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Newsletter March 2023 - JuliaCon Updates!

Andrew Claster
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JuliaCon 2023: Early Bird pricing is still available for JuliaCon 2023! Click here to take advantage of discounted Early Bird pricing. JuliaCon will be held in person for the first time since 2019, and will be held at MIT for the first time since 2016. JuliaCon will take place July 25-29. JuMP-dev and SciMLCon will both take place during JuliaCon this year.

  1. Keynote Speakers:  Dr. Christopher Rackauckas, Dr. Stephen Wolfram, Dr. Rumman Chowdhury, Dr. Tim Davis
  2. Sponsorship: Sponsorship is available at many levels, from $1,000 for an exhibition table to $45,000 for Diamond sponsorship. Recent sponsors include: JuliaHub, RelationalAI, Julius Technologies, Intel, AWS, Invenia Labs, Google, EVN, DataChef, Gordon and Betty Moore Foundation, Tangent Works, Replit, Capital One, Nvidia, Microsoft, Alan Turing Institute, Zapata, Beacon Biosignals, Metalenz, ASML, G-Research, Conning, Pumas-AI, QuEra Computing, Jeffrey Sarnoff and more.
  3. Julia Community Prize: Is there someone who you would like to see recognized for their contributions to the Julia language and/or community? Nominations are open now. Please note that past winners are not eligible.

Free Webinars and Demos from JuliaHub: Please register today to participate in a free Webinar or demo from JuliaHub.

  1. Tools for Non-Linear Model Predictive Control (MPC) - Wednesday March 29, 12:30-1:30 pm Eastern (US): Click here to register for this free Webinar with JuliaHub Sales Engineer Dr. Ranjan Anantharaman. Participants will learn how to develop a lane-changing controller in this real-time demo using JuliaSim Control. In non-linear MPC you have the advantage of incorporating a plant model with non-linear dynamics; a non-quadratic cost function with high interpretability; and non-linear constraints. Using a realistic case study of controlling a self-driving car, participants will learn to build simple dynamical models using Julia, specify reference trajectories and other constraints to be satisfied by the controller and analyze the final synthesized controller to understand its performance.
  2. Modern Industrial Modeling Made Easy - Wednesday April 5, 10:30-11:30 am Eastern (US): Click here to register for this free Webinar to learn how to modernize your industrial modeling workflow. Topics include: JuliaSim package suite, JuliaHub job outputs for monitoring and results, integrating JuliaHub DataSets to capture and version simulation runs, JuliaHub Pluto notebooks for sharing analysis and JuliaHub private registries for sharing packages.
  3. Robust MPC for Uncertain Parameters - Wednesday, April, 19 - 10:30 am Eastern (US) - Register to see a demo of controlling a simple linear system consisting of a single integrator. We will implement two versions of the controller, the first one will use the nominal plant model only and the second controller will use a model with explicit parameter uncertainty.
  4. Cutting Model Translation Time with Pumas-QSP Importers - Tuesday April 25, 1-2 pm Eastern (US): Click here to register for this free Webinar which answers the question: ‘How do you use performance research without having to go through the painstaking model development steps again?’ As part of this Webinar, we will: a) specify a full optimization problem with the PEtab format; b) import SBML and BioNetGen models together with CSV data; c) visualize your virtual population; d) generate a report of the optimization results.
  5. Building Data Visualization Apps with Dash and Julia - Wednesday, April 26, 1-2 pm Eastern (US): Register to see how you can turn your Julia data outputs into beautiful visualizations with Dash.jl. JuliaHub Product Manager Deep Datta will demonstrate how you can build, deploy, manage, and share interactive dashboards with Dash for Julia. Through a couple of simple patterns, you can abstract away all of the technologies and protocols that are required to build a full-stack web app with interactive data visualization. It is simple enough that you can bind a user interface to your code in less than 10 minutes.

Meta Chief AI Scientist Yann LeCun Says Machine Learning Would Have Advanced Faster If Julia Were Available and Widely Adopted Instead of Python: In one of his most-viewed tweets ever (1.7 million views), Meta Chief AI Scientist Yann LeCunn says that machine learning would have advanced faster if Julia had been available and widely adopted instead of Python.

JuliaHub Modeling Platform Newsletter March 2023 - Meta Yann LeCun

New Blog Posts from JuliaHub: JuliaHub has launched a new blog format and it features two new blog posts:

  1. Why is Pumas-QSP So Fast?: JuliaHub Software Engineer Dr. Paul Lang explains in this blog post what makes Pumas-QSP so fast.
  2. JuliaHub Talks Scientific Machine Learning and GPU Acceleration at the ASML Lounge in the Philips Stadium of Eindhoven: JuliaHub VP of Modeling and Simulation Dr. Chris Rackauckas, MIT JuliaLab researcher Valentin Churavy and ASML’s Matthijs Cox shared the latest advancements in Julia, scientific machine learning (SciML) and GPU acceleration. More information is available here.

