Big Data Sessions at 2014 Joint Statistical Meetings

By Steve Pierson posted 04-08-2014 20:11

  

[Update, 6/22/15: see Big Data Sessions at the 2015 Joint Statistical Meetings] 

Because my blog entry last year, Big Data Sessions at JSM, was so well-received, I'm doing it again for the 2014 JSM. The first list is based on titles that contain Big Data (using Quick Search on the JSM 2014 Preliminary Online Program.) The second list is where Big Data appears in the abstract of a talk or session (using Abstract Keyword Search). There is also a 3rd list of talk abstracts containing Data Science. Let me remind people that this list is not exhaustive. Please let me know of any I missed or add them through the comment section below.

Also, after this blog entry appeared last year, someone pointed out the many more sessions at JSM on Causal Inference. Please point out similar omissions this year!

See other ASA Science Policy blog entries. For ASA science policy updates, follow @ASA_SciPol on Twitter.

Sessions or Continuing Ed Courses with Big Data or Data Science in the Title:

Sessions with Big Data in the Abstract: There are 79 of these and probably include talks from the session listed above
Sunday, 08/03/2014
Climate Change, Air Quality and Health: Bayesian Hierarchical Models for Predicting the Change in Mortality Associated with Future Ozone Exposures
Stacey Alexeeff, National Center for Atmospheric Research; Douglas Nychka, National Center for Atmospheric Research; Gabi Pfister, National Center for Atmospheric Research
               
Simulation-based methods in Statistics Education; and Google Tools
Tim Hesterberg, Google
2:30 PM

Clustering and Feature Selection for Big Data
Damir Spisic, IBM; Jing Shyr, IBM; Jing Xu, IBM SPSS
3:20 PM

Analysis of big imaging data via a Bayesian thresholding approach
Jian Kang, Emory University
3:25 PM

Multivariate Spatial Modeling of Conditional Dependence to study arsenic contamination in drinking water
Montserrat Fuentes, North Carolina State University; Joe Guinness, North Carolina State University
4:05 PM

Industrial Internet, an Opportunity for Statisticians to become Data Scientists
Bill Ruh, GE Software Center
4:05 PM

Big Data: Challenges and Opportunities
Nicole Lazar, The University of Georgia
4:25 PM

Efficient data-driven knot selection for reduced rank spatial models
Casey M. Jelsema, National Institute of Environmental Health Sciences (NIEHS); Shyamal Peddada, NIH / NIEHS
4:35 PM

Big Data: Where Does Statistics Research Fit In?
Galit Shmueli, Indian School of Business
4:45 PM

Tackling Big Data with MATLAB
Ameya Deoras, MathWorks
4:45 PM

Big Data for Medical Research - A unified approach for individualized treatment recommendation and subgroup identification based on electronic medical record data
Haoda Fu, Eli Lilly & Company; Jin Zhou, University of Arizona
4:50 PM

Big Data Analytics in ATM Security
Arif Ansari, University of Southern California
5:05 PM

Listening to the World's Oceans: Searching for Marine Mammals by Detecting and Classifying Terabytes of Bioacoustic Data in Clouds of Noise
Christopher W Clark, Cornell University; Peter J Dugan, Cornell University
5:05 PM

Monday, 08/04/2014
Snowden, Google, and Text Networks
David Banks, Duke University


Socio-economic and public records data for health risk assessment and interventions
Donghui Wu, LexisNexis|Risk Solutions|Healthcare; Xin Deng, LexisNexis|Risk Solutions|Healthcare; Ognian Asparouhov, LexisNexis|Risk Solutions|Healthcare


Sentweetmental: Real-time Sentiment Analysis of Tweets
Yue Zeng, Twitter, Inc.; Tianhong He, Twitter


Preparing Students for Big Data using R and RStudio
Randall Pruim, Calvin College
8:35 AM

Deconstruction of Effects by Exposure Dose
William Heavlin, Google Inc.
8:35 AM

Conjoint Parametrers Directed to Isolating "Hot Spots" within Big Data
Turkan K. Gardenier, Pragmatica Corp.; John S. Gardenier, National Center for Health Statistics (Retired)
8:50 AM

