Name: 2020 Joint Statistical Meetings
Start: 2020-08-02T07:00:00+00:00
End: 2020-08-06

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26	Mon, 8/3/2020, 10:00 AM - 11:50 AM	Virtual
Statistics in Imaging: Student Award Session — Topic Contributed Papers
Section on Statistics in Imaging
Organizer(s): Russell Shinohara, University of Pennsylvania
Chair(s): Russell Shinohara, University of Pennsylvania
10:05 AM	Permutation-Based Inference for Spatially Localized Signals in Longitudinal MRI Data Jun Young Park, University of Minnesota; Mark Fiecas, University of Minnesota
10:25 AM	Bayesian Framework for Simultaneous Registration and Estimation of Noisy, Sparse and Fragmented Functional Data James Matuk, The Ohio State University; Karthik Bharath, University of Nottingham; Oksana Chkrebtii, The Ohio State University; Sebastian Kurtek, The Ohio State University
10:45 AM	Estimating Fiber Orientation Distribution Through Blockwise Adaptive Thresholding with Application to HCP Young Adults Data Presentation Seungyong Hwang, University of California, Davis; Thomas Lee, University of California, Davis; Jie Peng, University of California, Davis; Debashis Paul, University of California, Davis
11:05 AM	Extracting Brain Disease Related Connectome Subgraphs by Adaptive Dense Graph Discovery Qiong Wu, University of Maryland; James Waltz, Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland; Shuo Chen, University of Maryland, School of Medicine
11:25 AM	Discussant: Simon Vandekar, Vanderbilt University
11:45 AM	Floor Discussion

47	Mon, 8/3/2020, 10:00 AM - 2:00 PM	Virtual
Recent Development in Imaging Statistics — Contributed Papers
Section on Statistics in Imaging
Chair(s): Chao Huang, Florida State University
	A Comparison of Angle-Based JIVE and Iterative JIVE Presentation Raphiel Murden, Emory Univ, Rollins School of SPH; Ying Guo, Emory University; Benjamin B Risk, Emory University
	Scalar-On-Network Regression via Boosting Emily L Morris, Department of Biostatistics, University of Michigan; Jian Kang, University of Michigan
	Incorporating Spatial Structure into Bayesian Spike-And-Slab Lasso GLMs Justin Leach, University of Alabama at Birmingham; Inmaculada Aban, University of Alabama at Birmingham; Nengjun Yi, University of Alabama at Birmingham
	Permutation Testing for Function-On-Scalar Regression with PET Binding Data Along a Brain Tract Denise Shieh, Columbia University; Todd Ogden, Columbia University
	Utilizing Baseline and Differential Information to Improve fMRI Brain Activation Dan Rowe, Marquette University
	Statistical Inference for Mean Functions of Functional Objects Yueying Wang, Iowa State University; Guannan Wang, College of William and Mary; Lily Wang, Iowa State University
	A Bayesian Approach of Finding Fiber Orientation in Brain with Directional Prior ANJAN MANDAL, UNIVERSITY OF NEVADA LAS VEGAS; KAUSHIK GHOSH, UNIVERSITY OF NEVADA LAS VEGAS
	A Mixture Modeling Approach to Image Normalization in Highly Multiplexed Cellular Imaging Data Presentation Coleman Harris, Vanderbilt University Medical Center; Eliot McKinley, Vanderbilt University Medical Center; Joseph Roland, Vanderbilt University Medical Center; Ken Lau, Vanderbilt University Medical Center; Robert Coffey, Vanderbilt University Medical Center; Simon Vandekar, Vanderbilt University

121	Mon, 8/3/2020, 1:00 PM - 2:50 PM	Virtual
Emerging Statistical Methods for Structured and Multimodal Data Analysis — Topic Contributed Papers
Section on Statistics in Imaging
Organizer(s): Yize Zhao, Yale University
Chair(s): Yi Zhao, Indiana University
1:05 PM	Adaptive Estimation in Structured Factor Models with Applications to Overlapping Clustering Yang Ning, Cornell University
1:25 PM	Multi-State Markov Transition Models for Examining Multimodal Imaging Signatures of Alzheimer's Disease Zoe Zhang, Drexel University; Ashley Heywood, Northwestern University; Jane Stocks, Northwestern University; Lei Wang, Northwestern University
1:45 PM	Statistical Approaches for Dynamic Brain Networks Suprateek Kundu
2:05 PM	L_0 Shrinkage for Association Analysis Between Multivariate Imaging and Multivariate Genetics Data Shuo Chen, University of Maryland, School of Medicine
2:25 PM	Floor Discussion

