Panagiotis Andreou UNC-Chapel Hill Bayesian Bootstrap for the Transition Matrix of Finite State-Space Markov Chains We study the problem of estimating the transition probability matrix on the context of a discrete-time finite state-space Markov chain, based on an observed path … Read more
Kelly Bodwin Statistics Department California Polytechnic State University (3:30- 4pm) Data Science Education / Q&A Joe Hammond 2nd Order Solutions (4-4:30 pm) Career opportunities at 2nd Order Solutions
Pavlos Zoubouloglou UNC-Chapel Hill Dimension Reduction on Manifolds with an Emphasis on the Torus Recent advancements in the way information is collected have brought along the need to analyze data of a non-Euclidean nature. Dimension reduction has proved to be … Read more
Scott Smith Data Science at Advance Auto Parts Join alum Scott Smith (MS, 2018) to learn about working as a data scientist at Advance Auto Parts.
Optimal transport for stationary Markov chains with an application to the comparison and alignment of weighted graphs Informally, the optimal transport problem is to align, or couple, two distributions of interest as best as possible with respect to some prespecified … Read more
Stochastic Fixed Point Equations arising from PageRank on Stochastic Block Models Stochastic Fixed Point Equations are equations of the form X = f(X), where X is a random variable and f is some function, where the equality holds in distribution. … Read more
Abstract: American Airlines carries over 600,000 passengers daily (pre-pandemic, but flights are returning to pre-pandemic levels!). Planning for every single flight starts almost a year in advance, and requires the input of multiple departments. The Operations Research and Advanced Analytics … Read more
Stochastic Optimization Methods for Outpatient Appointment Scheduling & COVID Testing Under Limited Testing Capacity This talk comprises of two parts based on two unrelated research topics: Part 1 deals with outpatient appointment scheduling problems when patients are unpunctual. We … Read more
Discussions about different areas of research, advisors.
Large Deviations for Small Noise Diffusions Over Long Time Abstract: We study two problems. First, we consider the large deviation behavior of empirical measures of certain diffusion processes as, simultaneously, the time horizon becomes large and noise becomes vanishingly small. … Read more
Factoring Polynomials via the Splitting Circle Method Abstract: Finding the roots of a polynomial is an ill-conditioned problem that requires numerical methods in the general case. Unfortunately, most existing numerical methods do not guarantee convergence when working in finite precision. … Read more
Grouped integrative dynamic factor models for intra-and inter- individual brain networks Abstract: We introduce a novel framework for dynamic factor model-based data integration of multiple subjects, Grouped Integrative Dynamic factor models (GRIDY). This work is a pilot study to suggest … Read more
