Ann Arbor Julia Meetup 2023

1. Welcome, Julia Language intro - Michael Bologna
2. Dashboarding with Dash.jl - Steven Whitaker
3. Reproducible Research & Awesome Documentation - Prof. Jeff Fessler
4. Keynote: Automating the Discovery of Physics with Julia's SciML - Dr. Chris Rackauckas (Details below)
5. Public Q&A + Meetup

Light food provided.

Recommend Parking [5 minute walk]: lot NC8 at Fuller and Beal that has 74 visitor spots: https://ltp.umich.edu/lot/?xyz=fw

Scientific machine learning (SciML) methods allow for the automatic discovery of mechanistic models by infusing neural network training into the simulation process. In this talk we will showcase Julia's SciML ecosystem for mixing machine learning with the scientific process. Demonstrations of the automated discovery of relativistic corrections to black hole physics to the construction of earthquake-safe buildings showcase the successes of the techniques throughout scientific domains. Real-world use cases will be discussed, such as how SciML has led to improved trajectory planning in track-side computers for Formula 1 races, accelerated the clinical trials of the Covid vaccine, and allowed for crash testing computers to predict forces in a way that saved days of customer time on multi-million dollar machines. Live interactive tutorials would be shown so that the audience can replicate the results on their own computer and know leave with familiarity in how to use these tools for their own work.

Bio: Dr. Chris Rackauckas is the VP of Modeling and Simulation at JuliaHub, the Director of Scientific Research at Pumas-AI, Co-PI of the Julia Lab at MIT, and the lead developer of the SciML Open Source Software Organization. For his work in mechanistic machine learning, his work is credited for the 15,000x acceleration of NASA Launch Services simulations and recently demonstrated a 60x-570x acceleration over Modelica tools in HVAC simulation, earning Chris the US Air Force Artificial Intelligence Accelerator Scientific Excellence Award. See more at https://chrisrackauckas.com/. He is the lead developer of the Pumas project and has received a top presentation award at every ACoP in the last 3 years for improving methods for uncertainty quantification, automated GPU acceleration of nonlinear mixed effects modeling (NLME), and machine learning assisted construction of NLME models with DeepNLME. For these achievements, Chris received the Emerging Scientist award from ISoP.

Generously hosted by Prof. Jeff Fessler and the University of Michigan. Run by Great Lakes Consulting: https://glcs.io