We wanted to thank all Julia users and well wishers for the support and for being part of the Julia Community, and to give an update on some exciting developments for March 2018:
JuliaCon is coming to University College London Aug 7-11, 2018.
Corporate Sponsorship: JuliaCon 2018 has corporate sponsorship opportunities available. JuliaCon 2018 will be held Aug 7-11, 2018 at University College London.
Call for Proposals: Everyone who is interested is strongly encouraged to submit a proposal, regardless of level of experience with Julia or as a speaker. JuliaCon thrives on having talks ranging from introductory to advanced. If you are reading this and work with Julia in any form, you are encouraged to submit a proposal. Proposals may be submitted for talks, lightning talks, workshops, posters and package collaboration. Other ideas and suggestions, such as a topic or focus for a hackathon, are also welcome. Please click here for more details, proposal advice and submission.
Mentorship for First-Time Speakers: JuliaCon 2018 offers mentorship for first-time speakers and presenters. Details are available here. Please indicate in your proposal submission if you would be interested in mentorship. If you are willing to mentor a first-time speaker including providing feedback on abstracts or presentations, discussing presentation skills and more, please sign up here.
Application for Travel Assistance: If financial assistance will impact your ability to attend JuliaCon in London Aug 7-11, you are encouraged to apply now. Please note that you can begin your application today and finish later; assessing demand for financial assistance early will help us to better accommodate more people. The submission deadline is April 30.
Please visit our website for the latest Julia case studies.
Now-Casting Economics: Now-Casting Economics uses Julia to reduce macroeconomic modeling time from weeks to days. According to Senior Economists Thomas Hasenzagl and Filippo Pellegrino, “Given the computational intensity, Julia seemed the natural programming language to use. Julia significantly improved the computational efficiency and speed of the nowcasting model. Switching from Matlab to Julia reduced the run time from weeks to days.”
Fugro Roames: Fugro Roames engineers use a combination of LiDAR and high resolution aerial photography to create a detailed 3D map of the physical condition of the electrical network and possible encroachment. Then they use machine learning to identify points on the network that have failed or are at risk of failure.
MIT Robot Locomotion: The MIT Robot Locomotion Group programs legged robots to walk so that they can explore remote regions, assist in disaster response or travel places that are unsafe for humans, such as minefields and contaminated sites. Roboticists Robin Deits and Twan Koolen explain: “We find Julia to be more productive than Java. Compared to C++, we found that Julia is much more productive, while retaining similar performance. Julia’s Python-like productivity and C++-like speed allow us to avoid having to make decisions regarding when to move to the fast language.”
Artificial Intelligence and Machine Learning: Julia Computing continues to undertake a number of innovative consulting and custom development projects involving artificial intelligence, machine learning and deep learning. Julia’s machine learning capabilities are integrated with JuliaDB, making it possible to ingest data from a variety of sources, apply machine learning and generate insights quickly. Julia Computing employs many of the core developers of Julia and its machine learning packages. Please contact us if you are interested in partnering with Julia Computing on projects involving artificial intelligence, machine learning or deep learning.
Julia for Government: Julia’s use by government agencies continues to grow. Users include the Federal Aviation Administration (FAA), Federal Reserve Bank of New York (FRBNY), Brazilian National Bank for Economic and Social Development (BNDES), National Aeronautics and Space Administration Jet Propulsion Laboratory (NASA JPL), Lawrence Berkeley National Laboratory, Ames Laboratory, Langley Research Center, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, National Energy Research Scientific Computing Center (NERSC), Oak Ridge National Laboratory, and the National Renewable Energy Laboratory (NREL).
Parallel Computing with JuliaBox: JuliaBox is available at scale with parallel computing capabilities. JuliaBox runs in the cloud on dozens, hundreds or thousands of nodes, depending on your requirements. As always, there is no download required with JuliaBox - you can run it straight from your browser using a Jupyter notebook. Full JuliaBox documentation including examples and reference information for parallel functionality is available here. For pricing, a free 2 week trial, or more information about parallel computing with JuliaBox, please contact us and let us know how many nodes you require. The free version of JuliaBox continues to be fully supported for all current and new users with the latest version of Julia, package updates, new features and improved memory, flexibility and reliability.
