From 014e38aa4949a739844dad9d262da8bbd80e292f Mon Sep 17 00:00:00 2001 From: Matt McKay Date: Fri, 31 Jul 2026 11:23:37 +1000 Subject: [PATCH 1/4] news: add post for SciPy 2026 tutorial Smit Lunagariya delivered "Computational Methods for Simulation using JAX and NumPy" at SciPy 2026 (University of Minnesota, Minneapolis) on July 14, 2026. Materials are in QuantEcon/scipy_tutorial_2026. Co-Authored-By: Claude Opus 5 (1M context) --- _posts/2026-07-14-scipy-2026-tutorial.md | 22 ++++++++++++++++++++++ 1 file changed, 22 insertions(+) create mode 100644 _posts/2026-07-14-scipy-2026-tutorial.md 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..42a1431 --- /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] +--- + +QuantEcon's [Smit Lunagariya](https://smit-create.github.io/intro.html) 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. From dc6f717ec147e92c75d3bc51f5d14e6b314ea52b Mon Sep 17 00:00:00 2001 From: Matt McKay Date: Mon, 10 Aug 2026 14:31:41 +1000 Subject: [PATCH 2/4] news: label Smit as a Google Engineer in SciPy 2026 post Co-Authored-By: Claude Opus 5 (1M context) --- _posts/2026-07-14-scipy-2026-tutorial.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2026-07-14-scipy-2026-tutorial.md b/_posts/2026-07-14-scipy-2026-tutorial.md index 42a1431..e7280d7 100644 --- a/_posts/2026-07-14-scipy-2026-tutorial.md +++ b/_posts/2026-07-14-scipy-2026-tutorial.md @@ -6,7 +6,7 @@ excerpt: "QuantEcon delivered a four-hour tutorial on accelerating simulations w tag: [workshop] --- -QuantEcon's [Smit Lunagariya](https://smit-create.github.io/intro.html) 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. +Google Engineer [Smit Lunagariya](https://smit-create.github.io/intro.html), a QuantEcon lead developer, 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: From 3e48d1170446762b569d229d588e1fb6b3ab719a Mon Sep 17 00:00:00 2001 From: Matt McKay Date: Mon, 10 Aug 2026 14:32:52 +1000 Subject: [PATCH 3/4] news: describe Smit as a QuantEcon Ambassador Co-Authored-By: Claude Opus 5 (1M context) --- _posts/2026-07-14-scipy-2026-tutorial.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2026-07-14-scipy-2026-tutorial.md b/_posts/2026-07-14-scipy-2026-tutorial.md index e7280d7..5902667 100644 --- a/_posts/2026-07-14-scipy-2026-tutorial.md +++ b/_posts/2026-07-14-scipy-2026-tutorial.md @@ -6,7 +6,7 @@ excerpt: "QuantEcon delivered a four-hour tutorial on accelerating simulations w tag: [workshop] --- -Google Engineer [Smit Lunagariya](https://smit-create.github.io/intro.html), a QuantEcon lead developer, 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. +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: From cad4ebd02a46e23df60a98c289ac54b28b9ceec8 Mon Sep 17 00:00:00 2001 From: Matt McKay Date: Mon, 10 Aug 2026 14:36:12 +1000 Subject: [PATCH 4/4] team: add QuantEcon Ambassadors section and list Smit there Smit Lunagariya's profile now describes him as a QuantEcon Ambassador working as an engineer at Google, matching the SciPy 2026 news post. His role moves to a new "QuantEcon Ambassadors" section on the team page; the Lead Developer badge is retained. Co-Authored-By: Claude Opus 5 (1M context) --- _layouts/team.html | 17 +++++++++++++++++ _team-members/smit.md | 4 ++-- 2 files changed, 19 insertions(+), 2 deletions(-) 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/_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