Update README.md

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@@ -24,8 +24,6 @@ <h2>Education</h2>
    <li> 2016 - 2021: Ph.D. 
    from the <a href = "https://iisc.ac.in/">Indian Institute of Science</a> with thesis titled <a href = "https://etd.iisc.ac.in/handle/2005/5560">Deep Learning over Hypergraphs</a> advised by 
 <a href = "https://talukdar.net/">Prof. Partha Talukdar</a>.
-<li> 2014 - 2016: M. Tech. from <a href = "https://www.iiitb.ac.in/">IIIT Bangalore</a> with thesis advised by 
-<a href = "https://sites.google.com/view/ashish-choudhury">Prof. Ashish Choudhury</a>.
 </ul>
 
 <br></br>
@@ -36,7 +34,15 @@ <h2>Research Focus</h2>
 </ul>
 
 <br></br>
-<h2>Selected Publications, Tutorial from <a href = "https://scholar.google.com/citations?user=-td7hOYAAAAJ&hl=en">Google Scholar</a></h2>
+<h2>Key Publications</h2>
+<!-- Project 1 -->
+<div class="NeurIPS 2019">
+  <h3>Graph Convolution on Hypergraphs</h3>
+  <img src="1.png" alt="Graph Convolution on Hypergraphs">
+  <p>This project aimed to extend traditional graph neural networks to hypergraph structures, which encompass higher-order relationships between nodes. Outcomes of this research include the development of a novel deep learning algorithm capable of handling complex hypergraph data, with applications in social network analysis and bioinformatics. The project led to a publication in a top-tier conference and was awarded the Best Paper at XYZ Conference.</p>
+</div>
+
+
 <ul>
    <li> <p><a href = "https://link.springer.com/chapter/10.1007%2F978-3-030-75762-5_36">Graph Neural Networks for Soft Semi-Supervised Learning on Hypergraphs</a> [<a href = "https://drive.google.com/file/d/1DNJXIqKdpWqrimLQU3yZxUtYUYBXh1Oe/view">code</a>]
    <br>Naganand Yadati, Tingran Gao, Shahab Asoodeh, Partha Talukdar, and Anand Louis