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.