JuliaSim is a next generation cloud-based modeling and simulation platform, combining the latest techniques from scientific machine learning with equation-based digital twin modeling and simulation. More information is available on the new JuliaSim product page.
JuliaCon 2021 - Free and Online - July 28-30 - Register Today
Free Registration: JuliaCon 2021 will be free and online. Last year’s JuliaCon brought together 30,000 online participants from over 115 countries. Click here to register.
Sponsorship: JuliaCon is an excellent opportunity for sponsors to support and show their support for Julia. Platinum, gold and silver sponsorships are available. Current and recent JuliaCon sponsors include RelationalAI, Julia Computing, PumasAI, Conning, QuEra, Amazon, Facebook, Google, Microsoft, Intel, Nvidia, JP Morgan, Capital One, BlackRock, Invenia, Gordon and Betty Moore Foundation, Juspay, Zapata, University of Maryland School of Pharmacy, Jeffrey Sarnoff, Alfred P. Sloan Foundation, Replit, Maven, Gambit, Tangent Works, Alan Turing Institute, EVN, Maven and Voxel8.
JuliaHub from Julia Computing: JuliaHub is the entry point for all things Julia: explore the ecosystem, build packages and deploy a supercomputer at the click of a button. JuliaHub also allows you to develop Julia applications interactively using a browser-based IDE or by using the Pluto notebook environment and then scale workloads to thousands of cores . Version 5 features a brand new user interface, reduced app startup latency, and many more usability enhancements. JuliaHub is the easiest way to start developing in Julia or share your work using dashboards and notebooks. A free JuliaHub tutorial from Dr. Matt Bauman (Julia Computing) is available on YouTube.
Pumas from Julia Computing and Pumas-AI: Pumas 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 Webinars from Julia Computing and Pumas-AI: Register today to participate in a free Julia Computing or Pumas-AI Webinar. Each free Webinar is one hour.
|Length of Webinar
|Pumas 2.0 Feature Series: Censored and Truncated Data Models
|Dr. Andreas Noack and Dr. Patrick Mogensen, Julia Computing and Pumas-AI
|Thu Apr 15
|9:30 - 10:30 am Eastern (US)
|Interactive Development at Scale on JuliaHub
|Dr. Matt Bauman, Julia Computing
|Fri Apr 16
|12 noon - 1 pm Eastern (US)
|Deployment of Models and Apps on JuliaHub
|Dr. Matt Bauman, Julia Computing
|Fri Apr 23
|12 noon - 1 pm Eastern (US)
|Performance Benchmarking in Julia
|Jameson Nash, Julia Computing
|Thu Apr 29
|12 noon - 1 pm Eastern (US)
HPCWire Selects Alan Edelman for 2021 People to Watch List: HPCWire recognized Alan Edelman in its 2021 People to Watch list. Alan Edelman is Co-Founder and Chief Scientist at Julia Computing, Co-Creator of Julia, MIT Professor of Applied Mathematics and Principal Investigator of the MIT Julia Lab and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).
Julia Docs Published As Part of Google Season of Docs: Julia contributors published new Julia docs as part of the Google Season of Docs and the Julia Season of Docs. Mentors include Cameron Pfiffer, Hong Ge, Martin Trapp, Chris Rackauckas, Dhairya Gandhi, David Sanders and other members of the Julia community.
Elizaveta Semenova: Gaussian Processes in Julia and Turing (Google Season of Docs)
Maja Gwóźdź: The Unified Documentation of Scientific Machine Learning (Google Season of Docs)
Liliana Badillo: Reinventing the FluxML Website (Google Season of Docs)
Luca Ferranti: Developing JuliaIntervals Documentation (Julia Season of Docs)
Satellite Launched Into Space Using Julia: Ronan Arraes Jardim Chagas is the “mission architect and technician responsible for the altitude and orbit control subsystem (AOCS) for the Brazilian satellite Amazonia-1, launched on Feb 28.” He explains that Julia is used for:
General mission analysis such as fuel budget computation, orbit planning, ground station visibility analysis, etc.
The Amazonia-1 AOCS simulator is 100% written in Julia using the amazing DifferentialEquations.jl ecosystem. The results obtained from it greatly match the real satellite dynamics obtained after the orbit injection.
The AOCS telemetry analysis system is also 100% written in Julia. The problem with AOCS is that you often need to get a lot of data from the satellite telemetry and plot many graphics. During the integration and testing, I needed to do this daily. Hence, we developed inside INPE a Julia package that automatically fetches the raw telemetry from the database, process, and output what we want. Today I can very easily see the overall satellite AOCS state with just two or three commands.
The in-orbit sensor calibration required the implementation of Kalman filters, which, of course, was coded in Julia.
Furthermore, “We can now say that Julia is truly a part of the Brazilian space program. Finally, I want to thank all you developers that created Julia and the fantastic package ecosystem. It really made a lot of difference to me! I am 100% sure that I would have a lot more work if I had to use another computing language.”
Satellite image from Amazonia-1 Satellite, Instituto Nacional de Pesquisas Espaciais (INPE)
Los Alamos Scientists Use Julia for SmartTensors AI Platform: SmartTensors is a new AI tool developed by Los Alamos researchers to ‘make vast data streams intelligible and explainable … SmartTensors sifts through millions of millions of bytes of diverse data to find the hidden features that matter, with significant implications from health care to national security, climate modeling to text mining, and many other fields.’ More information is available here.
‘Safe Blues’ Team Uses Scientific Machine Learning in Julia to Model COVID-19 Spread: Researchers at ‘MIT, Cornell and several other colleges in England, Australia and New Zealand’ are using Scientific Machine Learning (SciML) in Julia to analyze the spread of a virtual phone virus they created to mimic COVID-19 transmission. More information is available at SafeBlues.org and “Safe Blues: The Case for Virtual Safe Virus Spread in the Long-Term Fight Against Epidemics.”
