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Events for March 29, 2019

  • Meet USC: Admission Presentation, Campus Tour, and Engineering Talk

    Fri, Mar 29, 2019

    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!

    RSVP

    Location: Ronald Tutor Campus Center (TCC) - USC Admission Office

    Audiences: Everyone Is Invited

    Contact: Viterbi Admission

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  • Architecture and Runtime for Scalable Quantum Computers

    Fri, Mar 29, 2019 @ 10:30 AM - 12:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Moinuddin Qureshi , Georgia Institute of Technology

    Talk Title: Architecture and Runtime for Scalable Quantum Computers

    Abstract: Quantum computing promise exponential speedups for a class of important problems. However, this potential can be realized only by large-scale quantum systems that operate on a large number of qubits. Unfortunately, to build a scalable quantum computer several challenges must be overcome, including the design of conventional computing and memory systems that can effectively interface with the quantum substrate while obeying the thermal and power constraints dictated by the quantum devices. In this, talk, I will discuss some of our recent work in addressing the design challenges for the control computer for scalable quantum computers.

    First, I will discuss our QuEST architecture from MICRO-50 that deals with taming the instruction bandwidth of quantum computers via hardware-managed Error Correction. Qubits are fickle and require continuous error correction. This can require an instruction bandwidth that must scale linearly with the number of qubits and can limit the scalability if error correction is managed in software. QuEST delegates the task of error correction to the hardware and uses programmable microcode to reduce the instruction bandwidth requirements. Second, I will discuss the feasibility of using DRAM-based memory system for Quantum Computers. Quantum computers will require significant memory that can operate at cryogenic temperatures. We characterized commodity DRAM at cryogenic environments and examined the minimum operating temperatures and nature of faults. Finally, I will discuss our upcoming work at ASPLOS 2019 that exploits variation in device error rate to improve the overall reliability of near-term quantum computers.


    Biography: Moinuddin Qureshi is a Professor of Electrical and Computer Engineering at the Georgia Institute of Technology. His research interests include computer architecture, memory systems, hardware security, and quantum computing. Previously, he was a research staff member (2007-2011) at IBM T.J. Watson Research Center, where he developed the caching algorithms for Power-7 processors. He is a member of the Hall of Fame for ISCA, MICRO, and HPCA. His research has been recognized with the best paper award at MICRO 2018, best paper award at HiPC, and two selections (and three honorable mentions) at IEEE MICRO Top Picks. His ISCA 2009 paper on Phase Change Memory was awarded the 2019 Persistent Impact Prize in recognition of exceptional impact on the fields of study related to non-volatile memories. He was the Program Chair of MICRO 2015 and Selection Committee Co-Chair of Top Picks 2017. He received his Ph.D. (2007) and M.S. (2003) from the University of Texas at Austin


    Host: Xuehai Qian, xuehai.qian@usc.edu

    More Information: 190329_Moinuddin Qureshi.pdf

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

    Audiences: Everyone Is Invited

    Contact: Brienne Moore

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  • Astronautical Engineering (ASTE) - Seminar

    Fri, Mar 29, 2019 @ 11:00 AM - 12:00 PM

    Astronautical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Prof. Jonathan Black, Virginia Tech

    Talk Title: Autonomy and Machine Learning in Space and Space Domain Awareness

    Abstract: As resident space object populations grow, and satellite propulsion capabilities improve, it is becoming increasingly challenging for space-reliant nations to maintain space situational awareness using current human-in-the-loop methods. This presentation describes several real-time adaptive approaches to autonomous sensor network management for tracking multiple maneuvering and non-maneuvering satellites with a diversely populated Space Object Surveillance and Identification network. The methods integrate suboptimal Partially Observed Markov Decision Processes (POMDPs) with covariance inflation or multiple model adaptive estimation techniques to task sensors and maintain viable orbit estimates for all targets. Like in real-world situations, the population of target satellites vastly outnumbers the available set of sensors. Robust and adaptable tasking algorithms are needed in this scenario to determine how and when sensors should be tasked. The strategies successfully track hundreds of non-maneuvering and maneuvering spacecraft using only dozens of ground and space-based sensors. The results show that multiple model adaptive estimation coupled with a multi-metric, suboptimal POMDP can effectively and efficiently task a diverse network of sensors to track multiple maneuvering spacecraft, while simultaneously monitoring a large number of non-maneuvering objects. Overall, this work demonstrates the potential for autonomous and adaptable sensor network command and control for real-world space situational awareness.

