The 31st New England Statistics Symposium

April 21–April 22, 2017, University of Connecticut

Invited Sessions


Morning sessions

1. New Vistas in Statistics with Applications

Organizer: Aleksey Polunchenko, Binghamton University
Chair: Vasanthan Raghavan, Qualcomm Flarion Technologies, New Jersey

  • Aleksey Polunchenko, Binghamton University
  • Vasanthan Raghavan, Qualcomm Flarion Technologies, New Jersey
  • Zuofeng Shang, Binghamton University
  • Emmanuel Yashchin, IBM

Oak Hall 235


2. Non-clinical in Pharmaceutical Industry

Organizer and Chair: Chi-Hse Teng, Novartis

  • Don Bennett, Pfizer
  • Jerry Lewis, Biogen
  • Ray Liu, Takeda
  • Chi-Hse Teng, Novartis

Oak Hall 267


3. Space-Time Statistical Solutions at IBM Research

Organizer: Yasuo Amemiya, IBM T. J. Watson Research Center
Chair: Beatriz Etchegaray Garcia, IBM T. J. Watson Research Center

  • Julie Novak, IBM T. J. Watson Research Center
    “Revenue Assessment in Large-Scale Businesses”
  • Xiao Liu, IBM T. J. Watson Research Center
    “A Spatio-Temporal Modeling Approach for Weather Radar Image Data”
  • Rodrigue Ngueyep Tzoumpe, IBM T. J. Watson Research Center
    “Spatial Segmentation of Spatial-Temporal Lattice Models for Agricultural Management Zoning”
  • Yasuo Amemiya, IBM T. J. Watson Research Center
    “Spatio-Temporal Analysis for System Management”

Oak Hall 269


4. Graphical Models, Networks, Regulomes and Multivariate Analysis

Organizer and Chair: Yuping Zhang, University of Connecticut

  • Forrest W. Crawford, Yale University
    “Causal Inference for Network Epidemics”
  • Zhengqing Ouyang, The Jackson Laboratory for Genomic Medicine”
    “Understanding Dynamic Regulomes through 3D Genome and Transcriptome Modeling”
  • Sijian Wang, University of Wisconsin Madison
  • Kuang-Yao Lee, Yale University
    “Learning Causal Networks via Additive Faithfulness”

Oak Hall 268


5. Big Data

Organizer and Chair: Haim Bar, University of Connecticut

  • Jacob Bien, Cornell University
    “Learning Local Dependence in Ordered Data”
  • Li Ma, Duke University
    “Fisher exact scanning for dependency”
  • Yuwen Gu, University of Minnesota
    “Penalized Composite Quantile Regression for High-Dimensional Data”
  • Chihwa Kao, University of Connecticut
    “Large Dimensional Econometrics and Identification”

Laurel Hall 301


6. Bayesian Applications in High-Dimensional and Multivariate Modeling

Organizer and Chair: Seongho Song, University of Cincinnati

  • Seongho Song, University of Cincinnati
    “Bayesian Multivariate Gamma-Frailty Cox Model for Clustered Current Status Data”
  • Xia Wang, University of Cincinnati
    “Scalable Massive Multivariate Data Modeling”
  • Gyuhyeong Goh, Kansas State University
    “Bayesian Variable Selection using Marginal Posterior Consistency”
  • Jian Zou, Worcester Polytechnic Institute
    “High Dimensional Dynamic Modeling for Massive Spatio-Temporal Data”

Laurel Hall 308


7. New Advances in Analysis of Complex Data: Heterogeneity and High Dimensions

Organizer and Chair: Min-ge Xie, Rutgers University

  • Dungang Liu, University of Cincinnati
    “Nonparametric Fusion Learning: Synthesize Inferences from Diverse Sources using Confidence Distribution, Data Depth and Bootstrap”
  • Dan Yang, Rutgers University
    “Bilinear Regression with Matrix Covariates in High Dimensions”
  • Pierre Bellec, Rutgers University
    “Slope Meets Lasso in Sparse Linear Regression”
  • Yiyuan She, Florida State University
    “On cross-validation for sparse reduced rank regression”

Laurel Hall 206


8. Machine Learning and Big Data Analytics

Organizer and Chair: Jinbo Bi, University of Connecticut

  • Sanguthevar Rajasekaran, University of Connecticut
    “The closest pair problem: Algorithms and applications”
  • Renato Polimanti, Yale University
    “Resources to Investigate the Genetic Architecture of Complex Traits: Large-Scale Datasets and Summary Association Data”
  • Sheida Nabavi, University of Connecticut
    “Statistical machine learning to identify candidate drivers of drug resistance in cancer”
  • Michael Kane, Yale University
    “A First Look at Using Human Mobility Data to Assess Community Resilience”