Curious about AI? Learn to solve real-world problems at an AI meetup in Eindhoven. Join JuliaHub and learn Julia in the region of Eindhoven

JuliaHub Returns to Eindhoven - Hosted by Sioux Technologies: Deepak Vinchhi (JuliaHub COO and co-founder) and Dr. Christopher Rackauckas (JuliaHub VP of Modeling and Simulation) will present Julia’s Disruption of the High-Tech Industry at Sioux Technologies’ Hot-or-Not on Tuesday April 18. Click here to register.

Introduction to Control Analysis and Design in Julia: Fredrik Bagge Carlson, JuliaHub Control Systems Team Lead, has created a series of 10 videos that together provide an introduction to control analysis and design in Julia. Click here to watch them all.

MakieCon 2023: MakieCon takes place April 18-20 at the Max Planck Institute for Biogeochemistry in Jena, Germany. Makie.jl is a data visualization ecosystem for Julia with high performance and extensibility. Organizers include Dr. Lazaro Alonso Silva, Simon Danisch and Julius Krumbiegel.

Julia for Saving Babies’ Lives: Neonatal EEG Graded for Severity of Background Abnormalities in Hypoxic-Ischaemic Encephalopathy is a new paper published in Nature - Scientific Data. Physician researchers from the Department of Paediatrics and Child Health joined researchers from the Department of Electronic and Electrical Engineering at the INFANT Research Centre at University College Cork, Ireland using machine learning in Julia to improve detection and evaluation of seizures which can cause death and disability in newborns.

Julia for Reducing COVID Transmission: How to Avoid a Local Epidemic Becoming a Global Pandemic is a new article in the Proceedings of the National Academy of Sciences. The authors use Julia for cosimulation and propose development of a digital twin model for further research.

Julia Used by Wells Fargo for Quantum Computing Simulator: How Does A Quantum Computer Simulator Work? is a new article from Rebellion Research by Constantin Gonciulea, Wells Fargo CTO of Advanced Technology featuring software engineers Saveliy Yusufov and Charlee Stefanski. They built a high-performance, fast and flexible quantum state simulator, the simple version of which has been ported to Python, Julia and Go. The original paper, Designing a Fast and Flexible Quantum State Simulator, is available here.

Julia for Imaging Black Holes: Dr. Paul Tiede (Center for Astrophysics, Harvard and Smithsonian) presented Accelerating Black Hole Imaging with Enzyme[.jl]. Julia accelerated the Event Horizon Telescope (EHT) team's imaging pipeline for supermassive black holes from days/weeks on a cluster to just one hour on a single CPU laptop.

JuliaHub Newsletter - March 2023 - Julia for Imaging Black Holes: Dr. Paul Tiede (Center for Astrophysics, Harvard and Smithsonian)

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? JuliaHub 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 JuliaHub and our partners to get your team up and running quickly. For more information, please contact us.

Careers at JuliaHub: JuliaHub is a fast-growing tech company with fully remote employees in 12 countries on 5 continents. Click here to learn more about exciting careers and internships with JuliaHub.

Julia and JuliaHub in the News

  • InfoWorld: Meet Zig: The Modern Alternative to C
  • Nature - Scientific Data:  Neonatal EEG Graded for Severity of Background Abnormalities in Hypoxic-Ischaemic Encephalopathy
  • Tekedia: Up-And-Coming Programming Languages That Will Be All Over the Place
  • Rebellion Research: How Does A Quantum Computer Simulator Work?
  • arXiv: Designing a Fast and Flexible Quantum State Simulator
  • TechBullion: Best 10 Programming Languages in 2023 for AI Development
  • Computerwoche: Zig Language - Die Moderne C-Alternative?
  • Film Daily: Best IDEs For R Programming 2023
  • Analytics Insight: How to Land a Data Science Internship? The Ultimate Guide
  • KDnuggets: 3 Julia Packages for Data Visualization
  • TechNative: The Data Science Triangle: A Model to Develop Great Data Teams
  • MakeUseOf: The Ultimate Guide to Landing a Data Science Internship
  • MakeUseOf: 6 Unusual & Groundbreaking Programming Languages to Learn in 2023
  • EENews Europe: PCIe Digitizer Cards Reach 10Gsample/s
  • Analytics Insight: Top 10 AI Software Products You Should be Aware of in 2023
  • RTInsights: The Ultimate Tripod of Data Scientists
  • Times Higher Education: Three Creative Ways to Use ChatGPT in Class
  • DevClass: Polyglot Notebooks Fully Released for VS Code, with Support for Multiple Languages – Not Including Python
  • Proceedings of the National Academy of Sciences: How to Avoid a Local Epidemic Becoming a Global Pandemic

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About JuliaHub and Julia

JuliaHub is a fast and easy-to-use code-to-cloud platform that accelerates the development and deployment of Julia programs. JuliaHub users include some of the most innovative companies in a range of industries including pharmaceuticals, automotive, energy, manufacturing, and semiconductor design and manufacture.

Julia is a high performance open source programming language that powers computationally demanding applications in modeling and simulation, drug development, design of multi-physical systems, electronic design automation, big data analytics, scientific machine learning and artificial intelligence. 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 prestigious James H. Wilkinson Prize for Numerical Software and the Sidney Fernbach Award.

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