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SUNMONTUEWEDTHUFRISAT
Events for the 3rd week of November
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Meet USC: Admission Presentation, Campus Tour, and Engineering TalkMon, Nov 12, 2018
Viterbi School of Engineering Undergraduate Admission
University Calendar
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!
RSVPLocation: Ronald Tutor Campus Center (TCC) - USC Admission Office
Audiences: Everyone Is Invited
Contact: Rebecca Kinnon
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USC Viterbi Data Analytics Boot Camp
Mon, Nov 12, 2018
Executive Education
Conferences, Lectures, & Seminars
Abstract: What you will learn:
- Students will learn the fundamental and specialized skills necessary to pursue a career or advance in the booming field of data analytics, including Python, JavaScript, Advanced Excel, SQL Databases and more.
- Students are equipped with the technical skills needed to translate data into competitive insights in the workplace, leading to career advancement opportunities.
- Students receive a hands-on, classroom learning experience, conducting robust analytics on a host of real-world problems.
- Students working to change career paths receive career-planning assistance, including industry speakers and company-led events, resume, Linkedln and portfolio support, and interview preparation.
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/computer-science/usc-viterbi-data-analytics-boot-camp/
Audiences: Registered Attendees
Contact: Corporate & Professional Programs
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CS Colloquium: Ram D. Sriram (NIST) - Explorations in Artificial Intelligence: A Personal Journey
Mon, Nov 12, 2018 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ram D. Sriram, National Institute of Standards and Technology
Talk Title: Explorations in Artificial Intelligence: A Personal Journey
Series: Computer Science Colloquium
Abstract: My first exposure to Artificial Intelligence (AI) was in the summer of 1981, when Carnegie Mellon University was tasked with the development of a knowledge-based expert system (KBES) to aid in the trouble shooting of the Atlanta People Mover. I was a student member of this team and went on to do my dissertation on AI in Design. Later, I joined MIT as an assistant professor (in 1986) and with my students built one of the most comprehensive computational frameworks for Internet-based collaborative design -“ called DICE. The DICE framework introduced several novel concepts in AI, including an active object-oriented blackboard, constraint satisfaction using asynchronous teams, merging qualitative geometry with traditional modeling, knowledge representation schemes for product and process models, and design rationale. In 1994, I moved to NIST and continued work on knowledge representation for entire product life cycle until 2010, when I took over as the chief of Software and Systems Division. Here, I have provided technical leadership for several AI projects, which include extending deep learning techniques in biomedical image processing, extracting protein-protein interaction sentences from documents, developing a novel natural language term extraction system based on Sanskrit, and applying Category Theory for AI knowledge representation. In this talk, I will describe my journey over nearly four decades with a particular focus on my recent work at NIST on knowledge representation, machine learning, and natural language processing.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Ram D. Sriram is currently the chief of the Software and Systems Division, Information Technology Laboratory, at the National Institute of Standards and Technology (NIST). Before joining the Software and Systems Division, Sriram was the leader of the Design and Process group in the Manufacturing Systems Integration Division, Manufacturing Engineering Laboratory, where he conducted research on standards for interoperability of computer-aided design systems. Prior to joining NIST, he was on the engineering faculty (1986-1994) at the Massachusetts Institute of Technology (MIT) and was instrumental in setting up the Intelligent Engineering Systems Laboratory. Sriram has co-authored or authored more than 250 publications, including several books on artificial intelligence. Sriram was a founding co-editor of the International Journal for AI in Engineering. Sriram received several awards including: an NSF's Presidential Young Investigator Award (1989); ASME Design Automation Award (2011); ASME CIE Distinguished Service Award (2014); the Washington Academy of Sciences' Distinguished Career in Engineering Sciences Award (2015); ASME CIE division's Lifetime Achievement Award (2016); and CMU CEE Lt. Col. Christopher Raible Distinguished Public Service Award (2018). Sriram is a Fellow of ASME, AAAS, IEEE and Washington Academy of Sciences, a Member (life) of ACM and a Senior Member (life) of AAAI. Sriram has a B.Tech. from IIT, Madras, India, and an M.S. and a Ph.D. from Carnegie Mellon University, Pittsburgh, USA.
