal Dependencies in Multivariate Time Series
Abstract: The talk starts with a motivation for casual analysis. Correlation does not imply causation. Similarly, lack of correlation does not imply lack of causation. How can we detect causality in complex systems such as telecom networks? The talk covers 3Wh of Causality (What, why, where). It covers taxonomy of time series casual discovery, an overview of the methods and techniques such as Granger causality, Convergent Cross Mapping, information theoretic approaches, graphical approaches and ML approaches. How can we connect any observed event to possibly a set of specific causal events? Why do we need counterfactual interventions for causal intensity? The talk describes the relevance of causality in telecom domain and cover a few use cases in telecom such as Key Performance Indicator (KPI) degradation and outlier root cause analysis and hardware failures. The speaker will share sample results from simulated experiments. He will introduce a few active research topics in this space.
Biography: Dr. Sunil Kumar Vuppala is the Director -“ Data Science, Ericsson Global AI Accelerator (GAIA), Bangalore. Dr. Vuppala has 18 years of industrial and research experience in Machine learning, Deep learning, Analytics, Internet of Things, and Automation. Sunil worked in Oracle, Infosys R&D, and Philips Research before joining Ericsson. He is the inventor of 35+ patents (6 US granted and 30+ published), has published 30+ papers, and delivered 100+ guest lectures. Dr. Vuppuala is a senior member of ACM, IEEE, and a fellow of IETE and IEI. He is one of the Top 10 data scientists in India for 2019, recipient of Zinnov Technical Role Model in Emerging Technology award 2020, IEEE TEMS Engineering Manager of the Year 2020, and ACM distinguished speaker. Dr. Vuppula is an alumnus of premier institutes in India. He is a visiting faculty at Case Western Reserve University, USA.
Host: Urbashi Mitra
More Info: https://usc.zoom.us/j/94255391488 pwd=cGoyOVoxWnc3K1RTeVcvYjlWOEJPQT09 Meeting ID: 942 5539 1488 Passcode: 114454
Location: https://usc.zoom.us/j/94255391488 pwd=cGoyOVoxWnc3K1RTeVcvYjlWOEJPQT09 Meeting ID: 942 5539 1488
Audiences: Everyone Is Invited
Contact: Susan Wiedem
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AME Seminar
Wed, Nov 02, 2022 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Marco Panesi, University of Illinois Urbana-Champaign
Talk Title: Construction of Hydrodynamic Models for Nonequilibrium Flows: Application to Hypersonics
Abstract: The simulation of the aerothermal environment surrounding vehicles moving at hypersonic speed is a complex problem due to its multi-physics and multi-scale nature. Progress in accurately modeling these systems has been hindered by the lack of reliable physical models for the thermochemical and transport processes that dominate the dynamics of the flow. The most physically consistent description of nonequilibrium flows relies on the direct numerical solution of the kinetic equations for each internal state of the gas particles. However, for problems of interest, the exponentially large many degrees of freedom, and the wide range of spatial and temporal scales involved, make these equations unsolvable.
This talk outlines a new paradigm for constructing predictive modeling and simulation tools from a fundamental physics perspective, rejecting the empiricism that has prevented progress in modeling hypersonic flows for decades. Inspired by model reduction strategies developed in statistical physics, this work addresses the challenges of the combinatorial explosion of the possible configurations of the system,obtaining new governing equations by projecting the master equation onto a few lower-dimensional subspaces. The distribution function within each subspace is then reconstructed using the Maximum Entropy Principle, thus ensuring compliance with the Detailed Balance.
I will cover the critical aspects involved in model development: (1) using direct numerical simulationto study the fundamental physics; (2) derivation of a reduced-order set of equations that give an accurateand physical consistent description of the physics at a much-reduced computational cost: (3) Validationand uncertainty quantification.
Biography: Dr. Marco Panesi is currently a Professor in the Aerospace Engineering Department and director of the Center for Hypersonics and Entry System Studies (CHESS) at the University of Illinois at Urbana-Champaign. In 2009, he received a Ph.D. degree from the von Karman Institute for Fluid Dynamics. He completed a post-doc with the PECOS center, one of the five DOE-funded PSAAP centers, at Odens Institute. Prof. Panesi joined the faculty in the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign as an assistant professor in August 2012.
Prof. Panesi has won several awards, including the Vannevar Bush Faculty Fellowship (VBFF), the Young Investigator Program (YIP) award from AFOSR, and the Early Career Faculty award from NASA. He has won the Best Paper/Presentation Awards at AIAA conferences several times. In 2015, he received the Award on Physical Modelling at the Symposium on Aerothermodynamics for Space Vehicles (ESA) for his contribution to the fundamentals of Aerothermodynamics.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/98775609685?pwd=a2lSd01oY0o2KzA4VWphbGxjWk5Qdz09Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/98775609685?pwd=a2lSd01oY0o2KzA4VWphbGxjWk5Qdz09
Audiences: Everyone Is Invited
Contact: Tessa Yao
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Six Sigma Black Belt
Thu, Nov 03, 2022 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Abstract: USC Viterbi School of Engineering's Six Sigma Black Belt for Process Improvement, offered in partnership with the Institute of Industrial and Systems Engineers, allows professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality. As a USC Six Sigma Black Belt, you will be equipped to support and champion a Six Sigma implementation in your organization. To earn the USC Six Sigma Black Belt Certificate, you will be required to pass the Institute of Industrial and Systems Engineer's Black belt exam (administered on the final day of the course).
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
Audiences: Registered Attendees
Contact: Corporate and Professional Programs
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NL Seminar-Modular and Composable Transfer Learning
Thu, Nov 03, 2022 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Jonas Pfeiffer, Google
Talk Title: Modular and Composable Transfer Learning
Series: NL Seminar
Abstract: REMINDER
Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you are highly encouraged to use your USC account to sign into Zoom.
If you are an outside visitor, please inform us at nlg DASH seminar DASH host AT isi DOT edu beforehand so we will be aware of your attendance and let you in.
In person attendance will be permitted for USC ISI faculty, staff, students only. Open to the public virtually via the zoom link and online.
With pre-trained transformer-based models continuously increasing in size, there is a dire need for parameter-efficient and modular transfer learning strategies. In this talk, we will touch base on adapter-based fine-tuning, where instead of fine-tuning all weights of a model, small neural network components are introduced at every layer. While the pre-trained parameters are frozen, only the newly introduced adapter weights are fine-tuned, achieving an encapsulation of the down-stream task information in designated parts of the model. We will demonstrate that adapters are modular components which can be composed for improvements on a target task and how they can be used for out of distribution generalization on the example of zero shot cross-lingual transfer. Finally, we will discuss how adding modularity during pre training can mitigate catastrophic interference and consequently lift the curse of multilinguality.
Biography: Jonas Pfeiffer is a Research Scientist at Google Research. He is interested in modular representation learning in multi task, multilingual, and multi-modal contexts, and in low resource scenarios. He worked on his PhD at the Technical University of Darmstadt, was a visiting researcher at the New York University and a Research Scientist Intern at Meta Research. Jonas has received the IBM PhD Research Fellowship award for 2021/2022. He has given numerous invited talks at academia, industry and ML summer schools, and has co-organized multiple workshops on multilinguality and multimodality
Host: Jon May and Meryem M'hamdi
More Info: https://nlg.isi.edu/nl-seminar/
Webcast: https://www.youtube.com/watch?v=hrGOb4okvI0Location: Information Science Institute (ISI) - Virtual and ISI-Conf Rm#689
WebCast Link: https://www.youtube.com/watch?v=hrGOb4okvI0
Audiences: Everyone Is Invited
Contact: Pete Zamar
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2022 Ebherhardt Rechtin Keynote Lecture
Thu, Nov 03, 2022 @ 03:30 PM - 06:00 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Bill Jia, Senior VP of Engineering, Meta/Facebook
Talk Title: Latest AI Research at Meta and the Untold Technologies Behind AI
Abstract: In this talk, the latest AI research results and the applications at Meta will be discussed. We will show how these results can be used to improve our day-to-day life experiences. Further, we will disclose the untold foundational technologies which are the critical parts to enable all the AI research work - this includes the data centers, network, hardware and the software which are used to create and train the AI research models.
