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Events for October 14, 2019

  • Engineering Nano-electronics for Enabling Ubiquitous Intelligence

    Mon, Oct 14, 2019 @ 11:00 AM - 12:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Akhilesh Jaiswal, Senior Research Engineer, GLOBALFOUNDRIES Worldwide Research Division

    Talk Title: Engineering Nano-electronics for Enabling Ubiquitous Intelligence

    Abstract: The science of Artificial Intelligence (AI) is built upon multi-disciplinary areas of research such as Nano-, Bio-electronics, and computational engineering. Despite its meticulous design, the underlying hardware fabrics fueling AI systems are based on decades-old computing principles using Boolean transistor switches. Although transistors have scaled from planar to 3D, the basic synchronous digital computing paradigm based on von-Neumann architecture has remained unaltered. Moreover, transistor scaling, which has been the driving force behind the ever-improving performance of traditional digital systems is approaching its imminent demise. These factors have led to multiple bottlenecks in terms of memory-wall, energy-efficiency, throughput, and security concerns. As such, the vision of enabling 'Ubiquitous Intelligence' cannot be achieved without mitigating the challenges mentioned above and embedding intelligent computations across high-end servers down to resource-constrained edge devices. In this talk, I will present two solutions to mitigate energy- and throughput- bottleneck based on emerging non-volatile technologies and also CMOS SRAM. In particular, I will discuss 1) voltage-controlled spin dynamics to achieve massively parallel in-memory Boolean computing, 3) embedding three terminal spin Hall device into standard SRAM cell to enable in-situ checkpointing and restore operations for intermittently powered devices 3) digital 8 transistor-SRAM bit-cells as multi-bit-analog dot product engine for AI acceleration. I will conclude the talk by presenting future research directions for beyond Moore-era AI computing.

    Biography: Akhilesh Jaiswal is currently a Senior Research Engineer for GLOBALFOUNDRIES Worldwide Research Division. As a Senior Engineer he is responsible for 1) developing compact device model for MRAM based AI in-memory circuits 2) enabling AI acceleration through hybrid photonic-electronic neuro-mimetic devices.

    Akhilesh received his Ph.D. degree in Nano-electronics from Purdue University in May 2019 under supervision of Prof. Kaushik Roy and Master's degree from University of Minnesota in May 2014. As a part of doctoral program his research focused on 1) Exploration of bio-mimetic devices and circuits using emerging non-volatile technologies for Neuromorphic computing. 2) CMOS based analog and digital in-memory and near-memory computing using standard memory bit-cells for beyond von-Neumann AI/ML acceleration. Akhilesh was an intern with GF Differentiating Technology Lab, Malta, in summer of 2017 and with ARM Devices-Circuits-System Research Group, Austin, in summer 2018. He has authored over 25+ articles in journals and conferences and has 2 issued patents and 13 pending patents under USPTO.

    Host: Professor Richard Leahy, leahy@sipi.usc.edu

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

    Audiences: Everyone Is Invited

    Posted By: Mayumi Thrasher

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  • Fall 2019 Joint CSC@USC/CommNetS-MHI Seminar Series

    Mon, Oct 14, 2019 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Vasileios Christopoulos, University of California, Riverside

    Talk Title: The acting and adapting brain: Making decisions and learning to adapt in a dynamic world

    Abstract: The ability to select between competing options while acting, and learning to adapt to new situations, underlies our impressive capabilities of playing soccer, flying aircrafts and skiing on the Olympics. Although significant progress has been made on understanding the mechanisms underpinning decision-making and learning, there is no strong consensus on how the brain chooses between actions and adapts to new environmental conditions. I will discuss recent findings from our lab providing evidence that decision-making is not a centralized cognitive process that resides solely within the frontal lobe. Instead, it also includes brain areas that have been traditionally associated with planning and generating actions. By modeling the decision-making process within a neurodynamical framework, I will present an alternative hypothesis according to which decisions emerge via a continuous competition between multiple potential actions. To select between actions, the brain needs an accurate representation of the state of the body and the environment it is in. Despite the sophistication of our sensory system, it is unlikely to extract a complete and accurate representation of the state due to noise and long sensory delays. To avoid instabilities due to these factors, previous work has suggested that the brain builds internal models that predict sensory outcome of motor actions. These predictions are integrated with the incoming sensory feedback to update the estimate of the current state. By recording neural activity from the posterior parietal cortex (PPC) in both humans and non-human primates, I will show that PPC contains an adaptive internal forward model that learns to compensate for delayed visual feedback. I will also discuss clinical brain-machine interface (BMI) studies in human with tetraplegia that have taken steps to elucidate the mechanisms behind the acquisition of new skills and why learning new skills is easier when they are related to already learned abilities. By training a participant to control a computer cursor by modulating the neural activity of PPC neurons, we found that some patterns of activity were generated more easily than others. The easier-to-learn patterns of activity were combinations of pre-existing neuronal patterns, whereas the difficult-to-learn activity patterns were different from the neuronal patterns that the participant had experienced in the past. Importantly, there were neuronal patterns that PPC could not generate indicating that neuroplasticity in learning is constrained by the pre-existing structure of the brain. This fundamental constraint may explain why learning novel tasks can be challenging.