Host: Computer Science Department
Location: Olin Hall of Engineering (OHE) - 100D
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Seminars in Biomedical Engineering
Mon, Nov 12, 2018 @ 12:30 PM - 01:50 PM
Conferences, Lectures, & Seminars
Speaker: Kaustabh Ghosh, PhD, Associate Professor, Department of Bioengineering, Division of Biomedical Sciences, and Program in Cell, Molecular and Developmental Biology University of California, Riverside
Talk Title: Learning the Hard Way: Role of Vascular Stiffening in Inflammatory Retinal Diseases
Host: Qifa Zhou
More Information: Ghosh USC BME Abstract.pdf
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Nov 12, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Munther Dahleh, MIT
Talk Title: A Marketplace for Data: An Algorithmic Solution
Abstract: In this work, we aim to create a data marketplace; a robust real-time matching mechanism to efficiently buy and sell training data for Machine Learning tasks. While the monetization of data and pre-trained models is an essential focus of industry today, there does not exist a market mechanism to price training data and match buyers to vendors while still addressing the associated (computational and other) complexity. The challenge in creating such a market stems from the very nature of data as an asset: it is freely replicable; its value is inherently combinatorial due to correlation with signal in other data; prediction tasks and the value of accuracy vary widely; usefulness of training data is difficult to verify a priori without first applying it to a prediction task. As our main contributions we: propose a mathematical model for a two-sided data market and formally define the key associated challenges; construct algorithms for such a market to function and rigorously prove how they meet the challenges defined. We highlight two technical contributions: a new notion of fairness required for cooperative games with freely replicable goods; a truthful, zero regret mechanism for auctioning a particular class of combinatorial goods based on utilizing Myerson's payment function and the Multiplicative Weights algorithm. These might be of independent interest.
This is a joint work with Anish Agarwal, Tuhin Sarkar, and Devavrat Shah.
Biography: Munther A. Dahleh received his PhD degree from Rice University, Houston, TX, in 1987 in Electrical and Computer Engineering. Since then, he has been with the Department of Electrical Engineering and Computer Science (EECS), MIT, Cambridge, MA, where he is now the William A. Coolidge Professor of EECS. He is also a faculty affiliate of the Sloan School of Management. He is the founding director of the newly formed MIT Institute for Data, Systems, and Society (IDSS). Previously, he held the positions of Associate Department Head of EECS, Acting Director of the Engineering Systems Division, and Acting Director of the Laboratory for Information and Decision Systems. He was a visiting Professor at the Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, for the Spring of 1993. He has consulted for various national research laboratories and companies. Dr. Dahleh is interested in Networked Systems with applications to Social and Economic Networks, financial networks, Transportation Networks, Neural Networks, and the Power Grid. Specifically, he focuses on the development of foundational theory necessary to understand, monitor, and control systemic risk in interconnected systems. His work draws from various fields including game theory, optimal control, distributed optimization, information theory, and distributed learning. His collaborations include faculty from all five schools at MIT. Dr. Dahleh is the co-author (with Ignacio Diaz-Bobillo) of the book Control of Uncertain Systems: A Linear Programming Approach, published by Prentice-Hall, and the co-author (with Nicola Elia) of the book Computational Methods for Controller Design, published by Springer. He is four-time recipient of the George Axelby outstanding paper award for best paper in IEEE Transactions on Automatic Control. He is also the recipient of the Donald P. Eckman award from the American Control Council in 1993 for the best control engineer under 35. He is a fellow of IEEE and IFAC. He has given many keynote lectures at major conferences.
Host: Ketan Savla, ksavla@usc.edu
More Info: http://csc.usc.edu/seminars/2018Fall/dahleh.html
More Information: 18.11.12_Dahleh_MIT-CSC Seminar.pdf
Location: 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: http://csc.usc.edu/seminars/2018Fall/dahleh.html
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Mathworks Information Session
Mon, Nov 12, 2018 @ 06:00 PM - 07:00 PM
Viterbi School of Engineering Student Organizations
Workshops & Infosessions
If you have a strong technical background in software design, web development, control theory, signal processing, or embedded systems - We'd love to talk to you!
Who: Students in Computer Science, Electrical Engineering, Mechanical Engineering, Biomedical Engineering or Aerospace Engineering - We are hiring for Spring Interns, Summer Interns, and Full-Time.
Chipotle will be provided!More Information: MatLab-Info-Session-2018-Ad.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Institute of Electrical and Electronics Engineers
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Trusted Inference Engine: Preventing Neural Network Exfiltration in Hardware Devices
Tue, Nov 13, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Michel A. Kinsy, Boston University
Talk Title: Trusted Inference Engine: Preventing Neural Network Exfiltration in Hardware Devices
Abstract: Companies, in their push to incorporate artificial intelligence - in particular, machine learning - into their Internet of Things (IoT), system-on-chip (SoC), and automotive applications, will have to address a number of design challenges related to the secure deployment of artificial intelligence learning models and techniques. Machine learning (ML) models are often trained using private datasets that are very expensive to collect, or highly sensitive, using large amounts of computing power. The models are commonly exposed either through online APIs, or used in hardware devices deployed in the field or given to the end users. This gives incentives to adversaries to attempt to steal these ML models as a proxy for gathering datasets. While API-based model exfiltration has been studied before, the theft and protection of machine learning models on hardware devices have not been explored as of now. In this work, we examine this important aspect of the design and deployment of ML models. We illustrate how an attacker may acquire either the model or the model architecture through memory probing, side-channels, or crafted input attacks, and propose power-efficient obfuscation as an alternative to encryption, and timing side-channel countermeasures.