More Information: Rechtin Keynote Lecture_Flyer 2022.pdf
Location: Charlotte S. & Davre R. Davidson Continuing Education Conference Center (DCC) - Vineyard Room
Audiences: Everyone Is Invited
Contact: Grace Owh
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Six Sigma Black Belt
Fri, Nov 04, 2022 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Abstract: USC Viterbi School of Engineering's Six Sigma Black Belt for Process Improvement, offered in partnership with the Institute of Industrial and Systems Engineers, allows professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality. As a USC Six Sigma Black Belt, you will be equipped to support and champion a Six Sigma implementation in your organization. To earn the USC Six Sigma Black Belt Certificate, you will be required to pass the Institute of Industrial and Systems Engineer's Black belt exam (administered on the final day of the course).
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
Audiences: Registered Attendees
Contact: Corporate and Professional Programs
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MHI ISSS Seminar - Dr. Omeed Momeni, Friday, Nov. 4th at 2pm in EEB 132
Fri, Nov 04, 2022 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Omeed Momeni, University of California
Talk Title: Scalable Standing Wave Integrated Circuits for Reconfigurable Power Generation, Radiation and Beam Steering at mm-Wave and Terahertz Spectrum
Series: Integrated Systems
Abstract: The power generation of transistors declines as the operation frequency increases. At the same time, the
free space propagation loss increases, demanding more radiated power from the system. The loss of passive
elements in the circuit increases as well, making functions such as oscillation or radiation even more challenging. In
order to boost the limited power, multiple sources need to be coupled together in an array structure. However, the
significant loss of the coupling circuitry and phase shifters at mm-wave and terahertz frequencies hinders the
implementation of large and efficient radiator and phased arrays. Scalable standing wave array structures are
proposed based on efficient low loss coupling schemes in order to boost the power and operation bandwidth.
Furthermore, a practical approach is proposed to maximize Equivalent Isotropic Radiated Power (EIRP) of the
source by optimizing influential parameters of the radiation apparatus. Finally, we demonstrate a new phase shifting
method based on combining standing and traveling waves and show how it can achieve significantly higher
reconfigurability, phase shifting range and bandwidth. Using all these methods we present coupled-oscillators,
scalable radiator arrays, and reconfigurable phased arrays that can produce high resolution images and achieve
record beam steering range, tuning range, and output power at mm-wave and terahertz frequencies.
Biography: Dr. Omeed Momeni (S'04-M'12-SM'18) received the B.Sc. degree from Isfahan University of
Technology, Isfahan, Iran, the M.S. degree from University of Southern California, Los Angeles,
CA, and the Ph.D. degree from Cornell University, Ithaca, NY, all in Electrical Engineering, in
2002, 2006, and 2011, respectively. He joined the faculty of Electrical and Computer
Engineering Department at University of California, Davis in 2011 and is currently an
Associate Professor. He was a visiting professor in Electrical Engineering and Computer
Science Department at University of California, Irvine from 2011 to 2012. From 2004 to 2006,
he was with the National Aeronautics and Space Administration (NASA), Jet Propulsion Laboratory (JPL) as a RFIC
designer. His research interests include mm-wave and terahertz integrated circuits and systems.
Prof. Momeni serves as an Associate Editor for The IEEE Microwave and Wireless Components Letters (MWCL) since
2021, and a Technical Program Committee (TPC) member of Radio Frequency Integrated Circuits (RFIC) Symposium
since 2018. He has also served as a Distinguished Lecturer for Solid-State Circuits Society (SSCS) in 2020-22, an
Associate Editor of Transactions on Microwave Theory and Techniques (TMTT) in 2018-20, a Steering Committee
Member (2020) and Technical Program Review Committee Member (2017-20) of the International Microwave
Symposium (IMS), an organizing committee member of IEEE International Workshop on Design Automation for
Analog and Mixed-Signal Circuits in 2013, and the chair of the IEEE Ithaca GOLD section in 2008-11. Prof. Momeni is
the recipient of UC Davis Graduate Program Advising and Mentoring Award in 2022, National Science Foundation
CAREER award in 2015, the Professor of the Year 2014 by IEEE at UC Davis, the Best Ph.D. Thesis Award from the
Cornell ECE Department in 2011, the Outstanding Graduate Award from Association of Professors and Scholars of
Iranian Heritage (APSIH) in 2011, the Best Student Paper Award at the IEEE Workshop on Microwave Passive
Circuits and Filters in 2010, the Cornell University Jacob's fellowship in 2007 and the NASA-JPL fellowship in 2003.
Host: MHI - ISSS, Hashemi, Chen and Sideris
More Information: Abstract and Bio-Nov 4-Momeni.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Photonics Seminar - Galan Moody, Tuesday, November 8th at 3pm in MCB 101
Tue, Nov 08, 2022 @ 03:00 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Galan Moody, University of California Santa Barbara
Talk Title: Integrated Quantum Photonics Beyond Silicon
Abstract: Silicon-on-insulator has been an indispensable platform for classical and quantum photonics, but it is lacking in several aspects that are needed for the next generation of advanced quantum technologies. Beyond silicon, there is a spectrum of alternative crystalline materials-”such as compound semiconductors, lithium niobate, and 2D materials-”that have the potential to enable radically new device concepts and related quantum technologies. In this presentation, I will highlight my group's progress in developing several heterogeneous photonic platforms to address key challenges in quantum communications, networking, and distributed information processing. These include AlGaAs-on-insulator photonics for ultra-efficient entangled-pair generation, squeezing, and frequency-bin information processing; the integration of AlGaAs and 2D material single-photon sources with silicon photonics; and hybrid quantum dot devices with opto-electronic and opto-mechanical resonators for dynamic tuning and quantum transduction.
Biography: Professor Moody joined the Electrical and Computer Engineering Department at the University of California Santa Barbara in July 2019. Prior to moving to Santa Barbara, he was a Research Scientist (2015-2019) at the National Institute of Standards and Technology (NIST) in Boulder, Colorado, USA, a National Research Council postdoctoral fellow at NIST (2013-2015), and a postdoctoral associate at the University of Texas, Austin, USA (2013). He received his PhD Degree in Physics (2013) and his BSc Degree in Engineering Physics (2008) from the University of Colorado Boulder. He is a recipient of an Air Force Young Investigator Program award (2020) and an NSF CAREER award (2021) for research on integrated quantum photonic technologies. He serves as a thrust co-lead and on the executive committee for UCSB's Quantum Foundry (an NSF institute for quantum materials and related technologies), on the technical program committees for several conferences including CLEO, and on the editorial board for IOP's Journal of Physics: Photonics.