Laurel Hall 306


9. Statistical Approaches in Modeling and Incorporating Dependence

Organizer and Chair: Ting Zhang, Boston University

  • Mengyu Xu, University of Central Florida
    “Pearson’s Chi-Squared Statistics: Approximation Theory and Beyond”
  • Kun Chen, University of Connecticut
    “Robust Dimension Reduction of Correlated Multivariate Data”
  • Liliya Lavitas, Boston University
    “Unsupervised Self-Normalized Change-Point Testing for Time Series”
  • Buddika Peiris, Worcester Polytechnic Institute
    “Constrained Inference in Regression”

Laurel Hall 309


10. Biopharmaceutical Statistics

Organizer: Abidemi Adeniji, EMD Serono
Chair: Adina Soaita, Pfizer

  • Abidemi Adeniji, EMD Serono
  • Bushi Wang, Boehringer-Ingelheim
  • Joseph C. Cappelleri, Pfizer
    “Meta-Analysis of Safety Data in Clinical Trials”
  • Qiqi Deng, Boehringer Ingelheim
  • Birol Emir, Pfizer

Laurel Hall 302


11. Extremes

Organizer and Chair: Richard Davis, Phyllis Wan, Columbia University

  • John Nolan, American University
    “Mvevd: An R Package for Extreme Value Distributions”
  • Jingjing Zou, Columbia University
    “Extreme Value Analysis without the Largest Values: What can be Done?”
  • Karthyek Murthy, Columbia University
    “Distributionally Robust Extreme Value Analysis”
  • Tiandong Wang, Cornell University
    “Asymptotic Normality of Degree Counts in the Preferential Attachment Network”

Laurel Hall 305


12. Feinberg Memorial Session: Bayesian Statistics with Applications

Organizer and Chair: Dipak Dey, University of Connecticut

  • Edoardo Airoldi, Harvard University
    “Bayesian Methods for Protein Quantification”
  • Bani Mallick, Texas A&M University
    “Fast Sampling with Gaussian Scale-Mixture Priors in High Dimensional Regression”
  • Sudipto Banerjee, UCLA
    “High-Dimensional Bayesian Geostatistics”

Laurel Hall 307


Afternoon sessions

1. Panel Discussion on Careers in Statistics

Organizer and Chair: Naitee Ting, Boehringer Ingelheim Pharmaceuticals, Inc.

  • Birol Emir, Pfizer
  • Chun Wang, University of Connecticut
  • Yasuo Amemiya, IBM T. J. Watson Research Center
  • Minge Xie

Oak Hall 235


2. Statistical Applications in Finance and Insurance

Organizer and Chair: Guojun Gan, University of Connecticut

  • Liang Peng, Georgia State University
    “Inference for Predictive Regressions”
  • Fangfang Wang, University of Connecticut
    “A Common Factor Analysis of Stock Market Trading Activity”
  • Oleksii Mostovyi, University of Connecticut
    “Sensitivity analysis of the expected utility maximization problem”
  • Aritra Halder, Shariq Mohammed, Matthew Lamoureux, Brien Aronov, University of Connecticut
    “Towards differential pricing in auto insurance via large-scale predictive modeling: a partnership between Travelers and UConn”

Oak Hall 267


Organizer and Chair: Nan Shao, New York Life Insurance

  • Xiaoyu Jia, Icahn School of Medicine at Mount Sinai
  • Zhaonan Sun, IBM T. J. Watson Research
    “Exploiting Convolutional Neural Network for Risk Prediction with Medical Feature Embedding”
  • Victoria Gamerman, Boehringer Ingelheim Pharmaceuticals, Inc.
  • Nan Shao, New York Life Insurance
    “Statistical Modeling in the Life Insurance Industry”

Oak Hall 268


4. Survival Analysis

Organizer and Chair: Sy Han Chiou, Harvard University

  • Daniel Nevo, Harvard University
  • Bella Vakulenko-Lagun, Harvard University
  • Jing Qian, University of Massachusetts
  • Sangwook Kang

Oak Hall 269


5. Complex Data/Network Modeling

Organizer and Chair: Yuan Huang, Department of Biostatistics, Yale University

  • Yize Zhao, Weill Cornell Medical College, Cornell University
    “Hierarchical Feature Selection of the Complex Biomedical Data”
  • Heather Shappell, Biostatistics, Boston University
    “Methods for Longitudinal Complex Network Analysis in Neuroscience”
  • Krista Gile, Math and Statistics, University of Massachusetts
    “Inference from Link-Tracing Network Samples”
  • Xizhen Cai, Temple University
    “Variable Selection for Dynamic Networks”
  • Xuan Bi, Department of Biostatistics, Yale University
    “Genome-Wide Mediation Analysis of Psychiatric and Cognitive Traits in the Philadelphia Neurodevelopmental Cohort”