JuliaPro: JuliaPro is the fast, free way to install the latest version of Julia on your laptop or desktop including the Julia compiler, profiler, integrated development environment, 100+ carefully curated packages, data visualization and plotting. There is also a paid version, JuliaPro Enterprise, which includes all of the features of JuliaPro plus support, integration with Microsoft Excel and can be purchased with an indemnity contract for an additional fee.
JuliaDB: JuliaDB is a high performance database for in-memory and distributed computing. It is a coherent environment for analytics, all in Julia, for storing and computing on large distributed datasets. An Intro to JuliaDB video tutorial is available online.
Dhaka Tribune: “Alan Edelman to Train Bangladeshi AI Developers”
YourStory: “Julia Computing has developed a unique and high performing programming language with rich applications in AI and Machine Learning.”
Application Development Trends: “As a data scientist who has been using the language for 5 years now, Julia is by far the best programming language for analyzing and processing data.”
Datanami: “Jupyter is the successor to the iPython notebook, and as such is closely aligned with Python, but it also supports R, Scala, and Julia.”
efinancialcareers: “While Julia is not yet among the most in-demand programming languages on Wall Street, its growth rate is impressive and hedge funds are among the early-adopters.”
Chicago: Intro to Julia Tutorial with Julia Computing and Illinois Institute of Technology Association for Women in Mathematics at the Illinois Institute of Technology Mar 6
Chicago: Intro to Julia Tutorial with Julia Computing and Harold Washington College STEM Club Mar 8
Montreal: Plots.jl and Intro to Package Development Mar 8
San Jose: Cataloging the Visible Universe through Bayesian Inference at Petascale in Julia at Strata Data Conference Mar 9
Chicago: Intro to Julia Tutorial with Julia Computing and University of Chicago Association for Computing Machinery Council on Women in Computing at the University of Chicago Mar 9
Cleveland: Let’s Challenge Numerai Competition Together Mar 10
Washington DC: ARPA-E Energy Innovation Summit with Julia Computing Mar 13-15
Washington DC: Machine Learning and Programming Languages with Julia Computing Mar 14
Exeter: Go, Julia and Expanding Your Toolbox Mar 14
Warsaw: Spotkanie na Konferencji Supercomputing Frontiers Europe 2018 Mar 15
London: Introduction to Julia Mar 20
San Francisco: Introduction to Julia for Data Analytics with Julia Computing at University of San Francisco School of Management Mar 23
San Jose: NVIDIA GPU Technology Conference Mar 26-29
Los Angeles: PyData SoCal Meetup Mar 29
Tucson: HPC User Forum Apr 16-18
Mexico City: Intro to Julia for Engineers with Julia Computing at Universidad Panamericana Apr 23-27
Hong Kong: SIAM Applied Linear Algebra Conference May 4-8
Oaxaca: Workshop in Statistical Methods on Distributed Computing May 20-25
Freiburg: IEEE Statistical Signal Processing Workshop Jun 10-13
Bordeaux: JuMP-dev Workshop at Institut de Mathématiques de Bordeaux,
University of Bordeaux Jun 27-29
London: JuliaCon 2018 Aug 7-11
Palo Alto, CA: Intro to Julia Tutorial with Julia Computing, Stanford Society of Women Engineers and Stanford Women in Computer Science at Stanford University Feb 5
Global (YouTube): Intro to Solving Differential Equations in Julia with Chris Rackauckas and Julia Computing Feb 6
Berkeley, CA: Intro to Julia with Julia Computing and FEMTech Berkeley at University of California - Berkeley Feb 6
Irvine, CA: SoCal Julia Meetup Feb 8
Bangalore, India: Code the Data Science Web App Using Julia Feb 10
Cambridge, MA: Intro to Julia Tutorial with Julia Computing and Harvard Society of Black Scientists and Engineers at Harvard University Feb 12
Waltham, MA: Intro to Julia Tutorial with Julia Computing at Brandeis University Feb 13