Host: Mercedeh Khajavikhan
Location: Michelson Center for Convergent Bioscience (MCB) - 101
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Epstein Institute - ISE 651 Seminar
Tue, Nov 08, 2022 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Jose Blanchet, Professor, Dept. of Management Science and Engineering, Stanford University
Talk Title: Optimal Transport and Distributionally Robust Optimization
Host: Dr. Renyuan Xu
More Information: November 8, 2022.pdf
Location: Online/Zoom
Audiences: Everyone Is Invited
Contact: Grace Owh
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MFD Seminar: "Bottom-Up Biology": Building Synthetic Cells
Tue, Nov 08, 2022 @ 04:00 PM - 05:20 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Professor Allen Liu, Associate Professor in Mechanical Engineering, Biomedical Engineering, and Biophysics, University of Michigan
Talk Title: "Bottom-Up Biology": Building Synthetic Cells
Series: MFD Distinguished Lecture Series
Abstract: "Biological membranes are involved in many cellular processes including cell migration, membrane trafficking, and cell signaling. A significant amount of work has elucidated the molecular machineries that regulate dynamic membrane-based processes. In parallel, there are growing interests in recent years in trying to understand how the mechanical state of the cells is utilized as a regulatory input to control cellular processes. My lab is broadly interested in studying the mechanochemical responses and force generation of biological systems, both in cells and in cell-like systems. In this talk, I will present two directions in building cell-like systems referred to as synthetic cells. In the first part of the talk, I will describe the self-organization of the reconstituted actin network, with crosslinker proteins and molecular motor myosin, in synthetic cells. Depending on the confinement size and concentrations of actin crosslinkers, distinct actomyosin patterns emerge in the form of asters and rings and could constrict the synthetic cell. In the second part of the talk, I will describe a general synthetic cell platform that makes use of encapsulation of mammalian cell-free expression reactions to reconstitute membrane proteins for generating membrane-active synthetic cells. I will share our work on building mechanosensitive synthetic cells and ongoing work on building synthetic neurons."
Biography: Allen Liu received a B.Sc. degree in Biochemistry (Honors) from the University of British Columbia, Vancouver, Canada, in 2001. He obtained his Ph.D. in Biophysics in 2007 from the University of California, Berkeley, and received his post-doctoral training at The Scripps Research Institute-La Jolla. He started his group in 2012, and he is currently an Associate Professor in Mechanical Engineering, Biomedical Engineering, and Biophysics at the University of Michigan. His current research interests lie in cellular mechanotransduction and uses tools from quantitative cell biology, synthetic biology, biophysics, and microfluidics. He is a recipient of the NIH Director's New Innovator Award, a Young Innovator by Cellular and Molecular Bioengineering (CMBE), a Rising Star from CMBE-BMES, and Future of Biophysics Burroughs Wellcome Fund Symposium speaker. He is a recipient of the Endeavour Executive Fellowship (Australia) and the Alexander von Humboldt Fellowship for Experienced Researcher (Germany).
Host: Professor Zeno, Mork Family Department of Chemical Engineering and Materials Science
More Information: Allen Liu Seminar Flyer 11.8.22.pdf
Location: James H. Zumberge Hall Of Science (ZHS) - 352
Audiences: Everyone Is Invited
Contact: Anthony Tritto
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CAIS Seminar: Swabha Swayamdipta (USC) - Contextualizing Bias in Hate Speech Detection through Annotator Perspectives
Wed, Nov 09, 2022 @ 02:00 AM - 03:00 PM
Computer Science
Conferences, Lectures, & Seminars
Speaker: Swabha Swayamdipta, University of Southern California
Talk Title: Contextualizing Bias in Hate Speech Detection through Annotator Perspectives
Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series
Abstract: In an increasingly online world, content moderation in social media has become immensely important. However, existing hate speech detection systems are riddled with racial biases introduced during annotation, which are reinforced and propagated by models trained on such data. In this talk, I will first present the inadequacies of current methods for debiasing hate speech detection. I will show how the subjectivity of this task design leads to debiasing failures. Next, I will focus on uncovering the origin of bias in toxic language detection. I will demonstrate how annotators' demographics and beliefs influence their toxicity ratings, and how ignoring such societal context can lead to biased outcomes. Overall, I will argue for the value of rethinking traditional the hate speech classification task, and the need for richer context in hate speech datasets.
Prof. Swayamdipta will give her talk in person at GFS 116 and we will also host the talk over Zoom.
Register in advance for this webinar at:
https://usc.zoom.us/webinar/register/WN_50yG4RHVTa-a6gKPUh7r3g
After registering, attendees will receive a confirmation email containing information about joining the webinar.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Swabha Swayamdipta is an Assistant Professor of Computer Science and a Gabilan Assistant Professor at the University of Southern California. Her research interests are in natural language processing and machine learning, with a primary interest in the estimation of dataset quality, the semi-automatic collection of impactful data, and evaluating how human biases affect dataset construction and model decisions. At USC, Swabha leads the Data, Interpretability, Language and Learning (DILL) Lab. She received her PhD from Carnegie Mellon University, and was then a postdoc at the Allen Institute for AI. Her work has received outstanding paper awards at ICML 2022 and NeurIPS 2021 as well as an honorable mention for the best overall paper at ACL 2020.
Host: USC Center for Artificial Intelligence in Society (CAIS)
Webcast: https://usc.zoom.us/webinar/register/WN_50yG4RHVTa-a6gKPUh7r3gLocation: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 116
WebCast Link: https://usc.zoom.us/webinar/register/WN_50yG4RHVTa-a6gKPUh7r3g
Audiences: Everyone Is Invited
Contact: Department of Computer Science
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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 09, 2022 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Quan Nguyen, Aerospace and Mechanical Engineering at the University of Southern California
Talk Title: Toward the Development of Highly Adaptive Legged Robots
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Deploying legged robots in real-world applications will require fast adaptation to unknown terrain and model uncertainty. Model uncertainty could come from unknown robot dynamics, external disturbances, interaction with other humans or robots, or unknown parameters of contact models or terrain properties. In this talk, I will first present our recent works on adaptive control and adaptive safety-critical control for legged locomotion adapting to substantial model uncertainty. In these results,
we focus on the application of legged robots walking rough terrain while carrying a heavy load. I will then talk about our solution on trajectory optimization that allows legged robots to adapt to a wide variety of challenging terrain. This talk will also discuss the combination of control, trajectory optimization and reinforcement learning toward achieving long-term adaptation in both control actions and trajectory planning for legged robots.
Biography: Quan Nguyen is an Assistant Professor of Aerospace and Mechanical Engineering at the University of Southern California. Prior to joining USC, he was a Postdoctoral Associate in the Biomimetic Robotics Lab at the Massachusetts Institute of Technology (MIT). He received his Ph.D. from Carnegie Mellon University (CMU) in 2017 with the Best Dissertation Award. His research interests span different control and optimization approaches for highly dynamic robotics including nonlinear control, trajectory optimization, real-time optimization-based control, robust and adaptive control. His work on the bipedal robot ATRIAS walking on steppingstones was featured on the IEEE Spectrum, TechCrunch, TechXplore and Digital Trends. His work on the MIT Cheetah 3 robot leaping on a desk was featured widely in many major media channels, including CNN, BBC, NBC, ABC, etc. Nguyen won the Best Presentation of the Session at the 2016 American Control Conference (ACC) and the Best System Paper Finalist at the 2017 Robotics: Science & Systems conference (RSS). Nguyen is a recipient of the 2020 Charles Lee Powell Foundation Faculty Research Award.
