Dyad 3.0 Launch Event: Join us on Tuesday, May 19 12:00 PM EDT for the live product reveal and celebrate the official launch of Dyad 3.0. The product launch will be a deep dive into what’s coming next, alongside customer and partner testimonials, including Dr. Prith Banerjee of Synopsys, Nathan VanRheenen of AE Ventures, Dr. Christopher Laughman of Mitsubishi Electronic Research Laboratories, Tom Ray of Binnies, and Dr. Clément Coïc of Siemens Healthineers. Register here.
JuliaHub Raises $65M Series B and Launches Dyad 3.0: JuliaHub is thrilled to announce a $65M Series B funding round, led by Dorilton Ventures, with participation from General Catalyst, AE Ventures, and technology investor and former Snowflake CEO Bob Muglia. The company also introduced Dyad 3.0, its latest platform, bringing agentic AI into engineering workflows. Find out more about the announcement. Also read: AI startup JuliaHub raises $65M to rival Simulink.
cuTile.jl for High-Performance Computing in Julia: NVIDIA's new CUDA Tile programming model brings a high-level, portable abstraction for writing high-performance GPU kernels. Join Dr. Andy Terrel(NVIDIA) and Dr. Tim Besard(JuliaHub) in this webinar that introduces the CUDA Tile, and how it's been ported to Julia as cuTile.jl. The session will explore tile-based GPU programming through real-world examples spanning linear algebra routines, AI inference kernels, and HPC algorithms. Register here.
Automating GPU Kernel Translation with AI Agents: cuTile Python to cuTile.jl: A new technical post explores how AI agents can translate GPU kernels from cuTile Python to cuTile.jl, reducing manual effort and avoiding common errors. It introduces a reusable “agent skill” that encodes translation rules, validation, and testing into a single workflow, enabling fast, reliable kernel conversion for Julia-based GPU computing. Read the full blog post.
cuTile.jl 0.3: CUDA.jl Integration and Improved Performance: The latest release of cuTile.jl introduces seamless integration with CUDA.jl, enabling easier kernel launches using the familiar @cuda interface. This version also delivers significant performance gains, often exceeding cuTile Python across benchmarks, along with reduced latency, array slicing support, and built-in random number generation. Read the full update.
Webinar Series with Dr. Michael Tiller: In this three-part webinar series, Dr. Michael Tiller explores modeling and simulation in Dyad. Starting with the fundamentals of acausal modeling, the series walks through building simple system models and comparing them with traditional approaches. It then progresses to composing hierarchical system models and understanding DAEs, along with techniques to solve them efficiently using symbolic methods. The series concludes with a live demonstration of the Dyad agent, showcasing how it supports engineering workflows, from model creation to analysis, while simplifying and accelerating the overall development process. Register here.
Numerical Methods in Quantum Information Science Summer School 2026: Registration is now open for this graduate-level program, taking place June 22–26 at the University of Massachusetts Amherst. The curriculum covers everything from setting up programming environments to advanced topics like quantum error correction, tensor networks, and quantum system simulation. Supported by the Center for Quantum Networks and National Science Foundation, the program is offered at a subsidized fee, including on-campus housing. Learn more and register.
Scientific Machine Learning-Assisted Model Discovery: A new paper by researchers introduces Dyad Model Discovery, a semi-automated approach that augments physics-based models with data-driven symbolic expressions. Demonstrated on a refrigeration system digital twin, the method improves model accuracy through an engineer-in-the-loop workflow. The improved physical models pave the way to future designs with better thermal efficiency. Read more.
Free Online Julia Webinars from JuliaHub: JuliaHub provides free one-hour Webinars led by JuliaHub staff and other experts. Space is limited and registration is required, so please sign up today!
Dyad 3.0 Launch: Livestream with Dr. Viral B Shah, Dr. Chris Rackuackas, Dr. Michael Tiller and others, Tuesday May 19, 12 PM Eastern(US)
cuTile.jl for High-Performance Computing in Julia with Dr. Andy Terrel (NVIDIA) and Dr. Tim Besard (JuliaHub), Tuesday May 12, 1-2 PM Eastern(US)
Introduction to Symbolic Manipulation with Dyad with Dr. Michael Tiller, Wednesday May 13, 12 PM Eastern (US)
Introduction to Agent Assisted Engineering Workflows with Dr. Michael Tiller, Wednesday May 20, 12 PM Eastern(US)
Easy Pharmacometric Modeling using Pumas on JuliaHub with Phil Vernes, Thursday May 21, 1-2 PM Eastern(US)
Recent JuliaHub Webinars: JuliaHub provides free one-hour Webinars on topics of interest to Julia users. Nearly 100 past Webinars are available online. Click here to watch.
This Month in Julia World: This Month in Julia World is a newsletter from Stefan Krastanov with up-to-date information about Julia events, new releases and more. Read it here.