    Biography: Professor, Department of Aerospace and Ocean Engineering; Director, Aerospace and Ocean Systems Laboratory; Virginia Tech

    Host: Astronautical Engineering - Mike Gruntman

    More Information: 2019_03_29_ASTE-Seminar_Prof-Black_flier.pdf

    Location: Vivian Hall of Engineering (VHE) - 217

    Audiences: Everyone Is Invited

    Contact: Mike Gruntman

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  • W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM

    Fri, Mar 29, 2019 @ 01:00 PM - 01:50 PM

    USC Viterbi School of Engineering

    Conferences, Lectures, & Seminars


    Speaker: Mr. Chris Tremmel and Mr. Vik Saraf, Co-General Managers, Jam City LA Studio

    Talk Title: The Business of Mobile Gaming

    Host: EHP and Dr. Prata

    Location: Henry Salvatori Computer Science Center (SAL) - 101

    Audiences: Everyone Is Invited

    Contact: Amanda McCraven

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  • J. Joshua Yang Seminar- Friday, March 29th at 2PM in EEB 132

    Fri, Mar 29, 2019 @ 02:00 PM - 03:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: J. Joshua Yang, University of Massachusetts

    Talk Title: Unconventional Computing With Memristive Devices

    Abstract: Memristive devices have become a promising candidate for energy-efficient and high-throughput unconventional computing, which is a key enabler for artificial intelligent systems in the big data and IoT era. The computing can be implemented on a Resistive Neural Network with memristive synapses and neurons or a Capacitive Neural Network with memcapacitive synapses and neurons. In this talk, I will first briefly introduce the promises and challenges of memristive devices and the key ideas behind bio-inspired computing. I will then discuss a few examples selected from our recent experimental demonstrations of unconventional computing using memristive networks with different levels of bio-inspiration: first, deep learning accelerators with supervised online learning; second, neuromorphic computing for pattern classification with unsupervised learning; last, other computing applications, such as reinforcement learning for decision making, artificial nociceptors for robotics, provable key destruction and true random number generators for cybersecurity.

    Biography: Dr. J. Joshua Yang is a professor of the Department of Electrical and Computer Engineering at the University of Massachusetts, Amherst. Before joining UMass in 2015, he spent eight years at HP Labs and led the Memristive Materials and Devices team since 2012. His current research interests are Nanoelectronics and Nanoionics for computing and artificial intelligent systems, where he authored and co-authored over 140 technical papers and holds 110 granted and 55 pending US Patents. His MRAM patents were licensed by Intel, RRAM patents were technology-transferred to SK-hynix for memory development and recent patents at UMass led to a spin-off company on AI accelerators. He was named as a Spotlight Scholar of UMass Amherst in 2017. He obtained his PhD from the University of Wisconsin - Madison in the Material Science Program in 2007.

    Host: ECE-Electrophysics

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

    Audiences: Everyone Is Invited

    Contact: Marilyn Poplawski

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  • Astronautical Engineering (ASTE) - Seminar

    Fri, Mar 29, 2019 @ 02:00 PM - 03:00 PM

    Astronautical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Prof. Jonathan Black, Virginia Tech

    Talk Title: Autonomy and Machine Learning in Space and Space Domain Awareness

    Abstract: As resident space object populations grow, and satellite propulsion capabilities improve, it is becoming increasingly challenging for space-reliant nations to maintain space situational awareness using current human-in-the-loop methods. This presentation describes several real-time adaptive approaches to autonomous sensor network management for tracking multiple maneuvering and non-maneuvering satellites with a diversely populated Space Object Surveillance and Identification network. The methods integrate suboptimal Partially Observed Markov Decision Processes (POMDPs) with covariance inflation or multiple model adaptive estimation techniques to task sensors and maintain viable orbit estimates for all targets. Like in real-world situations, the population of target satellites vastly outnumbers the available set of sensors. Robust and adaptable tasking algorithms are needed in this scenario to determine how and when sensors should be tasked. The strategies successfully track hundreds of non-maneuvering and maneuvering spacecraft using only dozens of ground and space-based sensors. The results show that multiple model adaptive estimation coupled with a multi-metric, suboptimal POMDP can effectively and efficiently task a diverse network of sensors to track multiple maneuvering spacecraft, while simultaneously monitoring a large number of non-maneuvering objects. Overall, this work demonstrates the potential for autonomous and adaptable sensor network command and control for real-world space situational awareness.

    Biography: Professor, Department of Aerospace and Ocean Engineering; Director, Aerospace and Ocean Systems Laboratory; Virginia Tech

    Host: Astronautical Engineering - Mike Gruntman

    More Information: 2019_03_29_ASTE-Seminar_Prof-Black_flier.pdf

    Location: Vivian Hall of Engineering (VHE) - 217

    Audiences: Everyone Is Invited

    Contact: Mike Gruntman

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