143 *	Tue, 8/4/2020, 10:00 AM - 11:50 AM	Virtual
Recent Advances in Imaging Genetics — Invited Papers
Section on Statistics in Imaging, Mental Health Statistics Section, Section on Statistics in Genomics and Genetics
Organizer(s): Wesley Thompson, University of California, San Diego
Chair(s): Lingjing Jiang, University of California, San Diego
10:05 AM	A Bayesian Spatial Model for Imaging Genetics Yin Song, University of Victoria; Shufei Ge, Simon Fraser University; Jiguo Cao, Simon Fraser University; Liangliang Wang, Simon Fraser University; Nathoo Farouk, University of Victoria
10:30 AM	Heritability Models for Neuroimaging Benjamin B Risk, Emory University; Hongtu Zhu, University of North Carolina at Chapel Hill
10:55 AM	A Grouped Beta Process Model for Multivariate Resting-State EEG Microstate Analysis on Twins Mark Fiecas, University of Minnesota
11:20 AM	Discussant: Wesley Thompson, University of California, San Diego
11:45 AM	Floor Discussion

221	Tue, 8/4/2020, 10:00 AM - 2:00 PM	Virtual
Contributed Poster Presentations: Section on Statistics in Imaging — Contributed Poster Presentations
Section on Statistics in Imaging
1:	An Exploration of the Use of Statistical Machine Learning Techniques to Shorten the Duration of Dynamic PET-FDG Imaging Protocols in a Clinical Context Qi Wu, University College Cork; Finbarr O'Sullivan, University College Cork; Mark Muzi, University of Washington ; David Mankoff, University of Pennsylvania
2:	A Bayesian Incorporated Linear Non-Gaussian Acyclic Model (BiLiNGAM) for Multiple Directed Acyclic Graph Estimation with Application to Causal Brain Connectivity Using fMRI Aiying Zhang, Tulane University; Yu-Ping Wang, Tulane University
3:	Modeling Extremal Dependence of Multi-Channel EEG Data Matheus Bartolo B. Guerrero, KAUST; Raphael Huser, King Abdullah University of Science and Technology (KAUST); Hernando Ombao, King Abdullah Univ. of Science and Technology (KAUST)
4:	Two-stage stratified PCA for simultaneous dimension reduction and nuisance variable mitigation Sarah M. Weinstein, University of Pennsylvania, Department of Biostatistics, Epidemiology, and Informatics; Kristin A. Linn, University of Pennsylvania, Department of Biostatistics, Epidemiology, and Informatics; Russell Shinohara, University of Pennsylvania
5:	Mixed-Effects Non-Stationary Time Series Bartlomiej Mulewicz, KAUST
6:	Quantification of Pixel-Wise Noise in Clinical Positron Emission Tomography (PET) Images Ran Ren, University College Cork; Jian Huang, University College Cork; Finbarr O'Sullivan, University College Cork; Tian Mou, Karolinska Institutet; Kevin O'Regan, Cork University Hospital
7:	Classifying Brain Edema with Low-Resolution MRI Danni Tu, Univ of Pennsylvania; Dylan Small, University of Pennsylvania; Manu S. Goyal, Department of Radiology, Washington University School of Medicine; Theodore Satterthwaite, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania; Kelly Clark, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania; Russell Shinohara, University of Pennsylvania
8:	Bayesian Inference for Brain Activity from Multi-Resolution Functional Magnetic Resonance Imaging Andrew Whiteman, University of Michigan; Jian Kang, University of Michigan; Timothy D Johnson, University of Michigan
9:	Discovering Alzheimer’s Disease pathology by neuroimaging and genetic data Kristen Knight, University of Georgia, Department of Statistics; Nicole Lazar, University of Georgia; Liang Liu, University of Georgia

