{"id":15338,"date":"2019-12-18T18:06:46","date_gmt":"2019-12-18T22:06:46","guid":{"rendered":"https:\/\/www.samsi.info\/?page_id=15338"},"modified":"2020-07-29T15:46:55","modified_gmt":"2020-07-29T19:46:55","slug":"2020-data-science-statistics-and-visualisation-conference-july-29-31-2020","status":"publish","type":"page","link":"https:\/\/www.samsi.info\/programs-and-activities\/research-workshops\/2020-data-science-statistics-and-visualisation-conference-july-29-31-2020\/","title":{"rendered":"Data Science, Statistics & Visualization 2020 – July 29-31, 2020"},"content":{"rendered":"

\"\"<\/a><\/h2>\n

<\/h2>\n

Due to COVID-19 this conference will be presented virtually July 29-31, 2020.\u00a0\u00a0<\/span><\/strong><\/h5>\n

Registration is now closed<\/strong><\/h3>\n
By registering for this conference you (1) consent to the use of your personal information for the purpose of processing this registration, (2) agree that the conference may include your name, affiliation, and country of residence on the list of attendees, and (3) agree that the organizers may use that information to contact you with updates about this conference and future events.<\/h5>\n

Participants are expected to adhere to the ISI and Associations Individual Conduct Policy<\/a><\/em><\/p>\n

Description:<\/strong><\/h3>\n

Data Science, Statistics & Visualisation (2020)<\/strong> is a virtual conference aimed at bringing together researchers and practitioners interested in the interplay of statistics, computer science, and visualization, and to build bridges between these fields.\u00a0 We shall create a forum to discuss recent progress and emerging ideas in these adjacent disciplines and encourage informal contacts and discussions among all the participants. The conference highlights contributions to practical applications, and in particular those which are linking and integrating these subject areas. Presentations will be oriented towards a very wide scientific audience and will cover topics such as machine learning, the visualization of data, big data infrastructures and analytics, interactive learning, advanced computing, and other important themes.<\/p>\n

In order to encourage networking during this virtual conference, it will be possible to set up (virtual) meetings with other participants.<\/em><\/p>\n

Speakers<\/a><\/strong><\/h3>\n

Speaker Titles\/Abstracts<\/strong><\/a><\/h3>\n

Posters<\/a><\/strong><\/h3>\n

(Posters will be presented in 30 minute parallel sessions. Participants can virtually attend the sessions to discuss posters with the presenters.)<\/em><\/p>\n

Conference Program<\/strong><\/a><\/h3>\n

Wednesday, July 29, 2020<\/strong>
\n<\/strong>Virtual – U.S. New York\/Eastern Daylight Time<\/em><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Time<\/th>\nDescription<\/th>\nSpeaker<\/th>\nSlides<\/th>\nVideos<\/th>\n<\/tr>\n<\/thead>\n
8:00-8:50<\/td>\nTest Audio\/Visual<\/td>\nJoin the “Click Here to Test Audio\/Video Connections” session by navigating to the “Agenda” tab in Whova. (Note: we will not be able to assist with audio\/visual issues once the meeting has begun)<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
9:00-9:10<\/td>\nOpening<\/td>\nDavid Banks<\/strong>, Duke University and SAMSI<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
9:10-10:00<\/td>\nPlenary Talk<\/td>\nChair:\u00a0David Banks<\/strong>, Duke University and SAMSI<\/p>\n

Cynthia Rudin<\/strong>, Duke University
\nSeeing into Data and Models<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
10:00-10:10<\/td>\nBreak<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
10:10-11:25<\/td>\nParallel Sessions<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
<\/td>\n\u00a0 Statistical Learning<\/td>\nOrg: Patrick Groenen<\/strong>, Erasmus University
\nChun-houh Chen<\/strong>, Academia Sinica
\nCovariate-adjusted Heatmaps for Visualizing Biological Data via Correlation Decomposition<\/em><\/p>\n

Patrick Groenen<\/strong>, Erasmus University
\nInterpretable Kernels for Explainable AI<\/em><\/p>\n

Mikhail Zehlonkin<\/strong>, Erasmus University
\nProbabilistic Forecasting of Binary Outcomes in the Presence of Outliers<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
<\/td>\n\u00a0 Statistical Learning<\/td>\nOrg:\u00a0 Jason Xu<\/strong>, Duke University
\nJason Xu<\/strong>, Duke University
\nA Proximal Distance Algorithm for Likelihood-Based Sparse Covariance Estimation<\/em><\/p>\n

Tianxi Li<\/strong>, University of Virginia
\nLinear Regression and its Inference on Noisy Network-linked Data<\/em><\/p>\n

Aaron J. Molstad<\/strong>, University of Florida
\nInsights and Algorithms for the Multivariate Square-root Lass<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
<\/td>\n\u00a0 Reproducible Computing and Reporting<\/td>\nOrg:\u00a0 Jim Harner<\/strong>, West Virginia University
\nDirk Eddelbuettel<\/strong>, U of Illinois at Urbana-Champaign
\nReliable Reproducible Research via Containers from the Rocker Project<\/em><\/p>\n

