From acc47fb9be368aaba39bf1b5df419f47535d290b Mon Sep 17 00:00:00 2001
From: Nhan Tran <nhan.v.tran@gmail.com>
Date: Thu, 29 Jun 2023 23:35:46 -0500
Subject: [PATCH] add the CFP

---
 index.html      | 27 ++++++++++++++++++---------
 submission.html | 10 +++++-----
 2 files changed, 23 insertions(+), 14 deletions(-)

diff --git a/index.html b/index.html
index 7e8a19e..71932ac 100644
--- a/index.html
+++ b/index.html
@@ -36,7 +36,7 @@
              <h1>Fast Machine Learning for Science Workshop</h1>
              <hr>
              <h5>Co-located with 2023 <u><a href="https://iccad.com/" style="color: white">International Conference on Computer-Aided Design (ICCAD)</a></u> </h5>
-             <h4>Date: TBD</h4>
+             <h4>Date: November 2, 2023</h4>
              <p></p>
          </div>
      </div>
@@ -52,10 +52,17 @@ <h4>Date: TBD</h4>
             <h2 class="add-top-margin">Overview</h2>
             <hr>
             <p class="text text-justify">
-              At bibendum potenti ipsum eros, leo interdum mus. Fusce volutpat risus fermentum volutpat. Convallis justo cras curabitur fames. Sagittis accumsan rhoncus maecenas libero dapibus condimentum ut suscipit. Potenti habitant quisque conubia luctus interdum leo metus aliquam curabitur eros fringilla natoque? Gravida at malesuada sociosqu lorem condimentum diam. Ante quam netus vehicula mus a cras et et purus senectus. Ultricies curabitur porta volutpat adipiscing, phasellus varius. Sollicitudin.
+                Our proposed workshop aims to address emerging challenges and explore innovative solutions in the field of computer-aided design (CAD) 
+                for integrated circuits and systems for ultra low latency and high bandwidth scientific applications.  
+                The workshop builds on the ideas laid out in this white paper: <a href="https://doi.org/10.3389/fdata.2022.787421">“Applications and Techniques for Fast Machine Learning in Science”</a>
+                and the corresponding conference series Fast Machine Learning for Science (<a href="https://indico.cern.ch/event/1283970/">2023 edition</a>).  This workshop at ICCAD 2023 aims to bring domains together and forge new connections with the CAD community.  
             </p>
             <p class="text text-justify">
-              Dignissim hendrerit hendrerit placerat taciti vestibulum in cursus laoreet class sem libero. Dolor sociosqu urna orci dignissim maecenas arcu. Nascetur nostra aliquam mi dis tempus nec facilisis tristique pulvinar ornare aenean urna! Malesuada varius praesent varius nulla, non iaculis. Enim aliquam nulla pellentesque taciti enim facilisis etiam felis varius. Gravida, porttitor in ad. Ullamcorper nullam metus nisl donec vehicula ac. Rhoncus quisque pulvinar eget felis. Mauris dui class purus quis velit sem dignissim. Mus tellus potenti parturient. Ut est molestie.
+                Scientific applications across particle physics, astrophysics, material sciences, quantum information sciences, fusion energy (and beyond!) 
+                utilize data acquisition and in situ processing systems which require very low latency and high data bandwidth custom processing elements 
+                and real-time control modules.  Integrating data reduction and control applications with real-time machine learning algorithms can enable significant 
+                breakthroughs in the sciences.  We will bring together researchers, practitioners, and industry experts to exchange ideas, share applications, 
+                and discuss the latest advancements in CAD methodologies, algorithms, and tools. 
             </p>
           </div>
           </div>
@@ -64,13 +71,15 @@ <h2 class="add-top-margin">Overview</h2>
           <div class="flex-item flex-column">
             <h2 class="add-top-margin">Topics of interest</h2>
             <hr>
-            <p class="text">The areas of interest include but are not limited to: </p>
+            <p class="text">Topics of interest as they are related to real-time scientific applications: </p>
             <ul>
-              <li>Topic 1</li>
-              <li>Topic 2</li>
-              <li>Topic 3</li>
-              <li>Topic 4</li>
-              <li>Topic 5</li>
+              <li>Efficient algorithm design, implementation, and integration methodologies</li>
+              <li>Design automation and synthesis, timing analysis and optimization </li>
+              <li>Physical design and layout </li>
+              <li>High-level synthesis and system-level design for edge AI hardware</li>
+              <li>Robust machine learning, anomaly detection, and fault tolerance</li>
+              <li>Continuous, adaptive, and reinforcement learning for low latency control</li>
+              <li>Emerging technologies in CAD Machine learning and AI-assisted design</li>
             </ul>
           </div>
           </div>
diff --git a/submission.html b/submission.html
index 7519688..79de69b 100644
--- a/submission.html
+++ b/submission.html
@@ -45,10 +45,10 @@ <h1>Paper Submission</h1>
             <h2 class="add-top-margin">Important Dates</h2>
             <hr>
             <ul>
-              <li>Paper Submission Deadline: TBD</li>
-              <li>Notification: TBD</li>
-              <li>Camera-Ready: TBD</li>
-              <li>Workshop: TBD</li>
+              <li>Paper Submission Deadline: September 23, 2023 AOE</li>
+              <li>Notification: October 20, 2023 </li>
+              <li>Camera-Ready: October 27. 2023</li>
+              <li>Workshop: November 2, 2023</li>
             </ul>
           </div>
         </div>
@@ -57,7 +57,7 @@ <h2 class="add-top-margin">Important Dates</h2>
             <h2 class="add-top-margin">Format</h2>
             <hr>
             <p class="text">
-              We welcome four types of submissions:
+              We welcome three types of submissions:
             </p>
             <ol class="nested">
               <li>Technical papers with evaluation results</li>