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Events for November 13, 2019
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Meet USC: Admission Presentation, Campus Tour, and Engineering TalkWed, Nov 13, 2019
Viterbi School of Engineering Undergraduate Admission
Workshops & Infosessions
This half day program is designed for prospective freshmen (HS seniors and younger) and family members. Meet USC includes an information session on the University and the Admission process, a student led walking tour of campus, and a meeting with us in the Viterbi School. During the engineering session we will discuss the curriculum, research opportunities, hands-on projects, entrepreneurial support programs, and other aspects of the engineering school. Meet USC is designed to answer all of your questions about USC, the application process, and financial aid.
Reservations are required for Meet USC. This program occurs twice, once at 8:30 a.m. and again at 12:30 p.m.
Please make sure to check availability and register online for the session you wish to attend. Also, remember to list an Engineering major as your "intended major" on the webform!
Register HereLocation: Ronald Tutor Campus Center (TCC) -
Audiences: Everyone Is Invited
Contact: Viterbi Admission
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CAIS Seminar: Sheldon H. Jacobson (University of Illinois) - Creating a Transparent Environment for Political Redistricting
Wed, Nov 13, 2019 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Sheldon H. Jacobson, University of Illinois
Talk Title: Creating a Transparent Environment for Political Redistricting
Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series
Abstract: Political redistricting is a multi-criteria problem with conflicting objectives (based on metrics like compactness, population balance, and efficiency gaps, among others). Many of these metrics have received significant attention, though they remain controversial as to which such metrics are best suited to define fair district maps. This research uses a multi-objective optimization approach to reveal obstacles in defining fair district maps. The results obtained challenge a number of common perceptions of redistricting, suggesting that defining fair maps may not only be extremely difficult, but also, simply unrealistic.
This lecture satisfies requirements for CSCI 591: Research Colloquium. Please note, due to limited capacity in OHE 136, seats will be first come first serve.
Biography: Sheldon H. Jacobson is a Founder Professor of Computer Science at the University of Illinois. He has a B.Sc. and M.Sc. (both in Mathematics) from McGill University, and a M.S. and Ph.D. (both in Operations Research) from Cornell University. From 2012-2014, he was on leave from the University of Illinois, serving as a Program Director at the National Science Foundation. His research interests span theory and practice, covering decision-making under uncertainty and optimization-based artificial intelligence, with applications in aviation security, public policy, public health, and sports. He has been recognized by numerous awards, including a Guggenheim Fellowship from the John Simon Guggenheim Memorial Foundation. He is a fellow of both IISE and INFORMS.
Host: USC Center for Artificial Intelligence in Society (CAIS)
Location: Olin Hall of Engineering (OHE) - 136
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar
Wed, Nov 13, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Nikil Dutt, Distinguished Professor, University of California, Irvine
Talk Title: Computational Self-awareness and Self-organization: A Paradigm for Building Adaptive, Resilient Computing Platforms
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Self-awareness and self-organization have a long history in biology, psychology, medicine, engineering and (more recently) computing. In the past decade this has inspired new self-aware/self-organizing strategies for building resilient computing platforms that can adapt to the (often conflicting) challenges of resiliency, energy, heat, cost, performance, security, etc. in the face of highly dynamic operational behaviors and environmental conditions. I will begin by outlining a computational self-awareness paradigm that enables adaptivity and which supports system resilience. I will show how computational self-awareness can be deployed to achieve cross-layer resilience on the exemplar CyberPhysical-Systems-on-Chip (CPSoC) platform. CPSoC is a new class of sensor-actuator rich many-core computing platform that intrinsically couples on-chip and cross-layer sensing and actuation to support computational self-awareness. Computational self-awareness is achieved through introspection (i.e., modeling and observing its own internal and external behaviors) combined with both reflexive and reflective adaptations via cross-layer physical and virtual sensing and actuations applied across multiple layers of the hardware/software system stack. Next I will outline strategies for combining computational self-awareness with self-organization for life-cycle management of dependable distributed computing platforms. Our ongoing NSF/DFG Information Processing Factory (IPF) project applies principles inspired by factory management that combine self-awareness and self-organization for continuous operation and optimization of highly-integrated-but-distributed embedded computing platforms. While each IPF computational component exhibits autonomy through self-awareness, collections of IPF entities can self-organize; the resulting emergent behavior must be controlled in order to ensure guaranteed service even under strict safety and availability requirements. I will outline strategies such as proactive reconfiguration to mitigate the risk of failures, self-optimization, self-identification using learning classifiers, and chip-level operation with flexible boundaries between critical and best effort regions, all guided by a self-aware planning component. The talk will conclude with the opportunities and challenges arising from adopting computational self-awareness and self-organization for making complex computational systems more resilient and self-adaptive.
