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Stochastic Modeling and Computational Statistics

SMAC talks are held each Friday during fall and spring semesters from 10:10 AM to 11:00 AM in 327 Thomas Building. Talks last 40 minutes, with time for clarification questions. The last 10 minutes are for open-ended discussion.

The general guidelines for each talk: 

  1. 40 minutes for each talk + 10 minutes for discussion.
  2. The talk should be accessible to all grad students who have completed 1 year of the program.
  3. Informal style. For instance, chalk and blackboard talks are welcome.
  4. Interruptions during the talk are welcome but they should only be for clarifications; longer questions are to be left to the discussion period.
  5. Unpublished work may not be shared or discussed outside the group without the permission of the speaker/author.
  6. While a large proportion of the talks may be related to stochastic modeling and computing, a much broader list of topics have also been discussed in this series.


Date Speaker Topic
August 25 Kei Hirano, Economics, Penn State

Local asymptotics for point forecasting applications

September 1 Jogesh Babu, Statistics, Penn State Gaussian Mixture Models
September 8 Likun Zhang, Statistics, (grad) Penn State Summer Internship Discussion
September 15 Yifan Zhang, Marketing, (grad) Penn State Scalable Bayesian Inference of the Hidden Markov Model
September 22 Krishnakumar Balasubramanian, Princeton U. On Stein's Identity and Near-Optimal Estimation in High-dimensional Index Models
September 29 Qunhua Li, Statistics, Penn State Irreproducible discovery rate regression with applications on Hi-C chromatin loops
October 6 No seminar (Marker Lecture)  
October 13 Nicholas Sterge, (grad) Statistics, Penn State Statistical Consistency of Kernel PCA with Random Features
October 20 Don Richards, Statistics, Penn State Statistical Properties of the Risk-Transfer Formula in the Affordable Care Act
October 27 Efstathia Bura, George Washington U. and Vienna University of Technology  Near-equivalence in Forecasting Accuracy of Linear Dimension Reduction Methods in Large Panels of Macro-variables
November 3 Claire Thomas, Biology, Penn State Looking for patterns in network forming proteins
November 10 Xinyu Zhang, (post-doc) Statistics, Penn State Parsimonious Model Averaging with a Diverging Number of Parameters
November 17 Greg Rice, Statistics, U. of Waterloo Inference for the autocovariance of a functional time series under conditional heteroscedasticity
November 24 Thanksgiving break  
December 1 Dennis Lin, Statistics, Penn State Ghost Data

A look back at previous SMAC TALKS.