Seminars

  • Streaming Analytics for the Future Grid

    Thu, Dec 12, 2019, 3:00 pm to 4:00 pm

    Abstract:

    How to conduct real-time analytics of streaming measurement data in the power grid? This talk offers a dynamic systems approach to utilizing data of different time scale for improved monitoring of the grid cyber and physical security. This talk presents how to leverage synchrophasor data dimensionality reduction and Robust Principal Component Analysis for early anomaly detection, visualization, and localization. The underlying theme of the work suggests the importance of integrating data with dynamic physical models in the smart grid.

  • Recent Advances in Non-Convex Distributed Optimization and Learning

    Mon, Nov 18, 2019, 4:30 pm to 5:30 pm

    Abstract:

    We consider a class of distributed non-convex optimization problems, in which a number of agents are connected by a communication network, and they collectively optimize a sum of (possibly non-convex and non-smooth) local objective functions. This type of problem has gained some recent popularities, especially in the application of distributed training of deep neural networks.

  • Gaussian Limits in Two Inference Problems

    Mon, Nov 11, 2019, 4:30 pm to 5:30 pm

    Abstract: Distribution limits in large systems are often the key to understanding the fundamental limits or designing algorithms for inference and learning problems. Yet, sometimes, such distribution limit properties are not easily recognized, or only exist in some indirect forms. I would like to discuss two pieces of work with this flavor.

  • Towards Learning with Brain Efficiency

    Thu, Oct 17, 2019, 12:30 pm to 1:30 pm

    Abstract:  Modern computing systems are plagued with significant issues in efficiently performing learning tasks. In this talk, I will present a new brain-inspired computing architecture. It supports a wide range of learning tasks while offering higher system efficiency than the other existing platforms. I will first focus on HyperDimensional (HD) computing, an alternative method of computation which exploits key principles of brain functionality: (i) robustness to noise/error and (ii) intertwined memory and logic.

  • Implantable Electronics for Highly Parallel Neural Interfaces

    Tue, Oct 8, 2019, 4:30 pm to 5:30 pm

    Abstract: Implantable medical devices (IMD) are nowadays widely employed to restore functions to the impaired individuals suffering from diseases like deafness, blindness, cardiac insufficiency, incontinence, neural disorders, and many more. Such implantable systems become increasingly challenging, if a large number of sensing or stimulating sites needs to be realized - space and power budget, safety issues, high bidirectional data rates, as well as the vast number of electrical interfaces make the electronic circuit design a complex task of research and development.

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