Host: Somil Bansal, somilban@usc.edu
Webcast: https://usc.zoom.us/webinar/register/WN_ySGInGwKRKKHX7NHJwTk3QLocation: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://usc.zoom.us/webinar/register/WN_ySGInGwKRKKHX7NHJwTk3Q
Audiences: Everyone Is Invited
Contact: Talyia White
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AME Seminar
Wed, Nov 09, 2022 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Douglas Holmes, Boston University
Talk Title: TBD
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/98775609685?pwd=a2lSd01oY0o2KzA4VWphbGxjWk5Qdz09Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/98775609685?pwd=a2lSd01oY0o2KzA4VWphbGxjWk5Qdz09
Audiences: Everyone Is Invited
Contact: Tessa Yao
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NL Seminar -Effective, Explainable, and Equitable NLP with World Knowledge and Interactions
Thu, Nov 10, 2022 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Bodhi Prasad Majumder, UCSD
Talk Title: Effective, Explainable, and Equitable NLP with World Knowledge and Interactions
Series: NL Seminar
Abstract: REMINDER
Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you are highly encouraged to use your USC account to sign into Zoom.
If you are an outside visitor, please inform us at nlg DASH seminar DASH host AT isi DOT edu beforehand so we will be aware of your attendance and let you in.
In person attendance will be permitted for USC ISI faculty, staff, students only. Open to the public virtually via the zoom link and online.
Artificial intelligence AI has shown remarkable effectiveness in knowledge seeking applications e.g., for recommendations and explanations. However, the increasing expectation of more trust, accessibility, and anthropomorphism in these AI systems requires the underlying components dialog models, LLMs, classifiers to be adaptive and adequately knowledge grounded. In reality, the outputs of the constituent models often lack commonsense, explanations, and subjectivity a long standing goal of artificial general intelligence.
In this talk, I aim to address this gap through the concept of interactive explainability, realized via three pillars knowledge, explanations, and interactions. First, I will explore the post-hoc methods to effectively inject relevant and diverse knowledge into an existing dialog model without additional training. Second, I will investigate the role of background knowledge in model reasoning, prediction, and faithfully constructing natural language explanations. Third, I will propose an interactive approach to address fairness and subjectivity in bias mitigation via feature level user interventions. Finally, I will hint at future possibilities and societal impacts of next-generation explainable interactive systems.
Biography: Bodhi Prasad Majumder is a final year PhD student at CSE, UC San Diego, advised by Prof. Julian McAuley. His research goal is to build interactive machines capable of producing knowledge grounded explanations. He previously spent time at the Allen Institute of AI, Google AI, Microsoft Research, and FAIR Meta AI, along with collaborations from U of Oxford, U of British Columbia, and the Alan Turing Institute.
His work has been recognized by the UCSD CSE Doctoral Award for Research, Adobe Research Fellowship, Qualcomm Innovation Fellowship, and Highlights of ACM Rec Sys, among many awards and several media coverages. In 2019, Bodhi led UCSD in the finals of the Amazon Alexa Prize. He also co authored a best selling NLP book with O Reilly Media that is being adopted in universities internationally.
Host: Jon May and Meryem Mhamdi
More Info: https://nlg.isi.edu/nl-seminar/
Webcast: https://www.youtube.com/watch?v=5Mva6sQgjuwLocation: Information Science Institute (ISI) - Virtual and ISI-Conf Rm#689
WebCast Link: https://www.youtube.com/watch?v=5Mva6sQgjuw
Audiences: Everyone Is Invited
Contact: Pete Zamar
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Dean's Seminar: Dean Gregory D. Abowd (Northeastern University) - The Internet of Materials: Rethinking the future of computing
Thu, Nov 10, 2022 @ 03:30 PM - 04:50 PM
Computer Science
Conferences, Lectures, & Seminars
Speaker: Dean Gregory D. Abowd, Northeastern University
Talk Title: The Internet of Materials: Rethinking the future of computing
Series: Dean's Seminar
Abstract: If we trace how computers have evolved over the past 8 or so decades, we can certainly see the impact of increasingly sophisticated manufacturing techniques. Computers now come in many different shapes and sizes. And applications, of course, have driven the widespread adoption, so much so that it appears we have an insatiable appetite for computing, and the power that is needed to feed it. That's a problem. We must take more seriously some of the past assumptions of how we manufacture computers and what properties the constituent materials impose. In this talk, I will introduce the notion of the Internet of Materials, whereby the power, form factor, and manufacturing costs of a computational object take precedence over other functional features of that object. I will show some simple examples that highlight how we can create self-sustaining computational materials. The purpose of the talk is to motivate researchers to think creatively about the convergence of materials, manufacturing, and computing. I hope these initial, and somewhat simple, examples prompt deeper discussions on how Northeastern can become a leader in defining a complementary computing industry.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Gregory D. Abowd is the Dean of the College of Engineering at Northeastern University, where he is also a Professor of Electrical and Computer Engineering with affiliate appointments in the Khoury College of Computer Sciences and the Bouvé College of Health Sciences. Prior to joining Northeastern in March 2021, Dr. Abowd was faculty in the College of Computing at the Georgia Institute of Technology for over 26 years, where he held the titles of Regents' Professor and J.Z. Liang Endowed Chair in the School in Interactive Computing. His research falls largely in the area of Human-Computer Interaction with an emphasis on applications and technology development for mobile and ubiquitous computing in everyday settings. His research has introduced innovations in the classroom, the home, for stakeholders connected with autism, and sustainable forms of computing in everyday life. He has been the founding Editor-in-Chief for two major journals and is the most highly cited researcher in HCI and ubiquitous computing in the world, according to csrankings.org (the second two are both his former PhD students). Dr. Abowd is a Fellow of the ACM and an elected member of the ACM SIGCHI Academy. He was a 2009 recipient of the ACM Eugene Lawler Humanitarian Contributions within Computer Science and Informatics. He earned his Bachelor of Science in Honors Mathematics (summa cum laude) from the University of Notre Dame in 1986 as well as a Master of Science (1987) and Doctor of Philosophy (1991) in Computation from the University of Oxford, where he attended as a Rhodes Scholar.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Department of Computer Science
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ISSS - Bahar Jalali-Farahani, Friday, Nov. 11th at 2pm in EEB 132
Fri, Nov 11, 2022 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Bahar Jalali-Farahani, Technical Lead, Cisco
Talk Title: Toward Tbps Optical and Wireline Communication: a Circuit Design Perspective
Series: Integrated Systems
Abstract: The demand for higher data rate communication has never been greater than today. Driven by
emerging technologies particularly IoT and cloud computing, higher capacity is required both in core
networking as well as computing applications. A report by the IEEE Ethernet Bandwidth Assessment ad
hoc group stated that "global demand for network bandwidth is growing at such an alarming rate that
terabit-speed networks will be the only way to support capacity, should current trends continue through
2015". This brings new challenges for circuit designer community as higher speed and better energy
efficiency are expected from building blocks of such communication systems.
This talk starts with an introduction to the two major category of optical communication; IMDD (Intensity
Modulated Direct Detect) vs Coherent detection. Pros, cons, and application of each are discussed and the
general architecture of receivers and transmitters in these systems are given. The talk then reviews the
latest trends in the design of high-speed transimpedance amplifiers and modulator drivers. Some examples
of co-design and co-optimization with optics are presented.
