Conference on High-Dimensional Statistics

High-Dimensional Statistics has grown out of modern research activities in diverse fields such as science, technology, and business, aided by powerful computing. It encompasses several emerging fields in statistics such as high-dimensional inference, dimension reduction, data mining, machine learning, and bioinformatics.


All talks will be given at Alter Hall, 7th floor.


Time Event Information

Opening Remarks by Hai-Lung Dai, Provost and Senior Vice President for Academic Affairs

Introduction by Moshe Porat, Dean, Fox School of Business
9:00 am – 10:30 am Session I: High-Dimensional Statistical Inference
Session Chair:
Stan Altan, Senior Research Fellow, Johnson & Johnson
  • Jianqing Fan: Endogeneity in Ultra High Dimensional Models
  • Liza Levina: Mixed and Covariate-Dependent Graphical Models
10:30 am – 10:45 amCOFFEE BREAK
10:45 am – 12:15 pm Session II: Spatio-Temporal Data Applications
Session Chair:
Kris Ghosh, Vice President of Informatics, Covance
  • Sudipto Banerjee: On Hierarchical Modeling for Massively Scalable Inference from Spatially Oriented Datasets
  • Zoran Obradovic: Learning from High Dimensional Partially Observed Temporal Data
12:15 pm – 1:30 pm LUNCH
Keynote Speaker: Sastry Pantula: Big Data and Opportunities in the International Year of Statistics
  • Introduction by Paul A. Pavlou, Director, PhD Program in Business Administration, Fox School
1:30 pm – 3:00 pm Session III: Computational Algorithms for High-Dimensional Data
Session Chair:
Joseph Heyse, Vice President of Biostatistics, Merck Research Labs
3:00 pm – 3:15 pmCOFFEE BREAK
3:15 pm – 4:45 pm Session IV: Genomic Applications
Session Chair:
Eric Ross, Director, Assistant Vice President of Biometrics and Information Sciences, Fox Chase Cancer Center
  • Mark van der Laan: Targeted Learning with High Dimensional Data
  • John Storey: Cross-Dimensional Inference of Dependent High-Dimensional Data
4:45 pm – 5:00 pmClosing Remarks: Sanat Sarkar, Cyrus H.K. Curtis Professor and Chair, Department of Statistics