Thinking with Data in the Second Course
Nicholas J. Horton, Amherst College; Ben S. Baumer, Smith College; Hadley Wickham, RStudio
8:55 AM

Additive and Interaction Models for Nonparametric Regression of Biomedical Imaging Data, with Applicaton to Ophthalmological Multi-Level Data on the Sphere
Jeffrey S Morris, UT MD Anderson Cancer Center; Veera Baladandayuthapani, UT MD Anderson Cancer Center
9:00 AM

Moving Towards Big Data using Long-Term Projects, Capstones and Culminating Experiences
Julie Marie Legler, St. Olaf College; Paul Roback, St. Olaf College
9:35 AM

Finding Fast Radio Bursts with the Very Large Array
Earl Lawrence, Los Alamos National Laboratory; Scott Vander Wiel, Los Alamos National Observatory
10:35 AM

Big data, big models, big problems: Consensus Monte Carlo methods for distributed Bayesian inference
Alexander Blocker, Google; Steven L Scott, Google; Fernando Bonassi, Google
11:15 AM

From Big Data to Actionable Intelligence in Pro Sports
Alexander Arthur Rucker, Toronto Raptors
11:25 AM

Adaptive Integration of Survey Data with Other Information Sources
John Eltinge, Bureau of Labor Statistics
11:35 AM

Industrial internet: an opportunity for statistician in data science and big data revolution
Ming Li, SAS Institute
2:30 PM

Daytime Population estimations based on Mobile Phone Metadata
Martijn Tennekes, Statistics Netherlands; May Offermans, Statistics Netherlands
2:35 PM

Estimating Networks from Big Neuroimaging Data
Xi Luo, Brown University; Xiaoxing Cheng, Brown University; Yi Zhao, Brown University
3:05 PM

How one government agency is approaching Big Data
Barbara Stevens
3:35 PM

Tuesday, 08/05/2014
What's the Difference Between Data Science and Statistics?
Charles Kincaid, Experis


Data Mining and Data Quality: Can't Have One Without the Other
Tamraparni Dasu, AT&T Labs - Research


Data Science and Statistics: How Should They Fit into Our Curriculum?
Johanna Hardin, Pomona College


Big Data Analysis: Concepts, Methods, and Computation
Sijian Wang, University of Wisconsin


Big Data and Advanced Analytics in Radiology Precision and Preemptive Patient Care
Nasser Fard, Northeastern University; Jean Hosseini, Intelek; Scott Cameron, Medical Clinic


Implementation of statistical algorithms in big data platforms
Martin Wells, Cornell University; Hui Jiang, University of Michigan; Steven L Scott, Google; Xiaoming Huo, NSF
8:35 AM

Analyzing Data at Scale with the Berkeley Data Analytics Stack
Michael Franklin, UC Berkeley
8:35 AM

Big Data from biostatisticians/bioinformaticians' perspective: From Epigenomics to Data Integration
Guo-Cheng Yuan, Harvard School of Public Health
9:25 AM

Big Data and Advanced Analytics in Radiology Precision and Preemptive Patient Care
Nasser Fard, Northeastern University; Jean Hosseini, Intelek; Scott Cameron, Medical Clinic
9:25 AM

Bringing Big Data to Personalized Healthcare: A Patient-Centered Framework
Nitesh Chawla, University of Notre Dame
9:50 AM

Scalable multiscale Bayesian models
David Dunson, Duke University
10:35 AM

Using Record Linkage to Create Big Data? How Good Is It?
K. Bradley Paxton, ADI, LLC
10:35 AM

Uncertainty Quantification for Massive Data Problems using Generalized Fiducial Inference
Thomas C. M, Lee, University of California at Davis; Jan Hannig, University of North Carolina at Chapel Hill; Randy C. S. Lai, UC Davis
10:35 AM

Randomized approximation of principal components analysis for large data sets
Daniel J. McDonald, Indiana University; Darren Homrighausen, Colorado State University
11:00 AM