Biography: Bahar Jalali-Farahani received her PhD in electrical engineering from The Ohio
State University in 2005. During her PhD program, she was working with the data
converter research group at Freescale Semiconductor in Tempe, AZ where she was
responsible for developing digital calibration techniques for high resolution data
converters. She joined the department of electrical engineering at Arizona State
University in January 2006 and continued her research on digitally assisted high
performance analog circuits, and low-power circuit techniques. From 2011 to 2014
she was with Cisco Systems working on design of high-speed components for
Silicon-Photonics-based 100Gb Ethernet. In 2014 she joined Nokia Bell Labs in NJ
where she was a major contributor to the development of Nokia's Wavence products, multi-standard
microwave links used for long haul and short haul applications. Since September 2017 She has been with
Acacia Communications (now part of Cisco) working on millimeter-wave front ends for Silicon-Photonics
coherent receivers.
Host: MHI - ISSS, Hashemi, Chen and Sideris
More Information: Abstract and Bio-Nov 11-Jalali.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Healthcare Labor Management
Tue, Nov 15, 2022 @ 11:00 AM - 12:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: TBD, TBD
Talk Title: Healthcare Labor Management
Abstract: The USC Viterbi School of Engineering's Healthcare Labor Management course offered in partnership with the Institute of Industrial and Systems Engineers (IISE) will provide an understanding and overview of critical aspects of designing and executing a comprehensive labor management program.
Host: Executive Education
More Info: https://viterbiexeced.usc.edu/healthcare-labor-management-course-page/
Audiences: Registered Attendees
Contact: Corporate and Professional Programs
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Photonics seminar speaker - Jeffrey Moses, Tuesday, November 15th at 3pm in MCB 102
Tue, Nov 15, 2022 @ 03:00 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jeffrey Moses, Cornell University
Talk Title: Tackling longstanding challenges in ultrafast nonlinear optics via foreign but familiar physics
Series: Photonics Seminar Series
Abstract: Silicon-Optical nonlinearities have expanded the optics and photonics toolset for applications as diverse as high intensity laser science, quantum information processing, and the imaging and spectroscopy of biological systems. Key to many applications is use of the nonlinear polarizability of materials to couple photons between optical fields, giving rise to amplification and frequency conversion methods that expand the reach of lasers and other photon sources, both classical and non-classical. Other applications use light 'self-effects' to guide, switch, and modulate. However, optical nonlinearities are often small, and even when large enough, the spatiotemporal and spectral inhomogeneities in nonlinear optical systems can severely hamper the efficiency and bandwidth of power flow between waves.
Our group has been seeking ways to 'trick' nonlinear systems into modes of evolution that can avoid the normal limiting behaviors or to make use of unconventional nonlinear interactions. I'll discuss a few of these that possess familiar physics that are somewhat foreign to optical light pulses, such as rapid adiabatic passage in optical frequency conversion, oscillation damping in parametric (i.e., lossless) wave mixing, and nonlinear optical interactions involving coherent phonon coupling. And I will present some technologies that they can enable, including efficient parametric amplifiers, dispersion-free octave-spanning frequency up- and down-converters, strong cross-phase modulation, and the removal of spectral distinguishability.
Biography: Jeff Moses joined the faculty at Cornell University in 2014, where he leads the Ultrafast Phenomena and Technologies Group in the School of Applied and Engineering Physics. He received his B.S. from Yale and Ph.D. from Cornell, with both degrees in applied physics, and spent several years at the Optics & Quantum Electronics Group in the Research Laboratory of Electronics at MIT as a postdoctoral associate and research scientist. He has received the US National Science Foundation CAREER award and was an Air Force Office of Scientific Research Young Investigator.
Host: Mercedeh Khajavikhan, Michelle Povinelli, Constantine Sideris; Hossein Hashemi; Wade Hsu; Mengjie Yu; Wei Wu; Tony Levi; Alan E. Willner; Andrea Martin Armani
More Information: Jeffery Moses Flyer.pdf
Location: Michelson Center for Convergent Bioscience (MCB) - 102
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Epstein Institute - ISE 651 Seminar
Tue, Nov 15, 2022 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Robert Hildebrand, Assistant Professor, Grado Dept. of Industrial & Systems Engineering, Virginia Tech
Talk Title: Redistricting, Gerrymandering, and Mixed Integer Nonlinear Programming
Host: Prof. Suvrajeet Sen
More Information: November 15, 2022.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - GER 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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MFD Seminar With Professor Lily Cheung
Tue, Nov 15, 2022 @ 04:00 PM - 05:20 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Professor Lily Cheung, Assistant Professor, School of Chemical and Biomolecular Engineering, Georgia Institute of Technology
Talk Title: MFD Seminar With Professor Lily Cheung
Biography: Research Interests:
-Engineering of genetically encoded biosensors
-Quantitative fluorescence microscopy and image analysis
-Computational models of gene regulatory networks
-Transcriptional regulation and developmental biology of plants
The goal of the Cheung lab is to bring quantitative techniques and mathematical modeling to plants in order to gain systems-level insight into their physiology and development, particularly to understand how metabolic and gene regulatory networks interact to control homeostasis and growth.
Host: Professor Finley, Mork Family Department of Chemical Engineering and Materials Science
Location: James H. Zumberge Hall Of Science (ZHS) - 352
Audiences: Everyone Is Invited
Contact: Anthony Tritto
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Healthcare Labor Management
Wed, Nov 16, 2022 @ 11:00 AM - 12:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: TBD, TBD
Talk Title: Healthcare Labor Management
Abstract: The USC Viterbi School of Engineering's Healthcare Labor Management course offered in partnership with the Institute of Industrial and Systems Engineers (IISE) will provide an understanding and overview of critical aspects of designing and executing a comprehensive labor management program.
Host: Executive Education
More Info: https://viterbiexeced.usc.edu/healthcare-labor-management-course-page/
Audiences: Registered Attendees
Contact: Corporate and Professional Programs
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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 16, 2022 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Hayk Martiros, Skydio
Talk Title: Frontiers of Autonomous Flight and Real-Time 3D Reconstruction
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: At Skydio, we ship autonomous robots that are flown at scale in unknown environments every day by our customers to capture incredible video, automate dangerous inspections, build digital twins, and protect the lives of soldiers and first responders. These robots operate intelligently and make decisions at high speed using their onboard cameras and algorithms. We've invested a decade of R&D into handling complex visual scenarios and building a robust pipeline for visual navigation, obstacle avoidance, and rapid trajectory planning. On top of that, we're building a rich ecosystem of real-time 3D reconstruction technology to enable 360 global localization and map building on our drones.
During the talk, I will discuss the technology and impact of our core navigation stack and 3D Scan technology, and what research frontiers lie ahead. I plan to share visual examples of the algorithms in action, and connect to how these products solve pressing global challenges and enable next-generation operations across multiple industries. I will also introduce SymForce, our library for fast symbolic computation, code generation, and nonlinear optimization. This library powers many of our algorithms, and we have just published and open-sourced it as a contribution to the robotics community.
Biography: Hayk is a roboticist leading the autonomy group at Skydio, building robust visual autonomy to enable the positive impact of drones. Hayk has worked at Skydio since 2015 and was one of its first employees, where he contributed to all of Skydio's core autonomy systems. He now focuses on technical management of world-class engineers and researchers. Hayk's technical interests are in computer vision, deep learning, nonlinear optimization, systems architecture, and symbolic computation. His previous works include novel hexapedal robots, collaboration between robot arms, micro-robot factories, solar panel farms, and self-balancing motorcycles. Hayk was born in Yerevan, Armenia and grew up in Fairbanks, Alaska. He did his undergraduate study at Princeton University and graduate study at Stanford University.
