added new page

nipunbatra · nipunbatra · commit ff636985e25b · 2024-06-05T14:18:30.000+05:30
diff --git a/.DS_Store b/.DS_Store
diff --git a/_quarto.yml b/_quarto.yml
@@ -8,18 +8,14 @@ website:
     right:
       - href: index.qmd
         text: Home
-      - href: papers
+      - href: https://sustainability-lab.github.io/papers/
         text: Publications
       - href: teaching.qmd
         text: Teaching
-      - href: https://nipunbatra.github.io/lab/
+      - href: https://sustainability-lab.github.io
         text: Lab (+Handbook)
       - href: blog
         text: Blog
-      - href: news.qmd
-        text: News
-      - href: media.qmd
-        text: Media
       - href: files/cv.pdf
         text: CV
 
diff --git a/index.qmd b/index.qmd
@@ -23,9 +23,9 @@ about:
       href: https://scholar.google.co.in/citations?user=rFGzHlIAAAAJ&hl=en   
 ---
 
-Nipun Batra is an Assistant Professor in Computer Science at IIT Gandhinagar. He previously completed his postdoc from University of Virginia. He completed his PhD. from IIIT Delhi where he was a TCS PhD fellow. His group broadly works on machine learning/AI/sensors/IoT for computational sustainability problems like smart buildings and air quality.
+Nipun Batra is an Assistant Professor in Computer Science at IIT Gandhinagar. He previously completed his postdoc from University of Virginia. He completed his PhD. from IIIT Delhi where he was a TCS PhD fellow. His group called the Sustainability Lab broadly works on machine learning and sensing for computational sustainability problems like smart buildings, air quality and wearable healthcare.
+
+His work has been awarded several awards, including, young alumni award from IIIT Delhi, the best PhD presentation at ACM Sensys, best demo at ACM Buildsys, and a best video nominee at ACM KDD. 
 
-His work has been awarded several awards, including, the best PhD presentation at ACM Sensys, best demo at ACM Buildsys, and a best video nominee at ACM KDD. 
 
-He is working with his team towards a Jupyter book on [code first understanding machine learning](https://code-first-ml.github.io).
 
