diff --git a/_layouts/team.html b/_layouts/team.html index 4310e3b..c59dc8e 100644 --- a/_layouts/team.html +++ b/_layouts/team.html @@ -79,6 +79,23 @@

{{ team-member.name }} + {% for team-member in team-members %} +
+
+
+
+

{{ team-member.name }}{% if team-member.tag %} {{ team-member.tag }}{% endif %}

+

{{ team-member.content }}

+
+
+
+ {% endfor %} + +

Design and Marketing

{% assign team-members = site.team-members | where: 'role', 'Design and Marketing' | sort: 'last_name' %} diff --git a/_posts/2026-07-14-scipy-2026-tutorial.md b/_posts/2026-07-14-scipy-2026-tutorial.md new file mode 100644 index 0000000..5902667 --- /dev/null +++ b/_posts/2026-07-14-scipy-2026-tutorial.md @@ -0,0 +1,22 @@ +--- +layout: post +title: "Tutorial: Computational Methods for Simulation at SciPy 2026" +author: Matt McKay +excerpt: "QuantEcon delivered a four-hour tutorial on accelerating simulations with NumPy and JAX at SciPy 2026 in Minneapolis." +tag: [workshop] +--- + +Google Engineer [Smit Lunagariya](https://smit-create.github.io/intro.html), a QuantEcon Ambassador, delivered a four-hour tutorial on **Computational Methods for Simulation using JAX and NumPy** at [SciPy 2026](https://www.scipy2026.scipy.org/), held at the University of Minnesota in Minneapolis, on July 14, 2026. + +The tutorial uses Thomas Schelling's segregation model as its running example — a classic demonstration of how mild individual preferences can lead to extreme aggregate outcomes — and works through how to turn readable but slow Python code into a high-performance simulation: + +1. **The basic model** — the dynamics of segregation implemented with Python classes +2. **NumPy implementation** — rewriting the model with arrays and functions for clarity and speed +3. **JAX implementation** — translating the model to JAX syntax and concepts +4. **Further parallelization** — exploiting modern parallel hardware such as GPUs + +The techniques carry over to other settings that rely on large-scale simulation, including urban planning and epidemiology. + +The materials were prepared by [John Stachurski](https://johnstachurski.net/), [Thomas J. Sargent](http://www.tomsargent.com/), [Smit Lunagariya](https://smit-create.github.io/intro.html), and [Matt McKay](https://github.com/mmcky). + +All tutorial materials are freely available [online](https://quantecon.github.io/scipy_tutorial_2026/) and on [GitHub](https://github.com/QuantEcon/scipy_tutorial_2026), including notebooks that can be run on Google Colab with no local setup. diff --git a/_team-members/smit.md b/_team-members/smit.md index 986b69c..081558f 100644 --- a/_team-members/smit.md +++ b/_team-members/smit.md @@ -3,7 +3,7 @@ name: Smit Lunagariya last_name: Lunagariya image: https://avatars.githubusercontent.com/u/55887635?v=4 link: https://github.com/Smit-create -role: "Research Assistant" +role: "QuantEcon Ambassador" tag: "Lead Developer" --- -Smit Lunagariya is a QuantEcon lead developer and now works at Google. Smit's interests lie in High-performance computing, compilers, and open source scientific computing. \ No newline at end of file +Smit Lunagariya is a QuantEcon Ambassador and works as an engineer at Google. Smit's interests lie in High-performance computing, compilers, and open source scientific computing. \ No newline at end of file