Host: Somil Bansal, somilban@usc.edu
Webcast: https://usc.zoom.us/webinar/register/WN_ySGInGwKRKKHX7NHJwTk3QLocation: Online
WebCast Link: https://usc.zoom.us/webinar/register/WN_ySGInGwKRKKHX7NHJwTk3Q
Audiences: Everyone Is Invited
Contact: Talyia Whtie
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AME Seminar
Wed, Nov 16, 2022 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Khalid Jawed, UCLA
Talk Title: Reduced Order Modeling and Inverse Design of Flexible Structures by Machine Learning
Abstract: Recent advances in highly deformable structures necessitate simulation tools that can capture nonlinear geometry and nonlinear material. We propose machine learning, neural networks (NN) in particular, to capture this nonlinearity and solve highly nonlinear inverse problems in structural mechanics. Two representative problems will be discussed in this talk.
In the first problem, we use NN to reduce the number of variables and speed up the simulation by orders of magnitude. As a test case, we explore the dynamical simulation of a slinky, a pre-compressed elastic helix that is widely used as a toy for children. However, most often the deformation of a slinky can be fully captured by the deformation of its helix axis. Instead of simulating the entire helical structure, the axis of the helix is a reduced-order representation of this system. We use NN to store the elastic forces of the slinky in its reduced-order representation, utilizing the concept of neural ordinary differential equations. The NN is trained using data from a fine-grained 3D rod simulation called the Discrete Elastic Rods (DER). Once the elastic forces in the reduced representation are stored in the NN, force balance equations can be solved in this representation for the dynamic simulation. This results in savings in computational time without much impact on its physical accuracy.
In the second problem, we explore shape-morphing structures that spontaneously transition from planar to 3D shapes. This is a transformative technology with broad applications in soft robotics and deployable systems. However, realizing these morphing structures that can achieve certain target shapes is challenging and typically involves a painstaking process of trials and errors with complex local fabrication and actuation. We propose a rapid design approach for fully soft structures that can achieve targeted 3D shapes through a fabrication process that happens entirely on a 2D plane. By combining the strain mismatch between layers in a composite shell and locally relieving stress by creating kirigami cuts, we are able to create 3D free buckling shapes from planar fabrication. However, the large design space of the kirigami cuts and strain mismatch presents a challenging task of inverse form finding. We develop a symmetry-constrained active learning approach to learn how to explore the large design space strategically. Interestingly, we report that, given a target 3D shape, multiple design solutions exist, and our physics-guided machine learning approach can find them in a few hundred iterations. Desktop-controlled experiments and finite element simulations are in good agreement in examples ranging from peanuts to flowers.
Acknowledgment: Our lab is supported by the National Science Foundation (Award numbers: IIS-1925360, CMMI-2053971, CMMI-2101751, CAREER-2047663, OAC-2209782, CNS-2213839), the National Institute of Food and Agriculture of the US Department of Agriculture (Award # 2021-67022-34200, 2022-67022-37021), and the Department of Energy (Smart Manufacturing Institute, UCLA).
Biography: M. Khalid Jawed is an Assistant Professor in the Department of Mechanical and Aerospace Engineering of the University of California, Los Angeles, and the Principal Investigator of the Structures-Computer Interaction Laboratory. He received his Ph.D. and Master's degrees in Mechanical Engineering from the Massachusetts Institute of Technology in 2016 and 2014, respectively. He holds dual Bachelor's degrees in Aerospace Engineering and Engineering Physics from the University of Michigan, Ann Arbor. He also served as a Postdoctoral Researcher at Carnegie Mellon University. He received the NSF CAREER Award in 2021, the outstanding teaching award from UCLA in 2019, the outstanding teaching assistant award from MIT in 2015, and the GSNP best speaker award at the American Physical Society March Meeting in 2014.
Dr. Jaweds research interests lie at the intersection of structural mechanics and robotics, emphasizing a data-driven and artificially intelligent approach to the modeling and design of programmable smart structures. Current research projects include robotic manipulation of flexible structures, numerical simulation of highly deformable structures, soft robotics, and robotics for precision agriculture.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/98775609685?pwd=a2lSd01oY0o2KzA4VWphbGxjWk5Qdz09Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/98775609685?pwd=a2lSd01oY0o2KzA4VWphbGxjWk5Qdz09
Audiences: Everyone Is Invited
Contact: Tessa Yao
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Machine Learning Center Seminar: Yang Liu (UC Santa Cruz) - Agency Bias in Machine Learning
Thu, Nov 17, 2022 @ 10:00 AM - 11:30 AM
Computer Science
Conferences, Lectures, & Seminars
Speaker: Yang Liu, UC Santa Cruz
Talk Title: Agency Bias in Machine Learning
Series: Machine Learning Seminar Series
Abstract: A trained machine learning model (e.g., a classifier) will ultimately observe data generated according to agents' responses. For instance, the rising literature on strategic classification concerns the setting where agents are fully rational and can best respond to a classifier in their own interests. The above interaction will lead to a distribution shift between training and deployment and will challenge the existing performance and fairness guarantees of the trained model. In this talk, I'll discuss three types of agency bias that arise due to the above interactional effects between agents and machine learning models. I'll then go over possible mitigation efforts, including our very recent works on certifying the fairness guarantees on an unknown and possibly different deployment distribution.
References:
[1] Unfairness Despite Awareness: Group-Fair Classification with Strategic Agents. Andrew Estornell, Sanmay Das, Yang Liu and Yevgeniy Vorobeychik. Preprint, 2022.
[2] Actionable Recourse in Linear Classification. Berk Ustun, Alexander Spangher and Yang Liu
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT), 2019.
[3] Unintended Selection: Persistent Qualification Rate Disparities and Interventions. Reilly Raab and Yang Liu. Neural Information Processing Systems (NeurIPS), 2021.
[4] Fairness Transferability Subject to Bounded Distribution Shift. Yatong Chen, Reilly Raab, Jialu Wang and Yang Liu. Neural Information Processing Systems (NeurIPS), 2022.
Prof. Liu will give his talk in person at EEB 248 and we will also host the talk over Zoom.
Register in advance for this webinar at:
https://usc.zoom.us/webinar/register/WN_WtHgpFUFSbCI214E2i9q3Q
After registering, attendees will receive a confirmation email containing information about joining the webinar.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Yang Liu is currently an Assistant Professor of Computer Science and Engineering at UC Santa Cruz (2018 - present). He was previously a postdoctoral fellow at Harvard University (2016 - 2018). He obtained his Ph.D. degree from the Department of EECS, University of Michigan, Ann Arbor in 2015. He is interested in weakly supervised learning and algorithmic fairness. He is a recipient of the NSF CAREER Award and the NSF Fairness in AI award (lead PI). He has been selected to participate in several high-profile projects, including DARPA SCORE and IARPA HFC. His recent works have won four best paper awards at relevant workshops.
Host: Yan Liu
Webcast: https://usc.zoom.us/webinar/register/WN_WtHgpFUFSbCI214E2i9q3QLocation: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/webinar/register/WN_WtHgpFUFSbCI214E2i9q3Q
Audiences: Everyone Is Invited
Contact: Department of Computer Science
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NL Seminar -Pragmatic Interpretability
Thu, Nov 17, 2022 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Shi Feng, Univ of Illinois, Chicago
Talk Title: Pragmatic Interpretability
Series: NL Seminar
Abstract: Abstract: REMINDER
Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you are highly encouraged to use your USC account to sign into Zoom.
If you are an outside visitor, please inform us at nlg DASH seminar DASH host AT isi DOT edu beforehand so we will be aware of your attendance and let you in.