Biography: Nikil Dutt is a Distinguished Professor of CS, Cognitive Sciences, and EECS at the University of California, Irvine, and also a Distinguished Visiting Professor of CSE at IIT Bombay, India. He received a PhD from the University of Illinois at Urbana-Champaign (1989). His research interests are in embedded systems, EDA, computer architecture and compilers, distributed systems, healthcare IoT, and brain-inspired architectures and computing. He has received numerous best paper awards and is coauthor of 7 books. Professor Dutt has served as EiC of ACM TODAES and AE for ACM TECS and IEEE TVLSI. He is on the steering, organizing, and program committees of several premier EDA and Embedded System Design conferences and workshops, and has also been on the advisory boards of ACM SIGBED, ACM SIGDA, ACM TECS and IEEE ESL. He is an ACM Fellow, IEEE Fellow, and recipient of the IFIP Silver Core Award.
Host: Jyotirmoy Deshmukh
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Talyia White
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AME Seminar
Wed, Nov 13, 2019 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Paolo Luzzatto-Fegiz,
Talk Title: Two Problems in Wall-Bounded Flow: Fluid Energy Extraction in Wind Farms, and Surfactant Effects in Superhydrophobic Drag Reduction
Abstract: In this talk, we consider two fluid problems directly linked to decarbonization efforts. In the first part, we investigate fundamental limits to the performance of large wind farms. Since wind turbines are often deployed in arrays of hundreds of units, wake interactions can lead to drastic losses in power output. Remarkably, while the theoretical Betz maximum has long been established for the output of a single turbine, no corresponding theory appears to exist for a generic, large-scale energy extraction system. We develop a model for an array of energy-extracting devices of arbitrary design and layout, first focusing on the fully-developed regime, which is relevant for large wind farms. We validate our model against data from field measurements, experiments and simulations. By defining a suitable ideal limit, we establish an upper bound on the performance of a large wind farm. This is an order of magnitude larger than the output of existing arrays, thus supporting the notion that large performance improvements may be possible.
In the second part of this talk, we examine flow past superhydrophobic surfaces (SHS). These coatings have long promised large drag reductions; however, experiments have provided inconsistent results, with many textures yielding little or no benefit. By performing surfactant-laden simulations and unsteadily-driven experiments, we demonstrate that surfactant-induced Marangoni stresses can be to blame. We find that extremely low surfactant concentrations, unavoidable in practice, can drastically increase drag, at least in laminar flows. To obtain accurate drag predictions on SHS, one must therefore solve the mass, momentum, bulk surfactant and interfacial surfactant conservation equations, which is not feasible in most applications. To address this issue, we propose a theory that captures how the near-surface dynamics depend on the seven dimensionless groups for surfactant. We validate our theory extensively in 2D, and describe progress toward 3D and turbulent models. Our theory significantly improves predictions relative to a surfactant-free one, which can otherwise overestimate drag reduction by several orders of magnitude.
Here are links to papers/resources that form the basis for this talk:
https://doi.org/10.1103/PhysRevFluids.3.093802
https://doi.org/10.1073/pnas.1702469114
https://doi.org/10.1103/PhysRevFluids.3.100507
https://doi.org/10.1103/APS.DFD.2017.GFM.V0098
https://arxiv.org/abs/1904.01194
Biography: Paolo Luzzatto-Fegiz graduated with a BEng in Aerospace Engineering from the University of Southampton, where he received the Royal Aeronautical Society Prize for highest first-class degree and the Graham Prize for best experimental project in the School of Engineering Sciences. After a summer working with the ATLAS Magnet Team at CERN, he completed an MSc in Applied Mathematics at Imperial College, and an MS and PhD in Aerospace Engineering at Cornell University. His doctoral work received the Acrivos Award of the American Physical Society for outstanding dissertation in Fluid Dynamics at a U.S. university. He was awarded a Devonshire Postdoctoral Scholarship from the Woods Hole Oceanographic Institution, as well as a Junior Research Fellowship from Churchill College, Cambridge. He is currently an Assistant Professor in Mechanical Engineering at UCSB, where he has received the Northrop Grumman Teaching Award and a Gallery of Fluid Motion Award from APS-DFD. He co-invented a salinity sensor for oceanography that has been adopted by 20 institutions, and led the first microgravity experiment from NSF CBET, which successfully returned in January 2019 from the International Space Station.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Location: 102
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