Biography: Michel A. Kinsy is an Assistant Professor in the Department of Electrical and Computer Engineering at Boston University (BU), where he directs the Adaptive and Secure Computing Systems (ASCS) Laboratory. He focuses his research on computer architecture, hardware-level security, neural network accelerator designs, and cyber-physical systems. Dr. Kinsy is an MIT Presidential Fellow, the 2018 MWSCAS Myril B. Reed Best Paper Award Recipient, DFT'17 Best Paper Award Finalist, and FPL'11 Tools and Open-Source Community Service Award Recipient. He earned his PhD in Electrical Engineering and Computer Science in 2013 from the Massachusetts Institute of Technology. His doctoral work in algorithms to emulate and control large-scale power systems at the microsecond resolution inspired further research by the MIT spin-off Typhoon HIL, Inc. Before joining the BU faculty, Dr. Kinsy was an assistant professor in the Department of Computer and Information Systems at the University of Oregon, where he directed the Computer Architecture and Embedded Systems (CAES) Laboratory. From 2013 to 2014, he was a Member of the Technical Staff at the MIT Lincoln Laboratory.
Host: Xuehai Qian, xuehai.qian@usc.edu
More Information: 18.11.13 Michel Kinsy_CENG Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
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Annual Grodins Keynote Lecture
Tue, Nov 13, 2018 @ 03:00 PM - 05:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Kullervo Hynynen, M.Sc., PhD, Professor, University of Toronto (Department of Medical Biophysics and Institute of Biomaterials and Biomedical Engineering)
Talk Title: Non-Invasive Brain Treatments Using Image Guided and Modulated Ultrasound Beams
Series: Annual Grodins Keynote Lecture
Abstract: Non-invasive brain treatments using image-guided and modulated ultrasound beams When combined with imaging-guidance focused ultrasound (FUS) provides means for localized delivery of mechanical energy deep into tissues. This focal energy deposition can modify tissue function via thermal or mechanical interactions with the tissue. MRI-guided hemi-spherical phased array technology with CT based beam modulation has made FUS treatments of brain through intact skull possible in the clinical setting. Thermal ablation of a target in a thalamus has been shown to be effective in the treatment of essential tremor and is now FDA approved. The impact of an ultrasound exposure can be potentiated by intravascular microbubbles that can enhance blood-brain barrier (BBB) permeability for a wide variety of molecules, particles and even cells. The ability to modulate the BBB has been shown to be effective in treatments of many deceases in animal models with initial patient trials showing clinical feasibility. In this talk, the progress in utilizing ultrasound phased array technology for brain treatments will be reviewed and its further potential discussed.
Biography: Dr. Hynynen received his PhD from the University of Aberdeen, United Kingdom. After completing his postdoctoral training in biomedical ultrasound also at the University of Aberdeen, he accepted a faculty position at the University of Arizona. After, he joined the faculty at the Harvard Medical School, and Brigham and Women's Hospital in Boston, MA. There he reached the rank of full Professor, and founded and directed the Focused Ultrasound Laboratory. In 2006 he moved to the University of Toronto. He is currently the Director of Physical Sciences Platform at the Sunnybrook Research Institute and a Professor in the Department of Medical Biophysics and Cross Appointed Professor at the Institute of Biomaterials & Biomedical Engineering (IBBME) at the University of Toronto. His research focuses on utilizing focused ultrasound for non-invasive, image-guided interventions. His work in the brain spans from developing devices and methods for focal tissue ablation in clinical testing to research for targeted drug and cell delivery and stroke treatments.