240 * !	Tue, 8/4/2020, 1:00 PM - 2:50 PM	Virtual
Statistical Analysis of Complex Imaging Data — Invited Papers
WNAR, Section on Statistics in Imaging, Mental Health Statistics Section
Organizer(s): Dehan Kong, University of Toronto
Chair(s): Dehan Kong, University of Toronto
1:05 PM	Principle ERP Reduction and Analysis: Estimating and Using Principle ERP Waveforms Underlying ERPs Across Tasks, Subjects and Electrodes Damla Senturk, UCLA; Shafali Jeste, UCLA; Emilie Campos, UCLA; Chad Hazlett, UCLA; Patricia Tan, UCLA; Holly Truong, UCLA; Sandra Loo, UCLA; Charlotte DiStefano, UCLA
1:35 PM	Covariance Regression for Connectome Outcomes Brian Caffo, Johns Hopkins University; Rossi Luo, The University of Texas Health Science Center; Yi Zhao, Indiana University; Bingkai Wang, Johns Hopkins Bloomberg School of Public Health
2:05 PM	A Source Separation Method for Investigating Brain Connectome Traits Ying Guo, Emory University; Yikai Wang, Emory University
2:35 PM	Floor Discussion

311 * !	Wed, 8/5/2020, 10:00 AM - 11:50 AM	Virtual
Modern Statistical Methods for Imaging Genomics — Topic Contributed Papers
Section on Statistics in Imaging, Biometrics Section, International Indian Statistical Association
Organizer(s): Shariq Mohammed, University of Michigan; Arvind Rao, University of Michigan
Chair(s): Arvind Rao, University of Michigan
10:05 AM	Thresholded Graph Laplacian Gaussian Priors for Bayesian Network Marker Selection with Application to Cancer Imaging Genomics Jian Kang, University of Michigan
10:25 AM	Issues in Integrating Genomics and Imaging Data in Cancer Debashis Ghosh, University of Colorado, School of Public Health
10:45 AM	Statistical Models for 3D Images Sayan Mukherjee, Duke University
11:05 AM	RADIOHEAD: Radiogenomic Analysis Incorporating Tumor Heterogeneity in Imaging Through Densities Shariq Mohammed, University of Michigan; Karthik Bharath, University of Nottingham; Sebastian Kurtek, The Ohio State University; Arvind Rao, University of Michigan; Veera Baladandayuthapani, University of Michigan
11:25 AM	A Bayesian 2D Functional Linear Model: Application to GLCM Matrices in LGG Cancer Radiomics Data Presentation Thierry Chekouo , University of Calgary; Shariq Mohammed, University of Michigan; Arvind Rao, University of Michigan
11:45 AM	Floor Discussion

376	Wed, 8/5/2020, 12:00 PM - 1:00 PM	Virtual
Section on Statistics in Imaging P.M. Roundtable Discussion — Roundtables PM Roundtable Discussion
Section on Statistics in Imaging
WL10:	Applying for Your First NIH Grant in Imaging Statistics Amanda Mejia, Indiana University

409	Wed, 8/5/2020, 1:00 PM - 2:50 PM	Virtual
Complex Innovative Approaches in Emerging Neurodegenerative / Neuroimaging Drug Developments — Topic Contributed Papers
Biopharmaceutical Section, Section on Medical Devices and Diagnostics, Section on Statistics in Imaging
Organizer(s): Tristan Massie, FDA
Chair(s): Sue-Jane Wang, FDA
1:05 PM	A ROC Surface Methodology in Diagnosing Early Stage Neurodegenerative Diseases for Early Interventions Chengjie Xiong, Washington University in St Louis; Jingqin Luo, Washington University in St. Louis
1:25 PM	Alternatives to MMRM for Preclinical Alzheimer’s Clinical Trials Presentation Michael C Donohue, University of Southern California; Gopalan Sethuraman, University of Southern California; Oliver Langford, University of Southern California; Wenyi Lin, University of California, San Diego; Philip S Insel, Lund University; Wesley Thompson, University of California, San Diego; Rema C Raman, University of Southern California; Reisa Sperling, Harvard Medical School; Paul S Aisen, University of Southern California
1:45 PM	Comparative Performance of Some Testing Approaches in Two-Arm Studies with Count Data Potentially Highly Skewed Sue-Jane Wang, FDA; Zhipeng Huang, U.S. Food and Drug Administration (Intern); Hai Zhu, The University of Texas Health Science Center at Houston
2:05 PM	Statistical Issues and Challenges Seen in Drug Development for Neurodegenerative Diseases Tristan Massie, FDA
2:25 PM	Floor Discussion

