**Group meetings are for students and faculty at CMU and UPitt.**

The STAMPS webinars are open to everyone.

The STAMPS webinars are open to everyone.

**Following University directives, meetings will transition to virtual presentation from March 20 going forward, from 1:30PM - 2:30PM EST as usual.**

### January 24 - Shamindra Shrotriya (CMU, Department of Statistics & Data Science) #

##### * Predictive Inference of a Wildfire Risk Pipeline in the United States Proposal Track *

### January 31 - Troy Raen (University of Pittsburgh, Department of Physics and Astronomy) #

##### * A Bayesian Belief Network for Streaming Classification of the Variable Night Sky (Part 1) *

### February 7 - Troy Raen (University of Pittsburgh, Department of Physics and Astronomy) #

##### * A Bayesian Belief Network for Streaming Classification of the Variable Night Sky (Part 2) *

### February 14 - Michael Stanley (CMU, Department of Statistics & Data Science) #

##### * Improving Upon the Bayesian Estimation of Carbon Fluxes (Part 1) *

### February 28 - Michael Stanley (CMU, Department of Statistics & Data Science) #

##### * Improving Upon the Bayesian Estimation of Carbon Fluxes (Part 2) *

### March 20 - Samuel Fletcher (University of Minnesota) #

##### * Severity and its potential applications in particle physics data analysis *

### April 3 - Biprateep Dey (University of Pittsburgh, Department of Physics and Astronomy) #

##### * Using Capsule Networks to find galaxy redshifts from images *

**Overview:**We will discuss methods to infer redshifts of galaxies from images using a combination of Capsule networks and Random Forest Regression.

### April 10 - Vikesh Siddhu (CMU, Pittsburgh Quantum Institute) #

##### * (Non)-Convex Optimization in Quantum Information *

### April 24 - Aaditya Ramdas (CMU, Department of Statistics & Data Science) #

##### * Applications of sequential testing in particle physics *

### May 1 - Hamish Gordon (CMU, Engineering Research Accelerator and the Center for Atmospheric Particle Studies) #

##### * Clouds and aerosols in weather and climate prediction *

### May 8 - Nic Dalmasso (CMU, Department of Statistics & Data Science) #

##### * Conditional Density Estimation Tools in Python and R with Applications to Photometric Redshifts and Likelihood-Free Cosmological Inference *

### May 15 - Lorenzo Tomaselli (CMU, Department of Statistics & Data Science) #

##### * Chemical Fingerprinting of Smoke from Western US Wildfires *

### May 22 - Liz Wayne (CMU, Department of Biomedical Engineering and Chemical Engineering) #

##### * Understanding macrophage phenotype heterogeneity and its implications in disease *

### June 12 - Ann Lee (CMU, Department of Statistics & Data Science) #

##### * A Geometry-Based Metric for Mixture Distributions *

### June 19 - Xiaoyi (Ivy) Gu (CMU, Department of Statistics & Data Science) #

##### * Computationally efficient density estimation via tree-based adaptive histograms and its applications *

### July 10 - Public Webinar: Adam Sykulski (Department of Mathematics and Statistics, Lancaster University) #

### July 24 - Boyan Duan (CMU, Department of Statistics & Data Science) #

##### * Introduction to interactive testing*

### Aug 7 - Guanglu Zhang (CMU, Department of Mechanical Engineering) #

##### * A Solution Interval Method for Least Squares Parameter Estimation in Nonlinear Models *

### Aug 14 - Public Webinar: Tommaso Dorigo (INFN-Padova) #

### Aug 21 - Parker Holzer (Department of Statistics & Data Science, Yale University) #

##### * Discovering Exoplanets With Hermite-Gaussian Linear Regression *