Student paper competition
Winners
2018
This year we had a great competition with 25 submissions. The
committee selected four winners and one honorable mention. Thank you to our judges for all their hard work in reading and evaluating these papers: Heike Hofmann, Daniel Sussman, Raymond Wong, and Hao Helen Zhang (chair). The four
winners are:
- "BRISC: Bootstrap for rapid inference on spatial covariances", by
Arkajyoti Saha (Department of Biostatistics, Johns Hopkins University)
- "MM algorithms for variance component models", by Liuyi Hu
(Department of Statistics, North Carolina State University).
- "An asympirical smoothing parameters selection approach for SS-ANOVA
models in large samples", by Xiaoxiao Sun (Department of Statistics,
University of Georgia)
- "Calendar-based graphics for visualizing people's daily schedules",
by Earo Wang (Department of Econometrics and Business Statistics,
Monash University)
The honorable mention is
- "Dependency diagnostic: visually understanding pairwise variable
relations", by Kevin Lin (Department of Statistics, Carnegie Mellon
University)
2017
We had a great competition this year with 27 submissions. Thank you to our judges for all their hard work in reading and evaluating these papers: Robert Gramacy, Kenneth Shirley, Kate Cowles, and Deepayan Sarkar. This year’s winners are:
- “acc: An R package to process, visualize, and analyze accelerometer data”, by Jae Joon Song (University of Texas)
- “The biglasso Package: A Memory- and Computation-Efficient Solver For Lasso Model Fitting With Big Data in R”, by Yaohui Zeng (University of Iowa)
- “Scalable Bayesian Learning for Sparse Logistic Models”, by Xichen Huang (University of Illinois)
- “The Self-Multiset Sampler”, by Weihong Huang (University of Illinois)
2016
We had a great competition this year with 27 submissions. Thank you to our judges for all their hard work in reading and evaluating these papers: Tim Hesterberg, Di Cook, and Grant Brown. This year's winners are:
- "A fully Bayesian strategy for high-dimensional hierarchical modeling
using massively parallel computing", by Will Landau (Iowa State University)
- "The picasso Package for Nonconvex Regularized M-estimation in High
Dimensions in R", by Xingguo Li (University of Minnesota)
- "Nonparametric Signal Procession of Space-Time Trajectory Data:
Algorithm for Eye Movement Pattern Recognition", by Shinjini Nandi
(Temple University)
- "Using the geomnet Package: Visualizing African Slave Trade, 1514 -
1866", by Samantha Tyner (Iowa State University)
2015
We had a great competition this year with 21 submissions. We would like to acknowledge our judges for their hard work in evaluating these submissions: Hadley Wickham, Jonathan Lane, and Mario Morales. We had two winners from the Graphics Section and two from the Computing Section, as listed below. This year's winners are:
- Computing: Ben Courtney Stevenson (University of St Andrews, United Kingdom) - An R package for the estimation of animal density from a fixed array of remote detectors
- Computing: Kaylea Haynes (Lancaster University, Lancaster) - Efficient penalty search for multiple changepoint detection in Big data
- Graphics: Lindsay Rutter (Iowa State University) - phyViz: Phylogenetic visualization of genealogical information in R
- Graphics: Eric Hare and Andrea J. Kaplan (Iowa State University) - Introducing statistics with intRo
2014
We had a great competition this year with 22 submissions, 19 in the Computing Section and 3 for the Graphics Section. We would like to acknowledge our judges for their hard work in evaluating these submissions: John Castelloe, Erik Iverson, and Heike Hofmann. We had one winner from the Graphics Section and three winners from the Computing Section, as listed below:
This year's winners are:
- Computing: Gina Grünhage (Technische Universität Berlin) - Visualizing the Effects of a Changing Distance Using Continuous Embeddings
- Computing: Geoffrey Thompson (Iowa State University) - An Adaptive Method for Lossy Compression of Big Images
- Computing: Guan Yu (University of North Carolina at Chapel Hill) - Sparse Regression Incorporating Graphical Structure Among Predictors
- Graphics: Susan Vanderplas (Iowa State University) - The Curse of Three Dimensions: Why Your Brain Is Lying to You
2013
The number of submissions this year is better than
last year, a total of 28 submissions (18 from last year and only 10
before that). The judges were John Castelloe, Erik Iverson and Michael
Lawrence. Many thanks for their efforts to review and rank all the
papers so quickly.
This year's winners are:
- Abbass Sharif, (Utah State University) "Multivariate Visual Data
Mining Tools for Functional Actigraphy Data"
- Adam Loy, (Iowa State University), "Are you Normal, The problem of
confounded residual structures in hierarchical models"
- Nathaniel Helwig, (University of Illinois at Urbana-Champaign), "Fast
and stable multiple smoothing parameter selection in smoothing spline
analysis of variance models with large samples"
- Xinxin Shu, (University of Illinois at Urbana-Champaign),
"Time-varying networks estimation and dynamic model selection"
2012
The number of submissions this year is better than
last year, a total of 18 submissions (10 from last year). The
four judges were John Castelloe, Erik Iverson, Mark Greenwood and
Michael Lawrence. Many thanks for their efforts to review and rank all
the papers so quickly.