Modeling Complexity with Symbolics.jl and ModelingToolkit.jl: Chris Rackauckas joined Federico Carrone to discuss Symbolics.jl and ModelingToolkit.jl. Click here for the full interview.
Physics-Informed Neural Networks (PINNs): Chris Rackauckas joined Jousef Murad to discuss Physics-Informed Neural Networks (PINNs). Click here to watch.
GitHub Satellite India - Building the Julia Programming Language and Its Community: Julia Computing co-founder and CEO and Julia co-creator Viral Shah presented Building the Julia Programming Language and Its Community as part of GitHub Satellite India. The full presentation is available on YouTube.
Circuitscape in Julia: Circuitscape is a Julia application that uses electrical circuit theory to predict animal, plant and human migration in response to climate change and other events. A new paper describes some of the advances realized by recoding Circuitscape in Julia, including increased efficiency, parallelism, major speed improvements and enabling assessments with higher resolution data or across a larger domain. The paper draws on examples from a collection of 572 Circuitscape applications.
Julia and Julia Computing in the News
The Next Platform: Why Julia Is Turning Heads in 2021
Developpez: Julia Est le Lauréat du Prix de la DARPA pour Créer un Framework
Analytics India: Top 8 Julia Libraries For Data Visualisation
Analytics Insight: A Rundown - Top Programming Languages in Machine Learning in 2021
Inside Big Data: Above the Trend Line
TechRepublic: Jupyter Has Revolutionized Data Science, and It Started with a Chance Meeting Between Two Students
Science Times: Top 5 Skills Needed To Become A Data Scientist
Stockhouse: Zapata Computing and KAUST Partner to Bring Quantum Computing to the Middle East for the Advancement of Computational Fluid Dynamics
Techzine: Nieuwe Versie 1.6 van Julia Is Voor Langere Termijn
SD Times: Julia 1.6 Released
Dev Class: Julia 1.6 Is Feted as Next LTS Release as Team Shows Off Compiler Tweaks
Channel Asia: Eclipse Hosts Visual Studio Code Extensions Marketplace
Business Because: MIT Master Of Business Analytics Review
Los Alamos National Laboratory: New AI Tool Makes Vast Data Streams Intelligible and Explainable
CircleID: Five Considerations When Selecting Your Data Science Team
HPCWire: HPCWire Unveils Honorees for Its 2021 People to Watch Feature
Julia Blog Posts
Julia 1.6 Highlights (Jeff Bezanson, Ian Butterworth, Nathan Daly, Keno Fischer, Jameson Nash, Tim Holy, Elliot Saba, Mosè Giordano, Stefan Karpinski, Kristoffer Carlsson)
Google Season of Docs 2020-2021 Wrap-Up (Logan Kilpatrick)
Developing JuliaIntervals Documentation (Luca Ferranti)
A Simplified E-graph Implementation (Philip Zucker)
Union Find Dicts: Dictionaries Keyed on Equivalence Classes (Philip Zucker)
Poor Man's Guide to Despecialization (Bogumił Kamiński)
Construction vs. Conversion in Julia (Bogumił Kamiński)
Expand Your DataFrames.jl Toolbox: the Flatten Function (Bogumił Kamiński)
Sorting Data By a Transformation of Columns in DataFrames.jl (Bogumił Kamiński)
Benchmarking and Profiling Julia Code (Ole Kröger)
Upcoming Julia Online Events
Online Meetup: Fall In Love with Julia: Hands-on Differential Equations with Stephan Sahm and Julia User Group Munich Apr 12
Virtual Conference: JuliaCon 2021 Jul 28-30
Recent Julia Online Events
Online Training: Introduction to Machine Learning and Artificial Intelligence Using Julia with Dr. Matt Bauman (Julia Computing) Mar 11-12
Webinar: Pumas 2.0 Feature Series - Uncertainty Quantification with Dr. Chris Rackauckas and Dr. Vijay Ivaturi (Pumas-AI) Mar 16
Webinar: Pumas 2.0 Feature Series - First Order Methods for Non-Gaussian NLME Models in Pumas with Dr. Andreas Noack (Julia Computing) and Mohamed Tarek (Pumas-AI) Mar 23
Webinar: Pumas 2.0 Feature Series - Beyond Gaussian Random Effects with Mohamed Tarek (Pumas-AI) and Dr. Andreas Noack (Julia Computing) Mar 30
Virtual Conference: National Kidney Foundation Spring Clinical Meetings with Otsuka Pharmaceutical Development & Commercialization and Pumas-AI Apr 6-10
Julia Jobs, Fellowships and Internships
Postdoctoral Research Fellow in Machine Learning: The University of Auckland, New Zealand, is looking to make a two-year postdoctoral appointment to join the Machine Learning in Julia project, a collaboration with the Alan Turing Institute in the United Kingdom. A PhD in mathematics, statistics, computer science or related field is essential, as is experience in scientific programming (Julia preferred) and some software engineering skills. Qualified candidates can find out more about the role by emailing Sebastian Vollmer (email@example.com) or Anthony Blaom (firstname.lastname@example.org). A significant part of the role will be to provide support for the development of the MLJ machine learning toolbox: https://github.com/alan-<wbr>turing-institute/MLJ.jl
Senior HPC Software Engineer at Liquid Analytics: Liquid Analytics uses artificial intelligence for consulting including retail, technology and market research. They are based in Toronto but hire remote team members anywhere worldwide. More information is available here.
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.
Contact Us: Please contact us if you wish to:
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 by users at more than 10,000 companies 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 for businesses and researchers using Julia.