In person attendance will be permitted for USC ISI faculty, staff, students only. Open to the public virtually via the zoom link and online.
Machine learning models have been quite successful at emulating human intelligence but their potential as intelligence augmentation is less explored. Part of the challenge is our lack of understanding in how these models work, and this is the problem interpretability is trying to tackle. But most existing interpretability work takes models trained under the emulation paradigm and adds humans into the mix post-hoc-the human's role is largely an afterthought. In this talk, I advocate for a more pragmatic approach to interpretability and emphasize modeling the human's needs in their cooperation with AIs. In the first part, I discuss how the human-AI team can be evaluated and optimized as a unified decision-maker, and how the model can learn to explain selectively. In the second part, I discuss how human intuition measured outside of the working with an AI context can be incorporated into models and explanations. I'll conclude with a brief discussion on formulating the model's pragmatic inference about its human teammate.
Biography: Shi Feng is a postdoc at University of Chicago working with Chenhao Tan. He got his PhD from University of Maryland under Jordan Boyd-Graber. He is interested in human-AI cooperation: how machine learning can help humans make better decisions, and how humans can provide supervision more effectively. His past work focuses on natural language processing, and covers topics including interpretability, adversarial attacks, robustness, and human-in-the-loop evaluations.
Host: Jon May and Meryem Mhamdi
More Info: https://nlg.isi.edu/nl-seminar/
Webcast: https://www.youtube.com/watch?v=C8jUO4w5xwULocation: Information Science Institute (ISI) - Virtual and ISI-Conf Rm#689
WebCast Link: https://www.youtube.com/watch?v=C8jUO4w5xwU
Audiences: Everyone Is Invited
Contact: Pete Zamar
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ECE Seminar: Learning Efficiently in Data-Scarce Regimes
Fri, Nov 18, 2022 @ 01:00 PM - 02:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Mohammad Rostami, Research Assistant Professor, Dept of CS / Research Lead, USC-ISI
Talk Title: Learning Efficiently in Data-Scarce Regimes
Abstract: The unprecedented processing demand, posed by the explosion of big data, challenges researchers to design efficient and adaptive machine learning algorithms that do not require persistent retraining and avoid learning redundant information. Inspired from learning techniques of intelligent biological agents, identifying transferable knowledge across learning problems has been a significant research focus to improve machine learning algorithms. In this talk, we explain how the challenges of knowledge transfer can be addressed through embedding spaces that capture and store hierarchical knowledge.
We first focus on the problem of cross-domain knowledge transfer. We explore the problem of zero-shot image classification, where the goal is to identify images from unseen classes using semantic descriptions of these classes. We train two coupled dictionaries that align visual and semantic domains via an intermediate embedding space. We then extend this idea by training deep networks that match data distributions of two visual domains in a shared cross-domain embedding space.
We then investigate the problem of cross-task knowledge transfer in sequential learning settings. Here, the goal is to identify relations and similarities of multiple machine learning tasks to improve performance across the tasks. We first address the problem of zero-shot learning in a lifelong machine learning setting, where the goal is to learn tasks with no data using high-level task descriptions. Our idea is to relate high-level task descriptors to the optimal task parameters through an embedding space. We then develop a method to overcome the problem of catastrophic forgetting within a continual learning setting of deep neural networks by enforcing the tasks to share the same distribution in the embedding space.
Finally, we focus on current research directions to expand past progress and plans for future research directions. Through this talk, we demonstrate that despite major differences, problems within the above learning scenarios can be tackled using a unifying strategy that allows transferring knowledge effectively.
Biography: Mohammad Rostami is a research assistant professor at the USC CS department and a research lead at the USC Information Sciences Institute. He received Ph.D. degree in Electrical and Systems Engineering from the University of Pennsylvania in August 2019. He also received an M.S. degree in Robotics and M.A. degree in Philosophy at Penn. Before Penn, he obtained an M.Sc. degree in Electrical and Computer Engineering from the University of Waterloo, and his B.Sc. degree in Electrical Engineering and B.Sc. degree in Mathematics from the Sharif University of Technology. His current research area is machine learning in time-dependent and data-scarce regimes.
Host: Dr. Richard M. Leahy
Webcast: https://usc.zoom.us/j/97552157471?pwd=RnVGWm10RlRORFU0cG5RYWVWU0R0Zz09More Information: Seminar Announcement-Rostami-111822.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 539
WebCast Link: https://usc.zoom.us/j/97552157471?pwd=RnVGWm10RlRORFU0cG5RYWVWU0R0Zz09
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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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
Tue, Nov 22, 2022 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mihaela van der Schaar, University of Cambridge
Talk Title: AI for Science: Discovering Diverse Classes of Equations in Medicine and Beyond
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Artificial Intelligence (AI) offers the promise of revolutionizing the way scientific discoveries are made and significantly accelerating their pace. This is important for numerous fields of study, including medicine. In this talk, I will present our research on AI for science over the past few years. I will start by briefly showing how we can discover closed-form prediction functions from cross-sectional data using symbolic metamodels. Then, I will introduce a new method, called D-CODE, which discovers closed-form ordinary differential equations (ODEs) from observed trajectories (longitudinal data).This method can only describe observable variables, yet many important variables in medical settings are often not observable. Hence, I will subsequently present the latent hybridisation model (LHM) that integrates a system of ODEs with machine-learned neural ODEs to fully describe the dynamics of the complex systems. However, ODEs are fundamentally inadequate to model systems with long-range dependencies or discontinuities. To solve these challenges, I will then present Neural Laplace, with which we can learn diverse classes of differential equations in the Laplace domain. I will conclude by presenting next research frontiers, including recent work on discovering partial differential questions from data (D-CIPHER). While these works are applicable in numerous scientific domains, in this talk I will illustrate the various works with examples from medicine, ranging from understanding cancer evolution to treating Covid-19. This work is joint work with Zhaozhi Qian, Krzysztof Kacprzyk and Sam Holt.
Biography: Mihaela van der Schaar is the John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge and a Fellow at The Alan Turing Institute in London. In addition to leading the van der Schaar Lab, Mihaela is founder and director of the Cambridge Centre for AI in Medicine (CCAIM).
Mihaela was elected IEEE Fellow in 2009. She has received numerous awards, including the Oon Prize on Preventative Medicine from the University of Cambridge (2018), a National Science Foundation CAREER Award (2004), 3 IBM Faculty Awards, the IBM Exploratory Stream Analytics Innovation Award, the Philips Make a Difference Award and several best paper awards, including the IEEE Darlington Award.
Mihaela is personally credited as inventor on 35 USA patents (the majority of which are listed here), many of which are still frequently cited and adopted in standards. She has made over 45 contributions to international standards for which she received 3 ISO Awards. In 2019, a Nesta report determined that Mihaela was the most-cited female AI researcher in the U.K.
