The MIDAS Webinar Series features research by MIDAS members, and is open to the public.
Date: Friday, June 27, 2025
Time: 1:00 – 2:00pm EDT
Speaker: Wasiur KhudaBukhsh, PhD
Title: Parameter Inference Based on Sparse Data
Abstract: In this talk, I will discuss the problem of parameter inference in the context of epidemic modelling when we have access to only a sparse data set, which is almost always the case. I will introduce a new statistical methodology called the Dynamic Survival Analysis (DSA) and discuss its theoretical guarantees under different data types and varying regimes of sparsity. No prior background in statistics is required. The method was developed during the Ohio State University (OSU)’s COVID-19 response modelling efforts.
Bio: Dr. Wasiur KhudaBukhsh is an Assistant Professor in the School of Mathematical Sciences, University of Nottingham, UK. He is primarily interested in probability theory and statistics, and their applications to epidemiology and systems biology. In particular, he is interested in studying epidemics on (random) graphs and developing methodologies for parameter inference.