Host: Professor Kirk Shung
More Information: 2018 Fred S. Grodins Keynote Speaker Kullervo Hynynen.pdf
Location: Michelson Center for Convergent Bioscience (MCB) - 101
Audiences: BME graduate students, Faculty, contact department if interested (213-740-7237)
Contact: Mischalgrace Diasanta
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Epstein Institute Seminar - ISE 651
Tue, Nov 13, 2018 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Hui Yang, Associate Professor, Penn State
Talk Title: Sensor-based Modeling and Control of Nonlinear Dynamics for Advanced Manufacturing and Smart Health
Host: Professor Julie Higle
More Information: November 13, 2018.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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CAIS Seminar: Dr. Sanmay Das (Washington University in St. Louis) - Allocating Scarce Societal Resources Based on Predictions of Outcomes
Tue, Nov 13, 2018 @ 03:30 PM - 04:50 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Sanmay Das, Washington University in St. Louis
Talk Title: Allocating Scarce Societal Resources Based on Predictions of Outcomes
Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series
Abstract: Demand for resources that are collectively controlled or regulated by society, like social services or organs for transplantation, typically far outstrips supply. How should these scarce resources be allocated? In this talk, Dr. Das will discuss his work on weighted matching and assignment in two domains, namely living donor kidney transplantation and provision of services to homeless households. His focus will be on how effective prediction of the outcomes of matches has the potential to dramatically improve social welfare both by allowing for richer mechanisms and by improving allocations. He will also discuss implications for equity and justice.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Dr. Sanmay Das is an associate professor in Computer Science and Engineering and the chair of the steering committee of the newly formed Division of Computational and Data Sciences at Washington University in St. Louis. He is vice-chair of the ACM Special Interest Group on Artificial Intelligence and a member of the board of directors of the International Foundation for Autonomous Agents and Multiagent Systems. Dr. Das has served as program co-chair of the AAMAS and AMMA conferences, and has been recognized with awards for research and teaching, including an NSF CAREER Award and the Department Chair Award for Outstanding Teaching at Washington University.
Host: Milind Tambe
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Mork Family Department of Chemical Engineering and Materials Science Seminar - Distinguished Lecture Series
Tue, Nov 13, 2018 @ 04:00 PM - 05:20 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Prof. Matthew Lazzara, Departments of Chemical Engineering and Biomedical Engineering, University of Virginia
Talk Title: Applications of mechanistic and data-driven models to problems in cell signaling
Abstract: Cells are signaled to proliferate, migrate, differentiate, and die through the action of receptors, membrane-spanning proteins that translate extracellular ligand binding events into cellular decisions by initiating networks of intracellular biochemical reactions. The complexity of these problems is ideal for, and often requires, application of computational modeling approaches to interpret data, predict system performance, and generate new hypotheses. However, the specific modeling approach must be tailored to the type and scope of problem at hand. While some problems are sufficiently circumscribed for use of familiar mechanistic governing equations, others are more easily tackled by first seeking statistical inferences from large data sets for which mechanistic governing equations are unknown. This seminar will cover examples of both types of problems. In the first part of the talk, I will describe our lab s efforts to develop experimentally validated mechanistic models of the regulation of epidermal growth factor receptor (EGFR) signaling by protein tyrosine phosphatases, focusing on the coupling between receptor endocytosis and dephosphorylation and on phosphatase-mediated regulation of the persistence of EGFR-driven signaling protein complexes. In the second part of the talk, I will describe our recent efforts to apply data-driven modeling approaches for the rational design of combination therapies for pancreas and brain cancers.
Biography: Matthew Lazzara received a B.S. in Chemical Engineering (with highest honors) from the University of Florida and a Ph.D. in Chemical Engineering from the Massachusetts Institute of Technology, where he trained in the lab of William Deen. He remained at MIT for postdoctoral studies in the lab of Douglas Lauffenburger and was the recipient of an NIH Ruth L. Kirschstein National Research Service Award Postdoctoral Fellowship. Dr. Lazzara is presently Associate Professor of Chemical Engineering and holds a joint appointment in the Department of Biomedical Engineering. Work in the Lazzara Lab employs a combination of experimental and computational methods to study problems in cell signaling, the complex biochemical process cells use to make decisions. Current projects focus on the rational (model-driven) identification of combination therapies for cancer and on fundamental studies of the spatiotemporal regulation of cell signaling by phosphatases and receptor trafficking. The lab's work is funded by grants from the American Cancer Society, National Science Foundation, and National Institutes of Health. Dr. Lazzara is also the recipient of several teaching awards, including the S. Reid Warren, Jr. Award and the Outstanding Faculty Award of the AIChE Delaware Valley, and is a member of the Board of Directors of the Museum of Science and Industry in Tampa, FL.
Host: Prof. Nicholas Graham
Location: John Stauffer Science Lecture Hall (SLH) - 200
Audiences: Everyone Is Invited
Contact: Karen Woo/Mork Family
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Astani Civil and Environmental Engineering Seminar
Wed, Nov 14, 2018 @ 11:30 AM - 12:30 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Mohammed Alnaggar, Ph.D., Rensselaer Polytechnic University
Talk Title: Predicting Reinforced Concrete Aging and Deterioration: Experiments or Modeling?