Nouvelles Julia - Julia News en Français: Nouvelles Julia is a newsletter in French with the latest Julia news. Read it here.
JuliaCon 2026: JuliaCon 2026 will take place August 10-15 in Mainz, at the Johannes Gutenberg University
New Blog Posts from SciML: SciML has published several new blog posts. You can read them here.
Blog Posts from Dr. Chris Rackauckas and Great Lakes Consulting: Read blog posts by JuliaHub VP of Modeling and Simulation Dr. Chris Rackauckas and Great Lakes Consulting Senior Julia Developer Steven Whitaker.
Julia Dispatch Podcast: Julia Dispatch is a Julia podcast from Dr. Chris Rackauckas (JuliaHub VP of Modeling and Simulation) and Dr. Michael Tiemann. Watch it here.
JuliaHub Digital Twin Solutions and Consulting: We help enterprises build deployable and scalable solutions leveraging SciML to create highly accurate and trustworthy Digital Twins. Applications span asset health monitoring, optimization and predictive maintenance, process optimization, model-based control, design optimization, and internal or external simulation tools. We also offer consulting and technical support. Schedule a consultation with our solutions team to discuss your use case.
Careers at JuliaHub: JuliaHub is a fast-growing tech company with fully remote employees in 20 countries on 6 continents. Click here to learn more about exciting careers and internships with JuliaHub.
Julia Expertise Needed at University of Glasgow: Dr. Eric Silverman, Research Fellow at the University of Glasgow, seeks a Research Associate for a 5-year research project on computational modeling for public health using an agent-based modeling framework developed in Julia. Julia experience and a PhD are required for this position. Click here for more information and to apply.
Julia and JuliaHub in the News
JuliaHub’s funding announcement was shared by prominent news organizations, startup newsletters, and technology and AI publications. Some prominent mentions include Axios.com, PRNewswire, SiliconAngle, Yahoo!Finance, FINSMES, HPCWire, Engineering.com, AviationPros, Daily CADCAM, CIMdata, and EngTechnica.
Julia Blog Posts
One Model: Two Analyses (Dr. Ranjan Anantharaman)
cuTile.jl 0.3: CUDA.jl Integration, and Even Better Performance & Latency (Tim Besard)
Research Project: Exploring Julia for High-Performance Computing (Yajie Zhang)
Julia, Custom Serialization With JSON.jl (Picaud Vincent)
This Month in Julia World (April 2026) (Stefan Krastanov)
Nouvelles Julia (March 2026) (Pierre Navaro)
Upcoming Julia and JuliaHub Events
Livestream: Dyad 3.0 Launch with Dr. Viral B Shah, Dr. Chris Rackauckas, Dr. Michael Tiller and others, Tuesday May 19, 1-2 PM Eastern(US)
Online: cuTile.jl for High-Performance Computing in Julia with Dr. Andy Terrel(NVIDIA) and Dr. Tim Besard(JuliaHub), Tuesday May 12, 1-2 PM Eastern(US)
Online: Introduction to Symbolic Manipulation with Dyad with Dr. Michael Tiller, Wednesday May 13, 1-2 PM Eastern(US)
Online: Introduction to Agent Assisted Engineering Workflows with Dr. Michael Tiller, Wednesday May 20, 1-2 PM Eastern (US)
Online: Easy Pharmacometric Modeling using Pumas on JuliaHub with Phil Vernes, Thursday May 21, 1-2 PM Eastern(US)
Udine, Italy: VI Grade 2026 Smart Prototypes Summit at VI grade’s Simcenter in Udine hosted by HBK from May 19-22
Dubrovnik, Croatia: Population Approach Group Europe, with JuliaHub June 2-5
Neckarsulm, Germany: AI & Data-Driven Simulation Forum 2026 with JuliaHub
Johannes Gutenberg University Mainz (Germany, near Frankfurt): JuliaCon 2026 with JuliHub, August 10-15
Contact Us: Please contact us if you want to:
Obtain pricing for Dyad and Julia consulting projects for your organization
Schedule Dyad or Julia training
Share information about exciting new Julia case studies or use cases
Partner with JuliaHub to organize a Julia event online or offline
About JuliaHub, Julia and Dyad
Dyad combines physics-based modeling with scientific machine learning(SciML) for mission-critical engineering. Dyad is fully agentic in its design, making it possible for engineers to carry out complex workflows through natural language interaction. Dyad integrates code, diagrams and agentic workflows in a seamless tool driving 10x productivity. Leveraging the Julia and the SciML ecosystem under the hood, Dyad also benefits from significantly higher performance compared to the competition, often being 100x faster at simulating complex physics. Teams leverage Dyad to build smarter, faster, and more reliable systems without compromising the rigor of traditional engineering, supporting use cases from predictive maintenance to real-time performance tuning and over-the-air updates. The Dyad tool powered by Julia and SciML is free to use. Get started here.
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.
