COVID-19 Modeling | JuliaHub

We hope that you and your family are staying safe during this challenging time. Julia Computing staff are working safely from home with our loved ones and we hope you are doing the same.

Due to the COVID-19 global pandemic, Julia Computing has suspended our participation in and the publication of in-person Julia events for the time being. Instead, we will continue to offer and promote online events, including online Julia Computing training courses, Webinars and microtrainings.

Julia Researchers Create Verifiable Neural Net in Julia for COVID-19 Epidemiology Model: In January, Christopher Rackauckas et al. published Using Differential Equations for Scientific Machine Learning, which introduced Universal Differential Equations (UDEs), combining the power of neural networks in Julia with the transparency of differential equations. In a new paper titled Quantifying the Effect of Quarantine Control in COVID-19 Infectious Spread Using Machine Learning, MIT researchers Raj Dandekar and George Barbarastathis describe how they use this method in Julia to create an epidemiology model of COVID-19 spread.

Pumas from Julia Computing for Pharmacology and Pharmacometrics: Pumas from Julia Computing provides end-to-end integration of machine learning and artificial intelligence into pharmacology and pharmacometrics. For more information, click here.

AstraZeneca Researchers Use Julia with a Bayesian Neural Network to Predict Toxicity: A new paper titled A Bayesian Neural Network for Toxicity Prediction describes how researchers from AstraZeneca and Prioris.ai use Julia and Flux.jl to predict toxicity.

Julia for COVID-19 - MIT Open Course Registration Spikes +1,400%: Course registration increased from 20 to 300 when Julia Computing Chief Scientist and MIT Professor Alan Edelman and MIT Visiting Professor David Sanders included COVID-19 modeling in MIT’s Introduction to Computational Thinking course. Course materials are available here.

JuliaCon 2020: Due to COVID-19, JuliaCon 2020 will be held online from July 27-31. JuliaCon ticket refund information will be available soon. Click here for the latest updates.

New Julia Benchmarks: ParallelKmeans.jl is ‘orders of magnitude’ faster than Python’s scikit-learn, R and Clustering.jl. More information is available here.

What Scientists Must Know About Hardware to Write Fast Code: Jakob Nybo Nissen has published a new tutorial: What Scientists Must Know About Hardware to Write Fast Code.

From COBOL to Julia: On COBOL and Legacy Systems: COVID-19 Turmoil Calls For Change explains how and why the finance industry is transitioning from COBOL to modern languages, including Julia. As Julia Computing CEO Viral Shah explains in the article, “The amount of data is just too [large] … they might as well embrace the new world and the new regulations with the new systems.”

Converting from Proprietary Software to Julia: Are you looking to leverage Julia’s superior speed and ease of use, but limited due to legacy software and code? Julia Computing and our partners can help accelerate replacing your existing proprietary applications, improve performance, reduce development time, augment or replace existing systems and provide an extended trusted team to deliver Julia solutions. Leverage experienced resources from Julia Computing and our partners to get your team up and running quickly. For more information, please contact us at info@juliacomputing.com.

Julia Computing Enterprise Products

• JuliaSure: JuliaSure from Julia Computing provides full service development support, production support and indemnification for companies using Julia. Subscriptions are USD $99 per month. Click here to subscribe.

• JuliaTeam: JuliaTeam from Julia Computing lets your entire enterprise work together using Julia. Collaborate, develop and manage private and public packages across your organization, manage open source licenses and benefit from continuous integration, deployment, security, indemnity and enterprise governance. Click here for more information.

• JuliaRun: JuliaRun from Julia Computing helps you scale and deploy Julia using high performance computing (HPC) resources, including large parallel simulations and analyses in the cloud: AWS, Microsoft Azure or Google Cloud. Click here for more information.

• Pumas: Pumas from Julia Computing is a comprehensive platform for pharmaceutical modeling and simulation, providing a single tool for the entire drug development pipeline. Click here for more information.

Free Webinar from Julia Computing - PackageCompiler and Static Compilation in Julia: Did you miss Krisstofer Carlsson’s free Julia Computing Webinar last month on PackageCompiler and Static Compilation in Julia? Julia Computing is publishing all of our free Webinars and Microtrainings online at JuliaComputing.com. Registration is required.

Upcoming Julia Computing Online Trainings, Microtrainings and Webinars: Julia Computing provides a number of online Trainings, Microtrainings and Webinars. All are conducted by advanced Julia Computing instructors. Click the links below to register.

JuliaBox Sunsets May 31, 2020: Julia Computing has decided to sunset JuliaBox on May 31, 2020. If you are a JuliaBox user, you will no longer be able to log in, and if you are a paid JuliaBox subscriber, you will no longer be charged for JuliaBox after that date. We encourage all JuliaBox users to download and install JuliaPro for free before May 31, 2020. JuliaPro is free to download, install and use, and is the fastest on-ramp to Julia. With JuliaPro, you can install and use any private or public packages, including your choice from among more than 2,600 open source packages and more than 250 curated packages.