Abstract: See attachment.
Host: Dr. Parick Lynett and Dr. Bora Gencturk
More Information: Nov 14 Mohammed Alnaggar Civil Engineering Seminar.pdf
Location: Ray R. Irani Hall (RRI) - 101.
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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Meet USC: Admission Presentation, Campus Tour, and Engineering Talk
Fri, Nov 16, 2018
Viterbi School of Engineering Undergraduate Admission
University Calendar
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!
RSVPLocation: Ronald Tutor Campus Center (TCC) - USC Admission Office
Audiences: Everyone Is Invited
Contact: Rebecca Kinnon
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W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM
Fri, Nov 16, 2018 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Garret Reisman, USC Professor of Astronautical Engineering, former NASA astronaut, former SpaceX Director of Space Operations
Talk Title: Human Spaceflight - Recent Past and Near Future
Host: EHP and Dr. Prata
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Amanda McCraven
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MASCLE Machine Learning Seminar: Ahmad Beirami (Electronic Arts) - Powering Games with Data & AI
Fri, Nov 16, 2018 @ 02:00 PM - 03:50 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ahmad Beirami, Electronic Arts
Talk Title: Powering Games with Data & AI
Series: Computer Science Colloquium
Abstract: At EA Digital Platform - Data & AI, we build centralized data-driven and AI-assisted services that power games. In this talk, we begin with an introduction to our data infrastructure and AI platform, that constitute a solid bedrock for solving practical AI problems. We overview several AI applications built on this platform to improve the gameplay experience for hundreds of millions across the globe in addition to contributing scientifically to the research community. We finish with a discussion on the open problems that we are currently tackling.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Ahmad Beirami is a research scientist with Electronic Arts (EA) leading fundamental research and development on training artificial agents in multi-agent systems. His research interests broadly include AI, machine learning, statistics, information theory, and networks. Prior to joining EA in 2018, he held postdoctoral fellow positions at Duke, MIT, and Harvard. He is the recipient of the 2015 Sigma Xi Best PhD Thesis Award from Georgia Tech.
Host: Yan Liu, USC Machine Learning Center
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Intermittent Computing Systems
Fri, Nov 16, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Brandon Lucia, Carnegie Mellon University
Talk Title: Intermittent Computing Systems
Abstract: The emergence of extremely low-power computing components and efficient energy-harvesting power systems has led to the creation of computer systems that operate using tiny amounts of energy scavenged from their environment. These devices create opportunities for systems where batteries and tethered power are inapplicable: sensors deeply embedded in pervasive civil infrastructure, in-body health monitors, and devices in extreme environments like glaciers, volcanoes, and space. The key challenge is that these devices operate only intermittently, as energy is available, requiring both hardware and software to tolerate power failures that may happen hundreds of times per second. This talk will describe the landscape of intermittent computing systems. I will focus on new programming and execution models that are robust to arbitrarily frequent power failures. In particular, the talk will focus on three models, DINO, Chain, and Alpaca, which we developed as a progression toward a system that is simple to program and offers reliable intermittent operation. I will then discuss how these models interact with our latest hardware platform, Capybara, enabling applications to dynamically re-configure the amount of energy continuously required by a region of code and supporting modal energy demands with a single hardware mechanism. I will close with a discussion of recent and upcoming deployment efforts for our intermittent systems work.
Biography: Brandon Lucia is an Assistant Professor of Electrical and Computer Engineering at Carnegie Mellon University. Lucia's lab's work spans programming languages, software and hardware computer systems, and computer architecture. Lucia's lab is defining the area of intermittent computing on energy-harvesting devices, and working on future reliable, efficient parallel computing systems, especially at the edge. Lucia's work has been recognized with a 2018 NSF CAREER Award, the 2018 ASPLOS Best Paper Award, three IEEE MICRO Top Picks in Computer Architecture, a 2015 OOPSLA Best Paper Award, the 2015 Bell Labs Prize, a 2016 Google Faculty Award, and an appointment to the DARPA ISAT study group. His website is https://brandonlucia.com and more information on his lab, which is supported by NSF, Intel, Google, SRC, DARPA, the Kavcic-Moura Fund, and Disney Research, is available at http://intermittent.systems.
Host: Xuehai Qian, xuehai.qian@usc.edu
More Information: 18.11.16 Brandon Lucia_CENG Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Brienne Moore