Using Big Data to Supplement Population Health Surveillance Systems
Carol Gotway Crawford, Centers for Disease Control and Prevention ; Steven Gittleman, Mktg, Inc.
2:05 PM

Using Information from Disparate Sources to Improve Survey Estimates
Linda J Young, USDA National Agricultural Statistics Service
2:30 PM

Text Analytics and Statistics
Terry Woodfield, SAS Institute Inc.
2:55 PM

GPCSIV & GraphPCA : Two R packages for PCA of complex data
Brahim Brahim, BDV (Big Data Visualizations); Sun Makosso-Kallyth, BDV (Big Data Visualizations)
3:05 PM

Parallel MCMC via Weierstrass Sampler
Xiangyu Wang; David Dunson, Duke University
3:25 PM

Wednesday, 08/06/2014
Visualization: Another V Associated with Big Data
John D. McKenzie, Jr., Babson College


Classroom Demonstrations of Big Data
Eric A. Suess, California State University, East Bay


Ethical Issues in Getting it Right: Using Big Data to Determine Medical Treatment
John J. Crowley, Cancer Research And Biostatistics
8:35 AM

Assessing the Ethical Implications of Big Data Sets
Kirsten Martin, George Washington University
8:55 AM

Efficient Dimension Reduction of A Group of High-Dimension Imaging Data
Haipeng Shen, University of North Carolina at Chapel Hill
8:55 AM

Emulation of Global 3D Spatio-Temporal Temperature: A Distributed Computing Approach to Model One Billion Data Points
Stefano Castruccio, KAUST; Marc G. Genton, King Abdullah University of Science and Technology
8:55 AM

High Performance Computing Based on Massive Parallel Processing: Lessons Learned from the NORC Data Enclave
Timothy Mulcahy, NORC At the University of Chicago; Johannes Huessy, NORC at the University of Chicago; Scot Ausborn, NORC at the University of Chicago
9:05 AM

The Legal and Regulatory Framework for the Analysis of Big Data
Paul Ohm, University of Colorado Law School
9:15 AM

Mining Solar Big Data with the Flare Detective
Henry "Trae" Winter III, Harvard
9:25 AM

Ethical issues in the collection and use of consumer and social data
Richard D. De Veaux, Williams College
9:35 AM

Mobile Phone Metadata: a new source for Official Statistics
May Offermans, Statistics Netherlands; Martijn Tennekes, Statistics Netherlands
9:50 AM

Statistics with Large astronomical Data Sets
Alex Szalay, The Johns Hopkins University
9:50 AM

Harnessing Big Data and High-Performance Computing Architecture for Loss Scenario Analysis
Mahesh V Joshi, SAS Institute Inc
9:55 AM

Great Expectations: Training Future Biostatisticians for Careers in Interdisciplinary Biomedical Research
Michelle Dunn, National Cancer Institute; Melissa D. Begg, Columbia University; Tor D. Tosteson, Geisel School of Medicine at Dartmouth; Robert E. Kass, Carnegie Mellon University
10:35 AM

Automatic model selection for forecasting large sets of count time series
Ta-Hsin Li, IBM Watson Research Center
10:50 AM

Managing and Outsizing Big Data in Healthcare Application
Maoqing Liu; Nasser Fard, Northeastern University
10:50 AM

Fast Algorithms for Logistic Regression with Big Data
HaiYing Wang, University of New Hampshire; Rong Zhu, Center for Forecasting Science, Chinese Academy of Sciences; Ping Ma, University Of Georgia
11:05 AM

Teaching Data Science at a Small Liberal Arts College for Women
Ben S. Baumer, Smith College
11:35 AM

Fast Bayesian inference for missing data on circular domains
Joe Guinness, North Carolina State University; Montserrat Fuentes, North Carolina State University
11:55 AM

Speeding up MCMC on Tall Data using Efficient Data Subsampling
Mattias Villani, Linköping University; Matias Quiroz, Sveriges Riksbank and Stockholm University; Robert J Kohn , University of New South Wales
11:55 AM

New graphical approach for visualization of EMR data with application to biomarker studies
Christine Duarte, Maine Medical Center; Ivette Emery, MMCRI; Andrew Prueser, MMCRI; Volkhard Lindner, MMCRI
2:35 PM

