update research topics - seil

Author: seilk

index.html

@@ -441,25 +441,22 @@ <h3>Xingchen Zhao</h3>
           <h1>Research Topics</h1>
         </div>
         <div class="col-12">
-          <h2 id="medical-imaging">Medical Imaging</h2>
-          <p>Artificial Intelligence (AI) is transforming the healthcare industry by automating
-            workflows and enhancing diagnostic capabilities. Our research includes:</p>
+          <h2 id="medical-imaging">Medical imaging analysis</h2>
           <ul>
-            <li>Implementing AI-driven techniques to improve the accuracy and speed of medical
-              diagnoses.</li>
-            <li>Developing algorithms to analyze and interpret complex medical data.</li>
-            <li>Creating innovative solutions for early detection and monitoring of diseases through
-              advanced imaging technologies.</li>
+            <li>Alzheimer's Disease Analysis with MRI/PET/DTI</li>
+            <li>Brain Connectivity</li>
+            <li>Data Harmonization</li>
+            <li>Brain Lesion Segmentation</li>
+            <li>Multimodal Generative Model</li>
           </ul>
-          <h2 id="computer-vision">Computer Vision</h2>
-          <p>Computer Vision is advancing the capabilities of automated image and video analysis.
-            Our research encompasses:</p>
+          <h2 id="computer-vision">Computer vision / Machine learning / Deep learning</h2>
           <ul>
-            <li>Designing algorithms that enable machines to understand and interpret visual data.
-            </li>
-            <li>Developing techniques for secure image processing and data protection.</li>
-            <li>Enhancing hardware to optimize the performance and efficiency of computer vision
-              systems.</li>
+            <li>PAC-Bayesian Performance Guarantee</li>
+            <li>Domain Generalization/Adaptation - Theory and Application</li>
+            <li>Semantic Segmentation</li>
+            <li>Generative Models</li>
+            <li>Multimodal Learning</li>
+            <li>Multimodal Large Language Models (for medicine)</li>
           </ul>
         </div>
       </div>