The College of Science in the Department of Mathematics discussed a seminar entitled Using Persistent Homology to Classify the Data Space for an Artificial Neural Network for postgraduate student Sajjad K. Hasan. This seminar focuses on applying Topological Data Analysis (TDA), specifically Persistent Homology, to assess the usefulness of geophysical well logs in predicting compressional sonic transit time (DT).