Phoenix, AZ: ARPA-E Energy-Smart Farm Workshop with Julia Computing Feb 13-14
Boston, MA: Intro to Julia Tutorial with Julia Computing and Boston University’s Women in Astronomy Lunch Association at Boston University Feb 14
Global (YouTube): Intro to Julia Tutorial with Julia Computing Feb 15
Boston, MA: Intro to Julia Tutorial with Julia Computing and Simmons College Math and Computer Science Liaison at Simmons College Feb 16
Northampton, MA: Intro to Julia Tutorial with Julia Computing and Smithies in Computer Science at Smith College Feb 17
London Meetup, UK: Bouncy Particle Sampler and Visual Studio Code Feb 19
Boston, MA: Intro to Julia Tutorial with Julia Computing and Northeastern University Graduate Women in Science and Engineering at Northeastern University Feb 19
Lorient, France: ROADEF 2018 Julia, JuMP for Operations Research Feb 21-23
Warsaw: Obliczenia Równolege w Julia Feb 27
Berlin: Nonsmooth Optimization Using Proximal Algorithms in Julia Feb 27
Global (YouTube): Intro to JuliaDB with Julia Computing Feb 28
Columbus, OH: Intro to Julia Tutorial with Julia Computing and the Ohio State University Association of Computing Machinery Committee on Women at Ohio State University Feb 28
Granville, OH: The Two Language Problem: Why it Matters for Data Scientists and How Julia Solves It with Julia Computing and Data Analytics at Denison University at Denison University Mar 1
Granville, OH: Intro to Julia Tutorial with Julia Computing and Data Analytics at Denison University at Denison University Mar 2
West Lafayette, IN: Intro to Julia Tutorial with Julia Computing and Women in Data Science at Purdue Mar 5
There are 26 Julia Meetup groups worldwide with more than 5 thousand members. If there’s a Julia Meetup group in your area, we hope you will consider joining, participating and helping to organize events. If there isn’t, we hope you will consider starting one.
Do you work at or know of an institution 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 more than 200 Julia jobs currently listed on Indeed.com, including jobs at Google, Facebook, IBM, KPMG, Ernst & Young, Booz Allen Hamilton, Comcast, Zulily, National Renewable Energy Research Laboratory, Los Alamos National Laboratory, Brown, Princeton, Columbia, Notre Dame, MIT, University of Chicago and many more.
Invenia Labs is hiring Julia developers for their Cambridge, UK and Winnipeg, Canada offices.
Penn State University’s Department of Astronomy and Astrophysics Center for Exoplanets and Habitable Worlds (CEHW) is looking to hire a Postdoc Researcher and Assistant Research Professor with Julia experience.
Please contact us if you wish to:
Julia is the fastest high performance open source computing language for data, analytics, algorithmic trading, machine learning, artificial intelligence, and many other domains. 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. For example, Julia has run at petascale on 650,000 cores with 1.3 million threads to analyze over 56 terabytes of data using Cori, the world’s sixth-largest supercomputer. With more than 1.8 million downloads and +101% annual growth, Julia is one of the top programming languages developed on GitHub. Julia adoption is growing rapidly in finance, insurance, machine learning, energy, robotics, genomics, aerospace, medicine and many other fields.
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. Julia Computing offers the following products:
To learn more about how Julia users deploy these products to solve problems using Julia, please visit the Case Studies section on the Julia Computing Website.
Julia users, partners and employers hiring Julia programmers in 2018 include Amazon, Apple, BlackRock, Booz Allen Hamilton, Capital One, Comcast, Disney, Ernst & Young, Facebook, Ford, Google, IBM, Intel, KPMG, Microsoft, NASA, Oracle, PwC, Uber, and many more.
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