Host: Urbashi Mitra and Pierluigi Nuzzo
Webcast: https://usc.zoom.us/webinar/register/WN_ySGInGwKRKKHX7NHJwTk3QLocation: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/webinar/register/WN_ySGInGwKRKKHX7NHJwTk3Q
Audiences: Everyone Is Invited
Contact: Talyia White
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***NO EPSTEIN INSTITUTE - ISE 651 SEMINAR (THANKSGIVING BREAK)***
Tue, Nov 22, 2022 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Location: Ethel Percy Andrus Gerontology Center (GER) - GER 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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Virtual Event - On Measuring Causal Contributions via do-interventions
Mon, Nov 28, 2022 @ 10:00 AM - 11:00 PM
Conferences, Lectures, & Seminars
Speaker: Dr. Shiva Kasiviswanathan,
Talk Title: On Measuring Causal Contributions via do-interventions
Location: https://usc.zoom.us/j/96927080167?pwd=Vk9MOEpOSUx3V1hlZFc3U0tmOTNsUT09
Audiences: Everyone Is Invited
Contact: Susan Wiedem
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Epstein Institute - ISE 651 Seminar
Tue, Nov 29, 2022 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Johannes Royset, Professor, Operations Research, Naval Post Graduate School
Talk Title: Relax! The Case For Rockafellian Relaxation In Stochastic Optimization and Learning
Host: Prof. Jong-Shi Pang
More Information: November 29, 2022.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - GER 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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Virtual Efficient Estimation of Treatment Effect in Online Experiments
Wed, Nov 30, 2022 @ 10:00 AM - 11:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Congshan Zhang, Meta , Core Data Science Team at Meta
Talk Title: Efficient Estimation of Treatment Effect in Online Experiments
Abstract: Randomized controlled trials are commonly used by tech companies to draw causal conclusions on various product changes. The confidence intervals from these experiments, however, are usually too large due to reasons such as limited number of users, heavy-tailed outcome variables and small treatment effects. Improving estimation efficiency for randomized controlled trials is not only a scientifically interesting but also a practically relevant area of research. In this talk, I will go over a few prominent techniques in statistics to improve estimation efficiency. Basic techniques such as CUPED and more advanced methodologies based on ML and synthetic controls will be introduced.
Biography: Congshan Zhang is a research scientist on Core Data Science Team at Meta. Congshan is interested in various topics in statistics and econometrics including causal inference, machine learning and time series. Congshan holds Ph.D. in economics from Duke University. Before joining Meta, Congshan did research on financial econometrics, with a focus on nonparametric and semi-parametric inference using high-frequency data and on testing models of financial markets. His work appears in top journals of econometrics such as Journal of Econometrics and Annals of Applied Probability.
Host: Urbashi Mitra
More Info: https://usc.zoom.us/j/96927080167?pwd=Vk9MOEpOSUx3V1hlZFc3U0tmOTNsUT09 Meeting ID: 969 2708 0167 Passcode: 586135
More Information: ECE Seminar Announcement_Nov21.docx
Location: https://usc.zoom.us/j/96927080167?pwd=Vk9MOEpOSUx3V1hlZFc3U0tmOTNsUT09 Meeting ID: 969 2708 0167 P
Audiences: Everyone Is Invited
Contact: Susan Wiedem
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PhD Academic Career Mentoring Panel Series "Charting the Multi-dimensional Path for Research Excellence"
Wed, Nov 30, 2022 @ 12:00 PM - 02:00 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
You are invited to the PhD Academic Career Mentoring Panel Series for current Engineering doctoral students and postdocs from all areas and departments. This session is aimed to encourage PhD students and postdocs to pursue rewarding careers in academia and research. Distinguished faculty will discuss their academic paths and offer strategic advice and answer your questions. Lunch is provided!
Moderated by: Mahta Moghaddam, Vice Dean for Research & Dr. Urbashi Mitra, Gordon S. Marshall Chair in Engineering
Faculty Panel:
Dr. David A. Barnhart
Information Science Institute, Astronautical Engineering
Dr. Mercedeh Khajavikhan
Electrical and Computer Engineering - Electrophysics
Dr. Lucio Soibelman
Civil and Environmental Engineering
Dr. Francisco Valero-Cuevas
Biomedical Engineering
Location: Sign into EngageSC to View Location
Audiences:
Contact: Nora Sandoval
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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 30, 2022 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Vikas Sindhwani, Google Brain
Talk Title: Foundation Models for Robotics
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Trained on internet-scale datasets, large language and vision models demonstrate breakthrough capabilities which until recently were thought to still be decades away in technological feasibility. Does this imply a paradigm shift in Robotics as well? If so, what is the bridge from symbols and tokens on the internet to actions in the physical world? Through a few illustrative vignettes of robotic manipulation and navigation research at Google, I will propose speculative paths towards making robots useful in human-centric spaces.
Biography: Vikas Sindhwani is Senior Staff Research Scientist in the Google Brain team in New York where he leads a research group focused on solving a range of planning, perception, learning, and control problems arising in Robotics. His interests are broadly in core mathematical foundations of statistical learning, and in end-to-end design aspects of building large-scale, robust machine intelligence systems. He received the best paper award at Uncertainty in Artificial Intelligence (UAI) 2013, the IBM Pat Goldberg Memorial Award in 2014, and was finalist for Outstanding Planning Paper Award at ICRA-2022. He serves on the editorial board of Transactions on Machine Learning Research (TMLR) and IEEE Transactions on Pattern Analysis and Machine Intelligence; he has been area chair and senior program committee member for NeurIPS, International Conference on Learning Representations (ICLR) and Knowedge Discovery and Data Mining (KDD). He previously led a team of researchers in the Machine Learning group at IBM Research, NY. He has a PhD in Computer Science from the University of Chicago and a B.Tech in Engineering Physics from Indian Institute of Technology (IIT) Mumbai. His publications are available at: http://vikas.sindhwani.org/.
Host: Somil Bansal, somilban@usc.edu
Webcast: https://usc.zoom.us/webinar/register/WN_ySGInGwKRKKHX7NHJwTk3QLocation: Online
WebCast Link: https://usc.zoom.us/webinar/register/WN_ySGInGwKRKKHX7NHJwTk3Q
Audiences: Everyone Is Invited
Contact: Talyia White
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AME Seminar (Virtual)
Wed, Nov 30, 2022 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Sebastian Pattinson, University of Cambridge
Talk Title: Generalisable 3D Printing Error Detection and Correction via Neural Networks
Abstract: Material extrusion is the most widespread additive manufacturing method but its application in end-use products is limited by vulnerability to errors. Humans can detect errors but cannot provide continuous monitoring or real-time correction. Existing automated approaches are not generalisable across different parts, materials, and printing systems. In this talk I will discuss recent work in our lab where we train a multi-head neural network using images automatically labelled by deviation from optimal printing parameters. The automation of data acquisition and labelling allows the generation of a large and varied extrusion 3D printing dataset, containing 1.2 million images from 192 different parts labelled with printing parameters. The thus trained neural network, alongside a control loop, enables real-time detection and rapid correction of diverse errors that is effective across many different 2D and 3D geometries, materials, printers, toolpaths, and even extrusion methods.
Biography: Sebastian Pattinson is an Assistant Professor in the Department of Engineering at the University of Cambridge. His group develops 3D printers that learn how to make things better and uses these to make better medical devices. Before joining the Cambridge, Sebastian was a postdoctoral fellow in the Department of Mechanical Engineering at MIT focusing on 3D printed materials and devices. He received Ph.D. and Masters degrees in the Department of Materials Science & Metallurgy at the University of Cambridge, where he developed nanomaterial synthesis methods. His awards include a UK Academy of Medical Sciences Springboard award; US National Science Foundation postdoctoral fellowship; UK Engineering and Physical Sciences Research Council Doctoral Training Grant; MIT Translational Fellowship; and a (Google) X Moonshot Fellowship.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/98775609685?pwd=a2lSd01oY0o2KzA4VWphbGxjWk5Qdz09WebCast Link: https://usc.zoom.us/j/98775609685?pwd=a2lSd01oY0o2KzA4VWphbGxjWk5Qdz09
Audiences: Everyone Is Invited
Contact: Tessa Yao
