Newsletter October 2022

Free Webinars from Julia Computing

1. Trimming, Linearization, and Model Predictive Control (MPC) Design with JuliaSim: Click here to register for a free JuliaSim Webinar, Trimming, Linearization, and Model Predictive Control (MPC) Design with JuliaSim on Wednesday November 2 from 10-11 am Eastern (US). The Webinar is led by Dr. Fredrik Bagge Carlson (Julia Computing Control Systems Team Lead) and Dr. Avinash Subramanian (JuliaSim Control Systems). JuliaSim is a next-generation simulation platform from Julia Computing that combines the latest Scientific Machine Learning (SciML) techniques with equation-based digital twin modeling and simulation. This introductory Webinar is open to anyone familiar with the language of model predictive control (MPC) and related fields. In this Webinar, Dr. Carlson and Dr. Subramanian will demonstrate the typical workflow for a control engineer with JuliaSim. They will show a demo using a realistic case study of controlling a non-linear Research Civil Aircraft Model (RCAM) and present the various steps starting from building the dynamic system model using ModelingToolkit, trimming, linearization about the trim point, as well as the formulation and solution of a closed-loop linear MPC model together with the non-linear observer and plant model. Lastly, a new MPC surrogatization feature will be presented that allows for fast, optimizer-free closed-loop control by learning the control law from data. Space is limited, so please register now to reserve your spot.

2. JuliaSim ModelOptimizer: Model Calibration and Parameter Estimation: Click here to register for a free JuliaSim Webinar, JuliaSim ModelOptimizer: Model Calibration and Parameter Estimation on Wednesday November 9 from 12-1 pm Eastern (US). The Webinar is led by Jacob Vaverka (Julia Computing Sales Engineer). JuliaSim is a next-generation simulation platform from Julia Computing that combines the latest Scientific Machine Learning (SciML) techniques with equation-based digital twin modeling and simulation. This introductory Webinar is open to anyone familiar with the language of model predictive control (MPC) and related fields. In this Webinar, participants will learn how to set up a modeling problem, how to create the inverse problem for parameter estimation and how to generate and visualize the optimized parameters. Space is limited, so please register now to reserve your spot.

3. Fast and Furious Development with JuliaHub Workflows: Click here to register for a free Julia Computing Webinar, Fast and Furious Development with JuliaHub Workflows, on Thursday November 10 from 1-2 pm Eastern (US). The Webinar is led by Deep Datta (Julia Computing Director of Product Management). JuliaHub is the fastest, easiest way to access Julia, the fastest and most powerful high performance open source programming language for scientific and numerical computing. Webinar participants will learn how JuliaHub tooling provides the easiest on-ramp for enterprise development, how to use the Julia package registry, bring new Julia packages into JuliaHub, create a private package repository and bring continuous integration into your workflows. Space is limited, so please register now to reserve your spot.

4. Hierarchical Bayesian Methods for Efficient Generation of Virtual Populations for Quantitative Systems Pharmacology (QSP): Click here to register for a free PumasQSP Webinar, Hierarchical Bayesian Methods for Efficient Generation of Virtual Populations for Quantitative Systems Pharmacology (QSP) on Wednesday November 16 from 10-11 am Eastern. The Webinar is led by Dr. Haris Organtzidis (Julia Computing Research Engineer). PumasQSP is a Julia package and methodology for quantitative systems pharmacology to solve difficult model calibration and analyses in a high-performance and user-friendly manner. In this Webinar, participants will learn how to improve construction of large, expensive virtual population sets, the advantages of advanced virtual population generation methods compared with more standard naive methods, why naïve virtual population methods are inefficient and have limited features, how hierarchical Bayesian methods can be used to generate virtual populations more efficiently by explicitly modeling a population of patients, noise in the data, and domain expertise in the form of prior distributions and how to use these Bayesian methods with Julia Computing’s PumasQSP. Space is limited, so please register now to reserve your spot.

Julia Computing - Coming to a Conference Near You: Julia Computing will be present at a number of upcoming conferences and events. Click below for more information.

• Dallas, TX: American Modelica Conference with Julia Computing Oct 26-28

• Aurora, CO: American Conference on Pharmacometrics (ACoP) with Julia Computing and Pumas-AI Oct 30-Nov 2

• Orlando, FL: Interservice/Industry Training, Simulation and Education Conference (I/ITSEC) with Julia Computing Nov 28-Dec 2

• New Orleans, LA: Conference on Neural Information Processing Systems (NeurIPS) with Julia Computing Nov 28-Dec 9

Julia Computing CEO Dr. Viral Shah at Intel Innovation: Dr. Viral Shah (Julia Computing CEO, co-founder of Julia Computing, co-creator of Julia) joined a panel at Intel to discuss Accelerating Developer Innovation through an Open Ecosystem. Click here to watch.

Julia at ASML Masterclass: ASML, ‘The World’s Supplier to the Semiconductor Industry’ hosted a Julia at ASML masterclass. Contact info@juliacomputing.com if you would like to publicize or organize a corporate Julia event for your organization.

Automatic Differentiation of Programs with Discrete Randomness and Julia for Climate Change: Automatic Differentiation of Programs with Discrete Randomness and Capturing Missing Physics in Climate Model Parameterizations Using Neural Differential Equations are two new papers co-authored by Dr. Chris Rackauckus, Julia Computing Director of Modeling and Simulation. Click here to read Automatic Differentiation of Programs with Discrete Randomness and Click here to read Capturing Missing Physics in Climate Model Parameterizations Using Neural Differential Equations.

NASA Sea Level Change Portal Powered by Julia: The NASA Sea Level Change Portal uses OceanStateEstimation.jl to provide an ‘open-source cloud-native platform with simple Webservice APIs to access the portal’s data, analysis and visualizations’. Click here for more information.