471	Thu, 8/6/2020, 10:00 AM - 2:00 PM	Virtual
Contemporary Statistical Methods for Imaging Data Analysis — Contributed Papers
Section on Statistics in Imaging
Chair(s): Dan Rowe, Marquette University
	Pill Shape Classification using Imbalanced Data with Human-Machine Hybrid Explainable Model William Lamberti, George Mason Univeristy
	Dynamic Diseased Region Detection for Longitudinal Medical Imaging Data Chao Huang, Florida State University
	Mixtures of Gaussian Random Fields and Its Application in Analyzing fMRI Data Mozhdeh Forghani, University of Northern Colorado; Khalil Shafie, University of Northern Colorado
	Extracting Dermoscopic Features with Neural Style Transfer for Skin Lesion Classification Yutong Li, University of Illinois at Urbana-Champaign; Ruoqing Zhu, University of Illinois at Urbana-Champaign; Annie Qu, University of Illinois at Urbana-Champaign
	Online Parameter Estimation for Time Varying VAR Models with Application to Brain Signals Presentation Anass El Yaagoubi Bourakna, KAUST; Hernando Ombao, King Abdullah Univ. of Science and Technology (KAUST)
	Unveil the Intrinsic Connectivity Network with Bayesian Dynamic Latent Factor Model Meini Tang, King Abdullah University of Science and Technology; Chee-Ming Ting, King Abdullah Univ. of Sci. and Tech (KAUST); Hernando Ombao, King Abdullah Univ. of Science and Technology (KAUST)
	Investigating the Temporal Pattern of Neuroimaging Based Brain Age Prediction as a Biomarker for Dementia Alexei Taylor, Drexel University; Zoe Zhang, Drexel University; Ashley Heywood, Northwestern University; Jane Stocks, Northwestern University; Lei Wang, Northwestern University
	Removal of Scanner Effects in Covariance Improves Multivariate Pattern Analysis in Neuroimaging Data Andrew Chen, University of Pennsylvania; Haochang Shou, University of Pennsylvania; Russell Shinohara, University of Pennsylvania; Philip Cook, University of Pennsylvania; Nicholas J Tustison, University of Virginia; Joanne Beer, University of Pennsylvania

532 * !	Thu, 8/6/2020, 1:00 PM - 2:50 PM	Virtual
Making Big and Complex Imaging Data Count with New Statistical Tools — Invited Papers
SSC (Statistical Society of Canada), Section on Statistics in Imaging, Section on Statistical Graphics
Organizer(s): Linglong Kong, University of Alberta
Chair(s): Nathoo Farouk, University of Victoria
1:05 PM	Multivariate Functional Responses Low Rank Regression with an Application to Brain Imaging Data Xiucai Ding, Duke University; Dengdeng Yu, University of Toronto; Zhengwu Zhang, University of Rochester; Dehan Kong, University of Toronto
1:30 PM	Modeling Brain Connectivity in Real Time Hernando Ombao, King Abdullah Univ. of Science and Technology (KAUST); Chee-Ming Ting, King Abdullah Univ. of Sci. and Tech (KAUST); Marco Pinto, King Abdullah Univ. of Science and Technology (KAUST)
1:55 PM	Adaptive Regularization in Complex Settings: Multimodal Brain Imaging Jaroslaw Harezlak, Indiana University; Damian Brzyski, Wroclaw University of Science and Technology, Poland; Kewin Paczek, Jagiellonian University, Krakow, Poland; Joaquin Goni, Purdue University; Timothy Randolph, Fred Hutchinson Cancer Research Center; Beau Ances, Washington University School of Medicine
2:20 PM	Discussant: Adam Kashlak, University of Alberta
2:45 PM	Floor Discussion

565 * !	Thu, 8/6/2020, 3:00 PM - 4:50 PM	Virtual
Statistical Methods for Understanding Brain Organization — Invited Papers
Section on Statistics in Imaging, Biometrics Section, International Association for Statistical Computing
Organizer(s): Ani Eloyan, Brown University
Chair(s): Sherri Rose, Harvard Medical School
3:05 PM	Some Topics in Multimodal Neuroimaging Analysis Lexin Li, University of California, Berkeley
3:30 PM	Graph Theoretic Modeling of Brain Functional Connectivity Ani Eloyan, Brown University
3:55 PM	Reliable Estimation of Individual Brain Organization Leveraging Population and Spatial Information in a Bayesian Framework Amanda Mejia, Indiana University; Mary Beth Nebel, Johns Hopkins University; Yu Ryan Yue, Baruch College; Brian Caffo, Johns Hopkins University
4:20 PM	Discussant: Tingting Zhang, University of Virginia
4:45 PM	Floor Discussion

JSM 2020 Online Program

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American Statistical Association