This year's winners are:
- Graphics: Niladri Roy Chowdhury, (Iowa State University), "Where's Waldo: Looking closely at a Lineup"
- Computing: Yunzhi Lin, (University of Wisconsin), Lasso Tree for Cancer Stage Grouping with Survival Data
- Computing: Karl Pazdernik, (Iowa State University), Efficient Maximum Likelihood Estimation for Fixed Rank Kriging
- Computing: Jingfei Zhang, (University of Illinois at Urbana-Champaign), Sampling
for Conditional Inference on Network Data
2011
- Graphics: Mahbubul Majumder (advisors Heike Hofmann and Dianne Cook, Department
of Statistics, Iowa State University) "Visual Statistical Inference
for Regression Parameters"
- Computing: Wonyul Lee (advisor Yufeng Liu, University of North Carolina at
Chapel Hill) "Simultaneous Multiple Response Regression and Inverse
Covariance Matrix Estimation via Penalized Gaussian Maximum
Likelihood"
- Computing: Yunpeng Zhao (advisors Elizaveta Levina and Ji Zhu, Department of
Statistics, University of Michigan) "Community extraction for social
networks"
2010
This year a large number of excellent entries were received, from
which the selection committee has chosen four winners (in alphabetical
order):
- Han Liu (advisors John Lafferty and Larry Wasserman, Statistics and
Machine Learning Program, Carnegie Mellon University)
"Multivariate Dyadic Regression Trees for Sparse Learning Problems"
- Hua Ouyang (advisor Alexander Gray, College of Computing, Georgia Institute of Technology)
"Fast Stochastic Frank-Wolfe Algorithms for Nonlinear SVMs"
- Ali Shojaie (advisor George Michailidis, Department of Statistics,
University of Michigan)
"Discovering Graphical Granger Causality Using the Truncating Lasso Penalty"
- Ying Sun (advisors Jeff Hart and Marc G. Genton, Department of
Statistics, Texas A&M University)
"Functional Boxplots for Complex Data Visualization"
The students will be recognized at the Statistical
Computing/Statistical Graphics business meeting at JSM 2010.
Congratulations to the winners and many thanks to the judges for their
hard work in making this year's competition a success!
2009
This year a large number of excellent entries were received, from which the selection committee selected five winners (in alphabetical order):
- Bjorn Bornkamp (advisors Jose Pinheiro and Katja Ickstadt)
"MCPMod: An
R Package for the Design and Analysis of Dose-Finding Studies"
- Wei-Chen Chen (advisor Karin Dorman)
"Twisted Sisters: Disentangling Selection in Overlapping Reading Frames"
- Jian Guo (advisors Elizaveta Levina, George Michailidis and Ji Zhu)
"Pairwise Variable Selection for High-dimensional Model-based Clustering"
- Ruth Hummel (advisor David Hunter)
"A Steplength Algorithm for Fitting ERGMs"
- Mihee Lee (advisors J.S. Marron and Haipeng Shen)
"Penalized Sieve Deconvolution Estimation of Mixture Distributions with Boundary Effects"
2008
We are pleased to announce the four winners of this year's Student Paper Competition. There were a total of 18 submissions and the four judges of this year's competition, Juana Sanchez, Linda Pickle, Jane Harvill and Peter Craigmile did an outstanding job of reviewing and ranking all papers in a very short period. Many thanks to them for their efforts and patience.
This year's winners are:
- Ming-Hung Kao (advisor John Stufken)
Multi-objective Optimal Experimental Designs for Event-Related fMRI Studies
- Ernest Kwan (advisor Michael Friendly)
Tableplot: A New Display for Factor Analysis
- Adam Rothman (advisor Liza Levina and Ji Zhu)
Sparse Permutation Invariant Covariance Estimation
- Michael Wu (advisor Xihong Lin)
Two-Group Classification Using Sparse Linear Discriminant Analysis
The students will be recognized at the Statistical Computing/Statistical Graphics business meeting at JSM 2009. Congratulations to the winners and many thanks to the judges for their hard work in making this year's competition a success!
