Scientific Computing with Python
Austin, Texas • July 6-12
Registration - 100% Full

Sponsors

 

Michael McKerns

Mike has over fifteen years of teaching experience in physics, applied math, and computing, and has taught twenty financial and science workshops in the past year alone. He been a research scientist at Caltech since 2002, where he has served as manager and lead developer for two $15M software projects on predictive science and large-scale computing. In the past five years, his software has been the backbone of several research projects on large-scale risk analysis and predictive science. Mike is a co-founder of the UQ Foundation, a non-profit for the advancement of predictive science, and co-creator of OUQ theory, a rigorous mathematical framework for uncertainty quantification. Mike has a B.S. in Applied Physics from Notre Dame, and a Ph.D. in Physics from the University of Alabama Birmingham. He has been developing parallel and distributed computing software infrastructure for ten years, and large-scale optimization and risk analysis software frameworks for over five years. His software has over 15,000 total downloads to unique IP addresses, including one library available in Fedora and RHEL distributions.

Presentations

help serialize all of python with dill

the failure of python object serialization: why HPC in python is broken, and how to fix it

Tuesday 11:45 a.m.–12:15 p.m. in Room 204