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Events for March 20, 2017

  • CS Colloquium: Yuanjie Li (UCLA) - Stimulating Intelligence in the Mobile Networked Systems

    Mon, Mar 20, 2017 @ 11:00 AM - 12:20 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Yuanjie Li, UCLA

    Talk Title: Stimulating Intelligence in the Mobile Networked Systems

    Series: CS Colloquium

    Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.

    The mobile networked systems (4G and upcoming 5G) are at a critical stage of the technology revolution. Despite offering working solutions for billions of users, they are complex and closed: The infrastructure lacks guarantees for the right designs and operations, while the mobile client lacks the insights of the "black-box" network behaviors. Both fundamentally limit our understanding of why various problems could happen, and how to resolve them.

    In this talk, I describe primitives that stimulate more infrastructure and client intelligence. For the infrastructure, I present verification and state management techniques that enforce provably correct designs and operations. For the client, I show how a data-driven system design allows it to be more active in improving its performance, reliability, and security. These results suggest that the future systems (5G) should be equipped with more intelligence, and make themselves easy to understand and use.

    Biography: Yuanjie Li is a Ph.D. candidate in Computer Science at UCLA, advised by Professor Songwu Lu. His interests include the networked systems, mobile computing, and their security. He has won ACM MobiCom'16 Best Community Paper Award and UCLA Dissertation Year Fellowship in 2016. His work has resulted in an open-source community tool (MobileInsight) used by 130 universities and companies so far.

    Host: CS Department

    Location: Ronald Tutor Hall of Engineering (RTH) - 217

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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  • AI Seminar

    Mon, Mar 20, 2017 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Xiang Ren, Computer Science PhD candidate at University of Illinois at UrbanaChampaign

    Talk Title: EFFORT-LIGHT STRUCTMINE: TURNING MASSIVE CORPORA INTO STRUCTURES

    Series: Recruitng Seminar

    Abstract: The realworld data, though massive, are hard for machines to resolve as they are largely unstructured and in the form of natural-language text. One of the grand challenges is to turn such massive corpora into machine-actionable structures. Yet, most existing systems have heavy reliance on human effort in the process of structuring various corpora, slowing down the development of downstream applications.

    In this talk, I will introduce a data-driven framework, EffortLight StructMine, that extracts structured facts from massive corpora without explicit human labeling effort. In particular, I will discuss how to solve three structure mining tasks under Effort-Light StructMine framework: from identifying typed entities in text, to fine-grained entity typing, to extracting typed relationships between entities. Together, these three solutions form a clear roadmap for turning a massive corpus into a structured network to represent its factual knowledge. Finally, I will share some directions towards mining corpus-specific structured networks for knowledge discovery.


    Biography: Xiang Ren is a Computer Science PhD candidate at University of Illinois at Urbana-Champaign, working with Jiawei Han and the Data and Information System DAIS Research Lab. The research Xiang develops data-driven methods for turning unstructured text data into machine-actionable structures. More broadly, his research interests span data mining, machine learning, and natural language processing, with a focus on making sense of massive text corpora. His research has been recognized with several prestigious awards including a Google PhD Fellowship, a Yahoo!-DAIS Research Excellence Award, and a C. W. Gear Outstanding Graduate Student Award from UIUC Computer Science. Technologies he developed has been transferred to US Army Research Lab, NIH, Microsoft, Yelp and TripAdvisor


    Host: Craig Knoblock

    Webcast: http://webcastermshd.isi.edu/Mediasite/Play/6b83d48fc61f4e398d8d8bbdff0004e01d

    Location: Information Science Institute (ISI) - 11th Floor Large CR #1135

    WebCast Link: http://webcastermshd.isi.edu/Mediasite/Play/6b83d48fc61f4e398d8d8bbdff0004e01d

    Audiences: Everyone Is Invited

    Contact: Alma Nava / Information Sciences Institute

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  • Seminars in Biomedical Engineering

    Mon, Mar 20, 2017 @ 12:30 PM - 01:50 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Zhongping Chen , Professor of Biomedical Engineering, UC Irvine, Beckman Laser Institute

    Talk Title: Novel OCT for Biomedical Application

    Host: Qifa Zhou

    Location: Olin Hall of Engineering (OHE) - 122

    Audiences: Everyone Is Invited

    Contact: Mischalgrace Diasanta

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  • Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems

    Mon, Mar 20, 2017 @ 02:00 PM - 03:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Brian Munsky, Assistant Professor, Colorado State University

    Talk Title: Identification of stochastic models to predict single-cell gene regulation dynamics

    Abstract: Stochastic fluctuations can cause identical cells or individual molecules to exhibit wildly different behaviors. Often labeled "noise," these fluctuations are frequently considered a nuisance that compromises cellular responses, complicates modeling, makes predictive understanding and control all but impossible. However, if we computationally examine fluctuations more closely and carefully match them to discrete stochastic analyses, we discover virtually untapped, yet powerful sources of information and new opportunities. In this talk, I will present our collaborative endeavors to integrate single-cell and single-molecule experiments with precise stochastic analyses to gain new insight and quantitatively predictive understanding for signal-activated gene regulation. I will explain how we experimentally quantify transcription dynamics at high temporal and spatial resolutions; how we use precise computational analyses to model this data and efficiently infer biological mechanisms and parameters; how we predict and evaluate the extent to which model constraints (i.e., data) and uncertainty (i.e., model complexity) contribute to our understanding. We will examine how different data statistics (e.g., expectation values versus probability densities) contribute to model bias and uncertainty, and we will show how these affect predictive power. Finally, we will introduce a new approach to compute the Fisher Information Matrix, and we will illustrate its application for the improved design of single-cell experiments.

    Biography: Dr. Munsky received B.S. and M.S. degrees in Aerospace Engineering from the Pennsylvania State University in 2000 and 2002, respectively, and his Ph.D. in Mechanical Engineering from the University of California at Santa Barbara in 2008. Following his graduate studies, Dr. Munsky worked at the Los Alamos National Laboratory -” as a Director's Postdoctoral Fellow (2008-2010), as a Richard P. Feynman Distinguished Postdoctoral Fellow in Theory and Computing (2010-2013), and as a Staff Scientist (2013). In 2014, he joined the Colorado State University Department of Chemical and Biological Engineering and the School of Biomedical Engineering, in which he is now an Assistant Professor. Dr. Munsky is best known for his discovery of Finite State Projection algorithm, which has enabled the efficient study of probability distribution dynamics for stochastic gene regulatory networks. Dr. Munsky's research interests are in the integration of discrete stochastic models with single-cell experiments to identify predictive models of gene regulatory systems. Dr. Munsky was the recipient of the 2008 UCSB Department of Mechanical Engineering best Ph.D. Dissertation award, the 2010 Leon Heller Postdoctoral Publication Prize, and the 2012 LANL Postdoc Distinguished Performance Award for his work in this topic. Dr. Munsky became a Keck Scholar in 2016. Dr. Munsky is the contact organizer of the internationally recognized, NIH-funded q-bio Summer School (q-bio.org), where he runs a course on single-cell stochastic gene regulation.

    Host: Paul Bogdan

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

    Audiences: Everyone Is Invited

    Contact: Estela Lopez

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