Brian Lee Yung Rowe<\/strong>, Pez.AI
\nAchieving Practical Reproducibility with Transparency and Accessibility<\/em><\/p>\n

Jim Harner<\/strong>, West Virginia University;\u00a0Chris Grant<\/strong>, Rc2ai;\u00a0Mark Lilback<\/strong>, Rc2ai
\nReproducible Computing and Reporting in a Complex Software Environment<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
11:25-11:35<\/td>\nBreak<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
11:35-12:50<\/td>\nParallel Sessions<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
<\/td>\n\u00a0 Visualisation<\/td>\nOrg:\u00a0 Adalbert Wilhelm<\/strong>, Jacobs University
\nAdalbert Wilhelm<\/strong>, Jacobs University
\nVisual Story Telling of Covid-19: A Case Study<\/em><\/p>\n

Xiaoyue \u201cZoe\u201d Cheng, <\/strong>University of Nebraska
\nVisually Exploring Age-based Population Data over Time<\/em><\/p>\n

Heike Hofmann<\/strong>, Iowa State University
\nVisualizing Elections in the U.S.<\/em><\/p>\n

Susan Vanderplas<\/strong>, University of Nebraska-Lincoln
\nPerception and Visual Communication in a Global Pandemic<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
<\/td>\n\u00a0 Statistical Learning<\/td>\nOrg.:\u00a0 Peter Filzmoser<\/strong>, TU Wien
\nSugnet Lubbe<\/strong>, University of Stellenbosch
\nComparison of Zero Replacement Strategies for Compositional Data with Large Numbers of Zeros<\/em><\/p>\n

Dorit Hammerling<\/strong>, Colorado School of Mines
\nContained Chaos: Ensemble Consistency Testing for the Community Earth System Model<\/em><\/p>\n

Matey Neykov<\/strong>, Carnegie Mellon University
\nHigh-Temperature Structure Detection in Ferromagnets<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
<\/td>\n\u00a0 Data Science<\/td>\nOrg.:\u00a0 Ruda Zhang<\/strong>, SAMSI
\nRuda Zhang<\/strong>, SAMSI
\nNormal-bundle Bootstrap<\/em><\/p>\n

Deborshee Sen<\/strong>, SAMSI
\nBayesian Neural Networks and Dimensionality Reduction<\/em><\/p>\n

Jason Poulos<\/strong>, SAMSI
\nRetrospective Causal Prediction via Elapsed-Time and Propensity-Weighted Matrix Completion, with an Evaluation of the Effect of European Integration on Labour Market Outcomes<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
12:50<\/td>\nAdjourn<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Thursday, July 30, 2020<\/strong>
\n<\/strong>Virtual – U.S. New York\/Eastern Daylight Time<\/em><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Time<\/th>\nDescription<\/th>\nSpeaker<\/th>\nSlides<\/th>\nVideos<\/th>\n<\/tr>\n<\/thead>\n
8:00-8:50<\/td>\nTest Audio\/Visual<\/td>\nJoin the “Click Here to Test Audio\/Video Connections” session by navigating to the “Agenda” tab in Whova. (Note: we will not be able to assist with audio\/visual issues once the meeting has begun)<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
9:00-10:15<\/td>\nParallel Sessions<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
<\/td>\n\u00a0 Statistical Learning<\/td>\nOrg:\u00a0 Kohei Adachi<\/strong>, Osaka University
\nKohei Adachi, <\/strong>Osaka University, Japan
\nPrincipal Component versus Factor Analyses with their Intermediate Procedure in Matrix Decomposition Formulation<\/em><\/p>\n

Inge Koch<\/strong>, University of Western Australia
\nPrincipal Components for High-Dimensional and Directional Data<\/em><\/p>\n

Giuseppe Vinci<\/strong>, Rice University
\nGraph Quilting: Graphical Model Selection from Partially Observed Covariances<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
<\/td>\nData Science<\/td>\nOrg:\u00a0 John Nardini<\/strong>, SAMSI
\nJohn Nardini<\/strong>, SAMSI
\nLearning Differential Equation Models for Noisy Biological Data<\/em><\/p>\n

Glen Wright Colopy<\/strong>. Cenduit
\nPersonalized Inference Protects Patients and Science<\/em><\/p>\n

Xinyi Li<\/strong>, SAMSI
\nSparse Learning and Structure Identification for Ultra-High-Dimensional Image-on-Scalar Regression<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
10:15-10:25<\/td>\nBreak<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
10:25-11:15<\/td>\nPlenary Talk<\/td>\nChair: Patrick Groenen<\/strong>, Erasmus University<\/p>\n

David Dunson<\/strong>, Duke University
\nGeneralized Bayes for Probabilistic Uncertainty Quantification in Unsupervised Learning<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
11:15-11:25<\/td>\nBreak<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
11:25-12:40<\/td>\nParallel Sessions<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
<\/td>\n\u00a0 Statistical Computing<\/td>\nOrg:\u00a0 Richard Samworth<\/strong>, University of Cambridge
\nHao Chen<\/strong>, University of California, Davis
\nChange-point Analysis for Modern Data<\/em><\/p>\n

