Inverse Problems Seminar: Olalekan Babaniyi
Inverse Problems Seminar
hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems
Olalekan Babaniyi, Ph.D.
Assistant Professor, Rochester Institute of Technology
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Abstract:
Inverse problems governed by differential equation models show up in many applications in science and engineering. I present an Inverse Problem PYthon library (hIPPYlib) for solving large-scale deterministic and Bayesian inverse problems governed by partial differential equations (PDEs). hIPPYlib implements state-of-the-art scalable algorithms that exploit the structure of the problem, notably the Hessian of the log posterior. The key property of the algorithms implemented in hIPPYlib is that the solution is computed at a cost, measured in forward PDE solves, that is independent of the parameter dimension. I will show applications of some of the algorithms to inverse problems in the ice sheet flow modeling, and medical imaging fields.
Speaker Bio:
Olalekan Babaniyi is currently an assistant professor in the School of Mathematical Sciences at Rochester Institute of Technology (RIT). Prior to joining RIT, he was a postdoctoral scholar at the University of California, Merced, working on developing computational tools to solve large scale inverse problems. Prior to that, he was a postdoctoral associate at Duke university working on inverse problems in the medical imaging field. He earned his Bachelors, Masters, and PhD degrees at Boston university where he began working on inverse problems as an undergraduate student.
Intended Audience:
Undergraduates, graduates, and experts. Those with interest in the topic.
Keep up with Inverse Problems Seminars on the Inverse Problems Seminar webpage.
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Event Contact: Olalekan Babaniyi | obsma@rit.edu
Event Snapshot
When and Where
Who
Open to the Public
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No