Julia Expert Meet Up
SciML + Julia 1.9
Join us in London on April 21st at 5:30 PM for a live meet-up with long-time Julia contributors Dr. Chris Rackaukas and Avik Sengupta.
Julia collaboration has taken a revolutionary leap forward with JuliaHub Projects.
Friday, APRIL 21st | 5:30 PM BST
Julia Expert MeetUp
SciML + Julia 1.9
Join us in-person, live in London on Friday, April 21st at 5:30 PM (BST) for the opportunity to hear from two leading Julia contributors.
Dr. Chris Rackauckas is the VP of Modeling and Simulation at JuliaHub, the lead developer of the SciML Open Source Software Organization, and Co-PI of the Julia Lab at MIT. He'll be showcasing the power of SciML and sharing the ways that SciML methods, like universal differential equations, are being used.
Avik Sengupta, long-time Julia language contributor and VP of Engineering at JuliaHub, will walk through the new features of Julia 1.9 including the fixes to the Time to First Execution (TTFX) issue as well as other improvements to threading, packages, and compilation.
This is the perfect opportunity to learn from experienced Julia experts while networking with other Julia users.
If you’re in the London area, don't miss out on this informative and engaging session.
Please note this is an in-person-only event and seating is limited. Reserve your seat now.
Snacks and wine + beer will be served.
Date: Friday, April 21st
Time: 5:30 PM BST
University of London
G11, Senate House
Malet St, London WC1E 7HU
Register now to reserve your spot!
Combine models with tools like DiffEqFlux and NeuralPDE to discover missing physics and generate digital twins.
Combine with Pre-Built Models and Digital Twins
Grab complete models from the JuliaSim Model Store and compose the pieces to accelerate the design process.
Specialized Numerical Environments
Use the latest numerical tools, like discontinuity-aware differential equation solvers, high-performance steady state solvers, and domain-specific environments.
Blending classical physical modeling with modern Scientific Machine Learning techniques.
JuliaSim is a next generation cloud-based simulation platform, combining the latest techniques in Scientific Machine Learning with equation-based digital twin modeling and simulation. Our modern ML-based techniques accelerate simulation by up to 500x, changing the paradigm of what is possible with computational design. The premise of the software is to facilitate the design and accelerate challenging real-life models of considerable complexity.
JuliaSim allows the user to import models directly from the Model Store (more information below) into the Julia environment, making it easy to build large complex simulations. The user-friendly GUI facilitates the process and makes simulation more accessible to a wider audience.
JuliaSim produces surrogates of blackbox (and regular) dynamical systems using Continuous Time Echo State Networks (CTESNs). This novel technique allows, amongst other features, for implicit training in parameter space to stabilize the ill-conditioning present in stiff systems.
Learn more about the JuliaSim Ecosystem
Julia Computing delivers JuliaSim as an answer to accelerating simulations through digital-twin (or surrogate) modeling. By blending classical, physical modeling with advanced scientific machine learning (SciML) techniques, JuliaSim provides a next-generation platform for building, accelerating, and analyzing models.