Julia and Julia Computing in the News

• ZDNet: Could a Neural Network Have Predicted this Pandemic’s Impact?

• Times of India: Some Old Languages Remain Gold: New Jersey Needs COBOL Coders

• WatersTechnology: On COBOL and Legacy Systems: COVID-19 Turmoil Calls For Change

• InsideBigData: Julia Language in Machine Learning: Algorithms, Applications, and Open Issues

• MIT News: Computational Thinking Class Enables Students to Engage in COVID-19 Response

Julia Blog Posts

• Julia in Practice - Building Scattering.jl from Scratch: 1, 2, 3, 4, 5, 6 (Yi-Xin Liu)

• Usage and Testing of Rotation.jl (Yi-Xin Liu)

• FluxArchitectures: Where to Go from Here? Announcing ‘FluxArchitectures’, LSTNet, DA-RNN (Sören Dobberschütz)

• ConstraintSolver.jl: Str8ts, v0.1.0, Table Constraint (Ole Kröger)

• JuliaLang Antipatterns (Lyndon White)

• Measure Distance Between Spectrograms Using Dynamic Time Warping and Optimal Transport (Fredrik Bagge Carlson)

• ParallelKMeans.jl Package

• What Scientists Must Know About Hardware to Write Fast Code (Jakob Nybo Nissen)

Upcoming Julia Online Events

• Webinar: Julia with Kubernetes for Enterprise Scaling with Tanmay Mohapatra (Julia Computing) May 8

• Webinar: GPU Programming in Julia with Tim Besard (Julia Computing) May 14

• Virtual Meetup: Pre-Memorial Day Kickoff of Julia5280 (A Julia Programming Language Virtual Meetup) with Michael Mallari and Julia5280 May 21

• Online Microtraining: Machine Learning Workflow on JuliaRun with Deepak Suresh (Julia Computing) May 26

• Virtual Conference: Plugin AI with Viral Shah (Julia Computing) May 28-29

• Online Microtraining: BinaryBuilder - Building Binaries for Your Julia Packages for Fun and Profit with Elliot Saba (Julia Computing) May 29

• Online Training: Introduction to Julia with Julia Computing June 10-11

• Online Training: Introduction to Machine Learning and Artificial Intelligence in Julia with Julia Computing June 17-18

• Online Training: Parallel Computing in Julia with Julia Computing June 24-25

• Virtual Conference: JuliaCon 2020 with Julia Computing July 27-31

Recent Julia Online Events

• Online: Intro to Lattices; Riemann Theta Function in Julia with Bay Area Julia Users April 11

• Online: Intro to Julia with Matt Bauman (Julia Computing) April 15-16

• Online: PackageCompiler.jl and Static Compilation in Julia with Kristoffer Carlsson (Julia Computing) April 17

• Online: Intro to Machine Learning and Artificial Intelligence in Julia with Matt Bauman (Julia Computing) April 22-23

• Online: Building Production Applications Using Julia with Avik Sengupta (Julia Computing) April 24

• Online: Intro to Parallel Computing in Julia with Matt Bauman (Julia Computing) April 29-30

Julia Jobs, Fellowships and Internships

Do you work at or know of an organization looking to hire Julia programmers as staff, research fellows or interns? Would your employer be interested in hiring interns to work on open source packages that are useful to their business? Help us connect members of our community to great opportunities by sending us an email, and we'll get the word out.

There are hundreds of Julia jobs currently listed on Indeed.com. Click here to apply.

Contact Us: Please contact us if you wish to:

• Purchase or obtain license information for Julia Computing products such as JuliaSure, JuliaTeam, JuliaRun or Pumas

• Obtain pricing for Julia consulting projects for your organization

• Schedule online Julia training for your organization

• Share information about exciting new Julia case studies or use cases

• Spread the word about an upcoming online event involving Julia

• Partner with Julia Computing to organize a Julia event online

• Submit a Julia internship, fellowship or job posting

About Julia and Julia Computing

Julia is the fastest high performance open source computing language for data, analytics, algorithmic trading, machine learning, artificial intelligence, and other scientific and numeric computing applications. Julia solves the two language problem by combining the ease of use of Python and R with the speed of C++. Julia provides parallel computing capabilities out of the box and unlimited scalability with minimal effort. Julia has been downloaded more than 13 million times and is used at more than 1,500 universities. Julia co-creators are the winners of the 2019 James H. Wilkinson Prize for Numerical Software and the 2019 Sidney Fernbach Award. Julia has run at petascale on 650,000 cores with 1.3 million threads to analyze over 56 terabytes of data using Cori, one of the ten largest and most powerful supercomputers in the world.

Julia Computing was founded in 2015 by all the creators of Julia to develop products and provide professional services to businesses and researchers using Julia.