diff --git a/_pages/about.md b/_pages/about.md
index daf0156e3d1b1..e7994fad1ffc2 100644
--- a/_pages/about.md
+++ b/_pages/about.md
@@ -8,8 +8,7 @@ profile:
   align: right
   image: pair-logo-sq-2.png
   image_circular: false # crops the image to make it circular
-  more_info: > #<p>Georgia Tech</p>
-
+  more_info: # <p>Georgia Tech</p>
 selected_papers: false # includes a list of papers marked as "selected={true}"
 social: true # includes social icons at the bottom of the page
 
diff --git a/_pages/contact.md b/_pages/contact.md
index 71b4838a4f982..4d49dad68ae40 100644
--- a/_pages/contact.md
+++ b/_pages/contact.md
@@ -24,10 +24,11 @@ Please follow instructions in course material to contact staff.
 
 {% details **Mailing Address** %}
 
+<!-- prettier-ignore -->
 **Prof. Animesh Garg**
 : CODA 11th Floor, Office S1145  
- 756 West Peachtree Street  
- Atlanta, GA 30308
+  756 West Peachtree Street  
+  Atlanta, GA 30308
 
 {% enddetails %}
 
diff --git a/_posts/2021-09-22-remote-sim2real-trifinger.markdown b/_posts/2021-09-22-remote-sim2real-trifinger.markdown
index 564a05f4d0661..d1438a6ceb052 100644
--- a/_posts/2021-09-22-remote-sim2real-trifinger.markdown
+++ b/_posts/2021-09-22-remote-sim2real-trifinger.markdown
@@ -98,6 +98,7 @@ We performed experiments to see how the use of keypoints impacted the speed and
 
 #### 2. The trained policies can be deployed straight from the simulator to remote real robots
 
+<!-- prettier-ignore -->
 | Dropping and Regrasping  |         Recovering from failure          |
 | :----------------------: | :--------------------------------------: | --------------------- | ------------------------------------ | -------------------- | ---------------------------------------- | --------------------- | ------------------------------------ |
 | ![]({{ 'drop_repose.gif' | prepend: '/assets/img/blog/s2r2-sept21/' | prepend: site.baseurl | prepend: site.url }}){: width="95%"} | ![]({{ 'recover.gif' | prepend: '/assets/img/blog/s2r2-sept21/' | prepend: site.baseurl | prepend: site.url }}){: width="95%"} |
@@ -114,12 +115,14 @@ Our policy is also robust towards dropping - it is able to recover from a cube f
 
 We found that our policy was fairly robust to variations in environment parameters in simulation. For example, it gracefully handles scaling up and down of the cube by ranges far exceeding randomization:
 
+<!-- prettier-ignore -->
 |    Scaled up cube     |             Scaled down cube             |
 | :-------------------: | :--------------------------------------: | --------------------- | ------------------------------------ | ----------------------- | ---------------------------------------- | --------------------- | ------------------------------------ |
 | ![]({{ 'big_cube.gif' | prepend: '/assets/img/blog/s2r2-sept21/' | prepend: site.baseurl | prepend: site.url }}){: width="95%"} | ![]({{ 'small_cube.gif' | prepend: '/assets/img/blog/s2r2-sept21/' | prepend: site.baseurl | prepend: site.url }}){: width="95%"} |
 
 Surprisingly, we found that our policies were able to generalise 0-shot to other objects, for example a cuboid or a sphere:
 
+<!-- prettier-ignore -->
 |       Cuboid        |                  Sphere                  |
 | :-----------------: | :--------------------------------------: | --------------------- | ------------------------------------ | ------------------- | ---------------------------------------- | --------------------- | ------------------------------------ |
 | ![]({{ 'cuboid.gif' | prepend: '/assets/img/blog/s2r2-sept21/' | prepend: site.baseurl | prepend: site.url }}){: width="95%"} | ![]({{ 'sphere.gif' | prepend: '/assets/img/blog/s2r2-sept21/' | prepend: site.baseurl | prepend: site.url }}){: width="95%"} |