This module will introduce trainees to advanced applications encompassing: object detection, semantic/instance segmentation for image analysis; and LSTMs, GRUs, among other applications, for time series forecasting and anomaly detection for time-series datasets.

Day and Time: December 9, 3-5 p.m. US CT

This session is a part of the ALCF AI for Science Training Series. 

About the Speaker:

Asad Kahn is a physics PhD Student in the gravity group at the National Center for Supercomputing Applications. He is interested in applying machine learning, and specifically deep learning techniques to accelerate discoveries in physics. Asad is also interested in the theoretical underpinnings of Computer Vision, NLP, Unsupervised Learning, and High Perfomance Parallel Computing. Before grad school, he studied Mathematics and Physics for Bachelors of Science at the University of Minnesota, Twin Cities. 

Kyle Felker is a computational scientist at Argonne National Laboratory.