Applying Data Clustering and Data Reduction Methods in Multivariate Survival Data Analysis
Keivan Sadeghzadeh, Northeastern University; Nasser Fard, Northeastern University
2:35 PM

Thursday, 08/07/2014
Privacy, Big Data, and the Public Good: Frameworks for Engagement
Julia Lane, American Institutes for Research; Victoria Stodden , Columbia University; Stefan Bender, Institut für Arbeitsmarkt- und Berufsforschung (IAB); Helen Nissenbaum, New York University
8:35 AM

Transelliptical Topic Modeling with Application to Genomics Data
Xingyuan Fang, Princeton University; Han Liu, Princeton University
8:35 AM

Big Data Tool for Estimating Baseline Event Rates in Clinical Trials
Roshan Shah, Evidera
8:55 AM

MrNMF and SrNMF: Recent Development in Robust Non-Negative Matrix Factorization Procedures
Yifan Xu, Case Western Reserve University; Jiayang Sun, Case Western Reserve University; Kenneth K. Lopiano, Statistical and Applied Mathematical Sciences Institute (SAMSI); S. Stanley Young, NISS
9:00 AM

Cloud-scale alignment of NGS short reads
Hao Xiong
9:15 AM

A split-and-merge Bayesian variable selection approach for ultra-high dimensional regression
Faming Liang, Texas A&M University; Qifan Song, Texas A&M University
9:35 AM

Big Data Meets Text Mining
Zheng Zhao, SAS Institute Inc.; James Cox, SAS Institute Inc.; Russell Albright, SAS Institute Inc.
10:35 AM

Training Decision Tree Forests on Big Data
Padraic Neville, SAS Institute; Pei-Yi Tan, SAS Institute
11:15 AM


Sessions with Data Science in the Abstract: There are 16 of these and probably include talks from the lists above
​
Sunday, 08/03/2014
Industrial Internet, an Opportunity for Statisticians to become Data Scientists
Bill Ruh, GE Software Center
4:05 PM

Data Scientists: How Do We Prepare for the Future?
Michael Rappa, Institute for Advanced Analytics, NCSU
5:05 PM

Monday, 08/04/2014
Preparing Students for Big Data using R and RStudio
Randall Pruim, Calvin College
8:35 AM

Getting Started with Data Science
Daniel Theodore Kaplan, Macalester College
9:15 AM

Moving Towards Big Data using Long-Term Projects, Capstones and Culminating Experiences
Julie Marie Legler, St. Olaf College; Paul Roback, St. Olaf College
9:35 AM

Industrial internet: an opportunity for statistician in data science and big data revolution
Ming Li, SAS Institute
2:30 PM

Daytime Population estimations based on Mobile Phone Metadata
Martijn Tennekes, Statistics Netherlands; May Offermans, Statistics Netherlands
2:35 PM

How one government agency is approaching Big Data
Barbara Stevens
3:35 PM

Tuesday, 08/05/2014
What's the Difference Between Data Science and Statistics?
Charles Kincaid, Experis


Data Science and Statistics: How Should They Fit into Our Curriculum?
Johanna Hardin, Pomona College


Analyzing Data at Scale with the Berkeley Data Analytics Stack
Michael Franklin, UC Berkeley
8:35 AM

Wednesday, 08/06/2014
Visualization: Another V Associated with Big Data
John D. McKenzie, Jr., Babson College


Partnering with computer scientists to develop and teach a statistical computing course
Paul Roback, St. Olaf College; Olaf Hall-Holt, St. Olaf College; Kevin Sanft, St. Olaf College
11:05 AM

Teaching Data Science at a Small Liberal Arts College for Women
Ben S. Baumer, Smith College
11:35 AM

DataFest: A (competitive) celebration of data
Andrew Bray, University of Massachusetts, Amherst; Herle McGowan, North Carolina State University; Johanna Hardin, Pomona College; Robert Gould, UCLA
2:05 PM

The Present and Future of Statistics: Challenges and Opportunities
Marie Davidian, North Carolina State University
2:40 PM
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