From February 6 through March 26, 2024, the ALCF will host an 8-part weekly virtual training series to teach undergraduates and graduates the fundamentals of using world-class supercomputers to advance the use of AI for research.
Trainees will learn the basics of neural networks, opening up the black box of machine learning by building out by-hand networks for linear regression to increase the understanding of the math that goes into machine learning methods.
Bethany Lusch is a Computer Scientist in the data science group at the Argonne Leadership Computing Facility at Argonne National Lab. Her research expertise includes developing methods and tools to integrate AI with science, especially for dynamical systems and PDE-based simulations. Her recent work includes developing machine-learning emulators to replace expensive parts of simulations, such as computational fluid dynamics simulations of engines and climate simulations. She is also working on methods that incorporate domain knowledge in machine learning, representation learning, and using machine learning to analyze supercomputer logs. She holds a Ph.D. and MS in applied mathematics from the University of Washington and a BS in mathematics from the University of Notre Dame.
Nicola Ferrier is a senior computer scientist as part of the Mathematics and Computer Science division at Argonne National Laboratory. Ferrier's research interests are in the use of computer vision (digital images) to control robots, machinery, and devices, with applications as diverse as medical systems, manufacturing, and projects that facilitate “scientific discovery” (such as her recent project using machine vision and robotics for plant phenotype studies). She will be speaking on AI @ Edge.