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