Laurel Hall 301


6. Spatial Analysis of Public Health Data

Organizer and Chair: Beth Ziniti, Applied Geosolutions LLC

  • Harrison Quick, Dornsife School of Public Health, Drexel University
    “Spatiotemporal Trends in Heart Disease Mortality”
  • Joshua Warren, Yale School of Public Health
    “A Bayesian Spatial Kernel Smoothing Method to Estimate Local Vaccine Uptake using Administrative Records”
  • Gavino Puggioni, University of Rhode Island
    “Spatiotemporal Analysis of Vector-Borne Disease Risk”
  • Chanmin Kim, Harvard T. H. Chan School of Public Health
    “Public Health Impact of Pollutant Emissions”

Laurel Hall 308


7. Network Data Analysis

Organizer and Chair: Edoardo M. Airoldi, Harvard University

  • JP Onnela, Harvard University
    “Inference and model selection for mechanistic network models”
  • Vishesh Karwa, Harvard University
    “Estimating average treatment effects under interference: Modes of failure and solutions”
  • Xinran Li, Harvard University
    “Randomization Inference for Peer Effects”

Laurel Hall 206


8. Statistical Approaches to Data Modeling and Analysis

Organizer and Chair: Erin Conlon, University of Massachusetts Amherst

  • Evan Ray, University of Massachusetts Amherst
    “Feature-Weighted Ensembles for Probabilistic Time-Series Forecasts”
  • Daeyoung Kim, University of Massachusetts Amherst
    “Assessment of the Adequacy of Asymptotic Theory in Statistical Inference”
  • Patrick Flaherty, University of Massachusetts
    “A Deterministic Global Optimization Method for Variational Inference”
  • Matthias Steinruecken, University of Massachusetts Amherst
    “Unraveling the Demographic History of Modern Humans using Full- Genome Sequencing Data”
  • Zheng Wei, University of Massachusetts Amherst
    “On Multivariate Asymmetric Dependence Using Multivariate Skew-Normal Copula-Based Regression”

Laurel Hall 306


9. Social Networks and Causal Inference

Organizer and Chair: Daniel Sussman, Boston University

  • Daniel Sussman, Boston University
    “Optimal Unbiased Estimation of Causal Effects under Network Interference”
  • Alex Volfovsky, Duke University
    “Causal Inference in the Presence of Networks: Randomization and Observation”
  • Dean Eckles, Massachusetts Institute of Technology
    “Estimating Peer Effects in Networks with Peer Encouragement Designs”
  • Hyunseung Kang, University of Wisconsin at Madison
    “Peer Encouragement Designs in Causal Inference with Partial Interference and Identification of Local Average Network Effects”

Laurel Hall 309


10. Statistical Innovations in Genomics

Organizer and Chair: Zhengqing Ouyang, The Jackson Laboratory for Genomic Medicine

  • Hongkai Ji, Johns Hopkins Bloomberg School of Public Health
  • Pei Wang, Mount Sinai School of Medicine
    “Constructing Tumor-Specific Gene Regulatory Networks Based on Samples with Tumor Purity Heterogeneity”
  • Yuping Zhang, University of Connecticut
    “Integrating Diverse Genomic Data to Estimate Multiple Networks”
  • Kai Wang, Columbia University
    “Long Read Sequencing to Study Human Genome Variation”

Laurel Hall 302


11. Recent Developments on High-Dimensional Statistics and Regularized Estimation

Organizer and Chair: Kun Chen, University of Connecticut

  • Ethan Fang, Pennsylvania State University
    “Blessing of Massive Scale: Spatial Graphical Model Estimation with a Total Cardinality Constraint Approach”
  • Cheng Yong Tang, Temple University
    “Sufficient Dimension Reduction with Missing Data”
  • Sahand Nagahban, Yale University
    “Restricted Strong Convexity Implies Weak Sub-Modularity”
  • Ting Zhang, Boston University
    “A Thresholding-Based Prewhitened Long-Run Variance Estimator and Its Dependence-Oracle Property”

Laurel Hall 305


12. Subgroup Analysis

Organizer and Chair: Xiaojing Wang, University of Connecticut

  • Yanxun Xu, Johns Hopkins University
    “A Nonparametric Bayesian Basket Trial Design”
  • Lynn Lin, Pennsylvania State University
    “Clustering with Hidden Markov Model on Variable Blocks”
  • Jared Huling, University of Wisconsin-Madison
    “Heterogeneity of Intervention Effects and Subgroup Identification based on Longitudinal Outcomes”
  • Wai-Ki Yip, Foundation Medicine, Inc.
    “STEPP Analysis for continuous, binary, and count outcomes and other recent STEPP development”

Laurel Hall 307