2007
- Andrew Finley (advisors Sudipto Banerjee and Alan R. Ek),
spBayes: An R Package for Univariate and Multivariate Hierarchical Point-referenced Spatial Models
- Alexander Pearson (advisor Derick R. Peterson),
A Flexible Model Selection Algorithm for the Cox Model with High-Dimensional Data
- Sijian Wang (advisor Ji Zhu),
Improved Centroids Estimation for the Nearest Shrunken Centroid Classifier
- Hadley Wickham (advisors Di Cook and Heike Hofmann),
Exploratory Model Analysis
2006
- Youjuan Li, University of Michigan-Ann Arbor (advisor: Ji Zhu)
Efficient Computation and Variable Selection for the L1-norm Quantile Regression
- Fan Lu, University of Wisconsin-Madison (advisor: Grace Wahba)
Kernel Regularization and Dimension Reduction
- Rebecca Nugent, University of Washington-Seattle (advisor: Werner Stuetzle)
Clustering with Confidence
- Philip Reiss, Columbia University (advisor: Todd Ogden)
An Algorithm for Regression of Scalars on Images
2005
2004
2003
- Guangzhe Fan, University of Alabama
Regression Tree Analysis using TARGET
- Feng Gao, Emory University
Estimation of Baseline Hazard with Time-Dependent Covariates
- Alexander Gray, Carnegie Mellon
Very Fast Multivariate Kernel Density Estimation via Computational Geometry
- Yufeng Liu, The Ohio State University
Multicateogry Support Vector Machine and Psi-Learning
2002
- Subharup Guha, Ohio State
Benchmark Estimation for Markov Chain Monte Carlo Samples
- Roger Peng, UCLA
Estimating the Renewal Distribution of a Spatial-Temporal Process
- Ronny Vallejos, University of Connecticut
A Recursive Algorithm to Restore Images Based on Robust Estimation of NSHP Autoregressive Models
- Ji Zhu, Stanford University
Kernel Logistic Regression and the Import Vector Machine
2001
- Roberto Gonzalez, York University, U.K.
A Panel Data Simultaneous Equation Model with a Dependent Categorical Variable and Selectivity
- Satoshi Miyata, Ohio State University
Adaptive Freeknot Splines
- Rituparna Sen, University of Chicago
Predicting a Web User's Next Access Based on Log Data
- Mu Zhu, Stanford University
Feature Extraction for Non-parametric Discriminant Analysis
2000
- Heike Hofmann, University of Augsburg
Generalized Odds Ratios for Visual Modeling
- Stijn Vansteelandt, University of Ghent
The Imputation towards Directional Extremes (IDE) Algorithm for Analyzing Sensitiveity to Incomplete Outcomes
(with E. Goetghebeur)
- Iain Pardoe, University of Minnesota
A Bayesian Sampling Approach to Regression Model Checking
- Peter Karcher, University of California-Santa Barbara
Generalized Nonparametric Mixed Effects Models
(with Yuedong Wang)
1999
- Alexandre Bureau, Dept of Biostatistics, University of California, Berkeley
An S-PLUS Implementation of Hidden Markov Models in Continuous Time
(with James P. Hughes and Stephen Shiboski)
- Ilya Gluhohvsky, Dept. of Statistics, Stanford University
Image Restoration Using Modifications of Simulated Annealing
- Peter D. Hoff, Dept of Statistics, University of Wisconsin-Madison
Nonparametric Maximum Likelihood Estimation Via Mixtures
- Muhammad Jalaluddin, Dept of Statistics, University of Wisconsin-Madison
An Algorithm for Robust Inference for the Cox Model with Frailties
(with Michael R. Kosorok)
1998
- Alessandra Brazzale, Department of Mathematics, Swiss Federal Institute of Technology
Approximate Conditional Inference in Logistic and Loglinear Models
- Matt Calder, Department of Statistics, Colorado State University
Scompile: A Compiler for SPLUS
- Steven Scott, Department of Statistics, Harvard University
Bayesian Analysis of a Two State Markov Modulated Poisson Process
- Yan Yu, Statistics Center, Cornell University
Fitting Trees to Curve Data: An Application to Time of Day Patterns of International Calls
(with Diane Lambert)
1997
- Wenjiang J. Fu, University of Toronto
Penalized Regressions: the Bridge versus the Lasso
- Alan Gous, Stanford University
Adaptive Estimation of Distributions using Exponential Sub-Families
- Gareth James, Stanford University
The Error Coding Method and PaCT's
- Ramani S. Pilla, Pennsylvania State University
New Cyclic Data Augmentation Approaches for Accelerating EM in Mixture Problems
1996
- Dmitrii Danilov, St. Petersburg State University
Principal Components in Time Series Forecasting
- Ranjan Maitra, University of Washington
Estimating Precision in Functional Images
- Bob Mau, University of Wisconsin, Madison
Bayesian Phylogenetic Inference via Markov Chain Monte Carlo Methods
(with Michael Newton)
- Chris Volinsky, University of Washington
Applying Bayesian Model Averaging to Cox Models
(with David Madigan, Adrian Raftery and Richard Kronmal)
1995
- Sudeshna Adak, Stanford University
Tree based Adaptive Estimation of Time-dependent Spectra for Nonstationary Processes
- John Gavin, University of Bath
Subpixel Reconstruction in Image Analysis
(with Christopher Jennison)
- William Lu, University of California, Berkeley
The Expectation-Smoothing Approach for Indirect Curve Estimation
- Yingnian Wu, Harvard University
Random Shuffling a New Approach to Match Making