Student paper competition

Winners

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

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

• Mingyu Cao, Carnegie-Mellon University (advisor: Bill Eddy)
  Estimation of Antenna Sensitivities for Parallel MRI
• Robert B. Gramacy, University of California, Santa Cruz (advisor: Herbert Lee)
  Adaptive Exploration of Computer Experiment Parameter Spaces
• Jouni Kerman, Columbia University (advisor: Andrew Gelman)
  Fully Bayesian Computing
• Lingsong Zhang, University of North Carolina at Chapel Hill (advisor: Steve Marron)
  Singular Value Decomposition and Its Visualization

2004

• Rima Izem, University of North Carolina -- Chapel Hill
  Analysis of Nonlinear Variation in Thermal Performance Curves
• Marloes Maathuis, University of Washington -- Seattle
  Reduction Algorithm for MLE for the Distribution Function of Bivariate Interval Censored Data
• Kary Myers, Carnegie Mellon
  The Billion Byte Brain: Combining Physiological Data and Gigabytes of Images to Improve Maps of Brain Activity
• J. Kyle Wathen, University of Texas
  Implementation of Backward Induction for Sequentially Adaptive Clinical Trials

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