    Biography: Dr. Christopoulos is an Assistant Professor at the Bioengineering Department at the University of California Riverside. He received his Ph.D. in Computer Science and Engineering (with minor in Cognitive Sciences) from the University of Minnesota, Minneapolis in 2010. He then moved to California Institute of Technology (Caltech) to work as a post-doctoral fellow at the Andersens lab. In 2017, he was appointed as Research Faculty at the Division of Biology and Biological Engineering at Caltech and Director of Neurotechnology at the T&C Chen Brain-Machine Interface Center. Dr. Christopoulos research group uses neurophysiological, functional brain-imaging and computational methods to elucidate the mechanisms underlying decision-making, motor learning and spatial awareness, and explore circuit dysfunctions in neurological and psychiatric disorders. In recent years, Dr. Christopoulos extended his research to clinical trials including neural prosthetic applications in individuals with tetraplegia (intracortical Brain-Machine Interface), and deep brain stimulation (DBS) in Parkinson's disease (PD) patients.

    Host: Mihailo Jovanovic, mihailo@usc.edu

    More Info: http://csc.usc.edu/seminars/2019Fall/christopoulos.html

    More Information: 191014_Vasileios Christopoulos_CSC.pdf

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

    Audiences: Everyone Is Invited

    Posted By: Brienne Moore

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  • CILQ Faculty Seminar

    Mon, Oct 14, 2019 @ 04:00 PM - 05:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Salman Avestimehr, Professor/USC

    Talk Title: Coded Computing: A Transformative Framework for Resilient, Secure, and Private Distributed Learning

    Abstract: This talk introduces Coded Computing, a new framework that brings concepts and tools from information theory and coding into distributed computing to mitigate several performance bottlenecks that arise in large-scale distributed computing and machine learning, such as resiliency to stragglers and bandwidth bottleneck. Furthermore, coded computing can enable (information-theoretically) secure and private learning over untrusted workers that is gaining increasing importance in various application domains. In particular, we present CodedPrivateML for distributed learning, which keeps both the data and the model private while allowing efficient parallelization of training across untrusted distributed workers. We demonstrate that CodedPrivateML can provide an order of magnitude speedup (up to ~30x) over the cryptographic approaches that rely on secure multiparty computing.

    Host: CSI

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

    Audiences: Everyone Is Invited

    Posted By: Corine Wong

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  • Astani Civil and Environmental Engineering Seminar

    Mon, Oct 14, 2019 @ 04:00 PM - 05:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Yves Weinand, Director and Head of Laboratory for Timber Construction (IBOIS)

    Talk Title: Advanced Timber Construction Using Digital Fabrication and Robotics Assemblies

    Abstract: Please see Attached.

    Host: Dr. Erik Johnson

    More Information: Y. Weinand Talk_10-14-19.pdf

    Location: Ray R. Irani Hall (RRI) - 101

    Audiences: Everyone Is Invited

    Posted By: Evangeline Reyes

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  • USC Graduate Engineering Info Session: Chennai

    Mon, Oct 14, 2019 @ 06:00 PM - 08:00 PM

    Viterbi School of Engineering Graduate Admission

    Workshops & Infosessions


    TechNext India: A Talk on MS and PhD Programs Rising in Popularity in US

    Who should attend:
    Candidates with a strong academic background and a Bachelor's degree (or those in the process of earning a Bachelor's degree) in engineering, computer science, applied mathematics, or physical science (such as physics, biology, or chemistry) are welcome to attend this session to learn more about graduate and doctoral engineering program trends and about applying to the University of Southern California.

    Topics covered:

    Master's & PhD Programs Trends in the US
    Popular Programs at USC (CS, Mech, Data Science, BioMed, Civil, EM etc.)
    How to Apply
    Scholarships and Funding
    Student Life at USC and in Los Angeles
    Application Tips
    Q & A

    Register Here

    Audiences: Everyone Is Invited

    Posted By: USC Viterbi Graduate Programs

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