RED Talks Video Archive

Dr.Tamara G. Kolda

Sandia National Laboratories

Date: October 29, 2018
Time: 6:00 PM
Location: 2203 SAS Hall
Talk Title: Decomposition: A Mathematical Tool for Data Analysis

Tensors are multiway arrays, and these occur naturally in many data analysis. Consider a series of experiments tracking multiple sensors over time, resulting in a three-way tensor of the form experiment-by-sensor-by-time. Tensor decompositions are powerful tools for data analysis that can be used for data interpretation, dimensionality reduction, outlier detection, and estimation of missing data. In this talk, we consider the mathematical, algorithmic, and computational challenges of tensor methods and highlight their wide ranging utility with examples in neuroscience, chemical detection, social network analysis, and more. We discuss several new developments, including a new “generalized” version of tensor decomposition that allows for alternative statistically-motivated fitting functions.
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Dr. Guillermo Sapiro

Duke University

Date: October 15, 2018
Time: 5:00 PM
Location: Duke Energy Hall C/D, Hunt Library, Centennial Campus, NCSU
Talk Title: It’s Your Data and Your Decision: Learning Representations to Keep Your Privacy

It is becoming increasingly clear that users should own and control their data. Utility providers are also becoming more interested in guaranteeing data privacy. As such, users and utility providers should collaborate in data privacy, a paradigm that has not yet been developed in the privacy research community. We introduce this concept and present explicit architectures where the user controls what characteristics of the data she/he wants to share and what she/he wants to keep private. This is achieved by collaborative learning a sensitization function, either a deterministic or a stochastic one, that retains valuable information for the utility tasks but it also eliminates necessary information for the privacy ones. As illustration examples, we implement them using a plug-and-play approach, where no algorithm is changed at the system provider end, and an adversarial approach, where minor re-training of the privacy inferring engine is allowed. In both cases the learned sanitization function keeps the data in the original domain, thereby allowing the system to use the same algorithms it was using before for both original and privatized data. We show how we can maintain utility while fully protecting private information if the user chooses to do so, even when the first is harder than the second, as in the case here illustrated of identity detection while hiding gender. We also present examples showing how secure devices can be designed to protect the privacy of ordinary people around the device. This talk is based on joint work with M. Bertran, N. Martinez, A. Papadaki, Q. Qiu, M. Rodrigues.
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C. Titus BrownC. Titus Brown

UC Davis

Date: September 11, 2018
Time: 6:00 PM
Location: 2203 SAS Hall
Talk Title: The Secret Life of Microbial Genomes

Recent advances in large scale sequencing of microbial DNA without culturing or isolation gives us easy and direct access to “wild” microbial metagenomes that are otherwise virtually impossible to study. Our recent work has focused on studying the ecology and genomics of microbial genomes and “population” pan-genomes in environmental samples, using tools and approaches developed in our lab and in collaboration with others. We see many ways in which microbial genomes do not particularly resemble our naive expectations, which is leading us into some productive confusion around known knowns, known unknowns, and unknown unknowns in environmental microbial systems.Our work relies heavily on novel methods and technical infrastructure development. In this talk I will present a series of vignettes on our techniques and some of the results, aimed at a general scientific audience.
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Dr. Ingrid DaubechiesDr. Ingrid Daubechies

Date: October 10, 2017
Location: Talley Student Union
Talk Title: Mathematicians Helping Art Historians and Art Conservators

In recent years, mathematical algorithms have helped art historians and art conservators putting together the thousands of fragments into which an unfortunate WWII bombing destroyed world famous frescoes by Mantegna, decide that certain paintings by masters were “roll mates” (their canvases were cut from the same bolt), virtually remove artifacts in preparation for a restoration campaign, and even get more insight into paintings hidden underneath a visible one. The presentation will review these applications, and give a glimpse into the mathematical aspects that make this possible.
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Dr. Elliot InmanDr. Elliot Inman

Date: September 27, 2016
Time: 7:00 PM
Location: Mountains Ballroom, Talley Student Union
Talk Title: Quantification: The Art of Making Data

In this Data Science Initiative talk and the DH Hill Makerspace workshops that follow, we will explore the art of making data – from the mechanics of setting up sensors and digitizing information to generating a data structure that will be useful for making sense of that information. We will experiment with a wide variety of data from recorded sound to human touch and even human emotions, building devices to help gather reliable, valid measures.
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Laura HaasDr. Laura Haas

Sandia National Laboratories

Date: October 18th, 2016
Time: 7:00 PM
Location: Duke Energy Hall, Hunt Library
Talk Title: The Power Behind The Throne: Information Integration in the Age of Data-Driven Discovery

Integrating data has always been a challenge. The information management community has made great progress in tackling this challenge, both on the theory and the practice. But in the last ten years, the world has changed dramatically. New platforms, devices and applications have made huge volumes of heterogeneous data available at speeds never contemplated before, while the quality of the available data has if anything degraded.
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Dr. Jeff Leek

Date: November 2nd, 2016
Time: 7:00 PM
Location: Mountains Ballroom, Talley Student Union
Talk Title: Is Most Published Research Really False?

The accuracy of published research is critical for scientists, physicians and patients who rely on these results. But the fundamental belief in the scientific literature was called into serious question by a paper suggesting most published medical research is false. This claim has launched an entire discipline focused on the crisis of reproducibility and replicability of science. In this talk I will discuss two major open problems inspired by this scientific crisis: how do we know when a study replicates and what is the rate of false discoveries in the scientific literature? In answering these questions I will argue that much of the crisis in science can be attributed to misunderstanding statistics.
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Dr. Deen Freelon

Date: March 15th, 2016
Time: 5:30 PM
Location: Mountains Ballroom, Talley Student Union
Talk Title: Toward a Framework for Inferring Individual-Level Characteristics from Digital Trace Data

Digital traces—records of online activity automatically recorded by the servers that undergird all online activity—allow us to explore age-old communication research questions in unprecedented ways. But one of the greatest challenges in doing so is managing the gap between the research’s conceptual focus and the set of readily available traces. Not every type of trace will be equally valuable from a particular research standpoint, and not every interesting concept will be measurable using the traces to which researchers have access.

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