Yining Chen<\/strong>, London School of Economics
\nJump or Kink: Super-efficiency in Segmented Linear Regression Break-point Estimation<\/em><\/p>\n

Tengyao Wang<\/strong>, University College London
\nHigh-Dimensional, Multiscale Online Changepoint Detection<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
<\/td>\n\u00a0 Data Science Technology<\/td>\nOrg: Jim Harner<\/strong>, West Virginia University
\nJavier Luraschi<\/strong>, RStudio
\nTraining ImageNet Using TensorFow and R<\/em><\/p>\n

Soren Harner<\/strong>, LayerJot & Jim Harner<\/strong>, West Virginia University
\nHarnessing Big Data and Machine Learning with Arrow Data Frames in R and Python<\/em><\/p>\n

Shih-Hsiung Chou<\/strong> & Phil Turk<\/strong>, Atrium Health
\nCURVE: a Web Application for In-Hospital Resource Forecasting During the COVID-19 Outbreak<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
<\/td>\n\u00a0 New Ideas for Old Problems<\/td>\nOrg: Deborshee Sen<\/strong>, SAMSI
\nPulong Ma<\/strong>, SAMSI
\nMultifidelity Computer Model Emulation with High-Dimensional Output: An Application to Storm Surge<\/em><\/p>\n

Kate Moore<\/strong>, Wake Forest University<\/span>
\nCommunities in Data<\/em><\/span><\/p>\n

Wenjia Wang<\/strong>, SAMSI<\/span>
\nUncertainty Quantification for Bayesian Optimization<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
12:40<\/td>\nPoster Session<\/td>\n<\/td>\n<\/tr>\n
1:10<\/td>\nAdjourn<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Friday, July 31, 2020<\/strong>
\n<\/strong>Virtual – U.S. New York\/Eastern Daylight Time<\/em><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Time<\/th>\nDescription<\/th>\nSpeaker<\/th>\nSlides<\/th>\nVideos<\/th>\n<\/tr>\n<\/thead>\n
8:00-8:50<\/td>\nTest Audio\/Visual<\/td>\nJoin the “Click Here to Test Audio\/Video Connections” session by navigating to the “Agenda” tab in Whova. (Note: we will not be able to assist with audio\/visual issues once the meeting has begun)<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
9:00-9:50<\/td>\nPlenary Talk<\/td>\nChair: Peter Filzmoser<\/strong>, TU Wien<\/p>\n

Robert Gramacy<\/strong>, Virginia Polytechnic
\nReplication\u00a0or\u00a0Exploration? Sequential Design for Stochastic Simulation Experiments<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
9:50-10:00<\/td>\nBreak<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
10:00-11:15<\/td>\nParallel Sessions<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
<\/td>\n\u00a0 JDSSV<\/td>\nOrgs: Patrick Groenen<\/strong>, Erasmus University & Stefan Van Aelst<\/strong>, KU Leuven
\nAndreas Alfons<\/strong>, Erasmus University
\nCellwise and Rowwise Robust Regression with Compositional Covariates<\/em><\/p>\n

Eun-Kyung Lee<\/strong>, Ewha Woman’s University<\/span>
\nTree-structured Models using Projection Pursuit Method and their Explanation<\/em><\/p>\n

Mu Zhu<\/strong>, University of Waterloo
\nSome Statistical Applications of Generative Neural Networks
\n<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
<\/td>\n\u00a0 SAS<\/td>\nOrgs:\u00a0 Brett Wujek<\/strong>, SAS Institute
\nXan Gregg<\/strong>, SAS Institute
\nUnderstanding Smoothers through Interactive Examples<\/em><\/p>\n

Kelci Miclaus<\/strong>, JMP Lifesciences
\nThe Role of Visualization in Translational and Clinical Research<\/em><\/p>\n

Guohui Wu<\/strong>, SAS Institute
\nLocation matters: Estimating Spatial Regression Models with Large Spatial Weights Matrices using SAS Econometrics<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
11:15-11:25<\/td>\nBreak<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
11:25-12:15<\/td>\nPlenary Talk<\/td>\nChair:\u00a0David Banks<\/strong>, Duke University and SAMSI<\/p>\n

Ming Yuan<\/strong>, Columbia University
\nInformation Based Complexity of High Dimensional Sparse Functions<\/em><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
12:15-12:25<\/td>\nClosing<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"excerpt":{"rendered":"

Due to COVID-19 this conference will be presented virtually July 29-31, 2020.\u00a0\u00a0 Registration is now closed By registering for this conference you (1) consent to the use of your personal information for the purpose of processing this registration, (2) agree that the conference may include your name, affiliation, and country of residence on the list […]<\/p>\n","protected":false},"author":4,"featured_media":0,"parent":998,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages\/15338"}],"collection":[{"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/comments?post=15338"}],"version-history":[{"count":144,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages\/15338\/revisions"}],"predecessor-version":[{"id":16573,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages\/15338\/revisions\/16573"}],"up":[{"embeddable":true,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages\/998"}],"wp:attachment":[{"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/media?parent=15338"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}