Update people

Author: mbeyeler

index.json

@@ -3107,7 +3107,7 @@ <h3 class="m-0" itemprop="name">
 
 
     <div itemprop="articleBody">
-      <p class="m-0">We introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks to forecast patient perceptual capabilities across diverse prosthetic designs and tasks. We evaluate performance across six visual tasks, six electrode configurations, and two artificial …</p>
+      <p class="m-0">We introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks to forecast patient perceptual capabilities across diverse prosthetic designs and tasks.</p>
     </div>
 
 

people/beyeler_michael/index.html

@@ -122,8 +122,8 @@ Her research goal is to model the dynamics of brain functions by integrating kno
       <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
 
       <guid>https://bionicvisionlab.org/people/lima_adriano/</guid>
-      <description>&lt;p&gt;Adriano Melo Lima Cotralha Afonso is a volunteer in the lab focusing on computational models for robust navigation that draw on conceptsat the intersection of neuroscience and artificial intelligence. 
-This project is directly aligned with his undergraduate training in Psychological &amp;amp; Brain Sciences.&lt;/p&gt;
+      <description>&lt;p&gt;Adriano Lima is a volunteer research assistant in the lab and a recent UC Santa Barbara graduate with a BS in Psychological &amp;amp; Brain Sciences. He is passionate about work at the intersection of neuroscience and artificial intelligence, focusing on computational models for robust vision grounded in neural data. More broadly, he is curious about topics ranging from the philosophy of mind to computational neuroscience and beyond.&lt;/p&gt;
+&lt;p&gt;Outside of the lab, he enjoys music, video games, and spending time in nature.&lt;/p&gt;
 </description>
     </item>
 

people/index.xml

@@ -489,8 +489,8 @@ <h5 class="mt-1" itemprop="worksFor" itemscope itemtype="http://schema.org/Organ
 
 
 
-    <p>Adriano Melo Lima Cotralha Afonso is a volunteer in the lab focusing on computational models for robust navigation that draw on conceptsat the intersection of neuroscience and artificial intelligence. 
-This project is directly aligned with his undergraduate training in Psychological &amp; Brain Sciences.</p>
+    <p>Adriano Lima is a volunteer research assistant in the lab and a recent UC Santa Barbara graduate with a BS in Psychological &amp; Brain Sciences. He is passionate about work at the intersection of neuroscience and artificial intelligence, focusing on computational models for robust vision grounded in neural data. More broadly, he is curious about topics ranging from the philosophy of mind to computational neuroscience and beyond.</p>
+<p>Outside of the lab, he enjoys music, video games, and spending time in nature.</p>
 
 
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people/lima_adriano/index.html

@@ -1407,7 +1407,7 @@ <h3 class="m-0" itemprop="name">
 
 
     <div itemprop="articleBody">
-      <p class="m-0">We introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks to forecast patient perceptual capabilities across diverse prosthetic designs and tasks. We evaluate performance across six visual tasks, six electrode configurations, and two artificial …</p>
+      <p class="m-0">We introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks to forecast patient perceptual capabilities across diverse prosthetic designs and tasks.</p>
     </div>
 
 

people/varshney_apurv/index.html

@@ -523,7 +523,7 @@ <h2><a href="/publications/2025-07-vision-loss-scene-understanding/">Distinct ro
     <h2><a href="/publications/2025-06-deep-learning-framework-predict-functional-vision/">A deep learning framework for predicting functional visual performance in bionic eye users</a></h2>
     <div class="article-style">
 
-      We introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks to forecast patient perceptual capabilities across diverse prosthetic designs and tasks. We evaluate performance across six visual tasks, six electrode configurations, and two artificial vision models, positioning our CVP approach as a scalable pre-implantation method.
+      We introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks to forecast patient perceptual capabilities across diverse prosthetic designs and tasks.
 
     </div>
   </div>

publication_types/6/index.html

@@ -24,7 +24,7 @@
 
 
 
-  <meta name="description" content="We introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks to forecast patient perceptual capabilities across diverse prosthetic designs and tasks. We evaluate performance across six visual tasks, six electrode configurations, and two artificial vision models, positioning our CVP approach as a scalable pre-implantation method.">
+  <meta name="description" content="We introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks to forecast patient perceptual capabilities across diverse prosthetic designs and tasks.">
 
 
   <link rel="alternate" hreflang="en-us" href="https://bionicvisionlab.org/publications/2025-06-deep-learning-framework-predict-functional-vision/">
@@ -120,7 +120,7 @@
   <meta property="og:site_name" content="Bionic Vision Lab">
   <meta property="og:url" content="https://bionicvisionlab.org/publications/2025-06-deep-learning-framework-predict-functional-vision/">
   <meta property="og:title" content="A deep learning framework for predicting functional visual performance in bionic eye users | Bionic Vision Lab">
-  <meta property="og:description" content="We introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks to forecast patient perceptual capabilities across diverse prosthetic designs and tasks. We evaluate performance across six visual tasks, six electrode configurations, and two artificial vision models, positioning our CVP approach as a scalable pre-implantation method."><meta property="og:image" content="https://bionicvisionlab.org/publications/2025-06-deep-learning-framework-predict-functional-vision/featured.png">
+  <meta property="og:description" content="We introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks to forecast patient perceptual capabilities across diverse prosthetic designs and tasks."><meta property="og:image" content="https://bionicvisionlab.org/publications/2025-06-deep-learning-framework-predict-functional-vision/featured.png">
   <meta property="twitter:image" content="https://bionicvisionlab.org/publications/2025-06-deep-learning-framework-predict-functional-vision/featured.png"><meta property="og:locale" content="en-us">
 
   <meta property="article:published_time" content="2025-06-25T09:49:00&#43;00:00">

publications/2025-06-deep-learning-framework-predict-functional-vision/index.html

@@ -2950,7 +2950,7 @@ <h3 class="m-0" itemprop="name">
 
 
     <div itemprop="articleBody">
-      <p class="m-0">We introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks to forecast patient perceptual capabilities across diverse prosthetic designs and tasks. We evaluate performance across six visual tasks, six electrode configurations, and two artificial …</p>
+      <p class="m-0">We introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks to forecast patient perceptual capabilities across diverse prosthetic designs and tasks.</p>
     </div>
 
 

publications/index.html

@@ -1648,7 +1648,7 @@ <h3 class="m-0" itemprop="name">
 
 
     <div itemprop="articleBody">
-      <p class="m-0">We introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks to forecast patient perceptual capabilities across diverse prosthetic designs and tasks. We evaluate performance across six visual tasks, six electrode configurations, and two artificial …</p>
+      <p class="m-0">We introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks to forecast patient perceptual capabilities across diverse prosthetic designs and tasks.</p>
     </div>
 
 

research/smart-bionic-eye/index.html

@@ -469,13 +469,13 @@ <h2 itemprop="name">PSY-221F: Computational Neuroscience</h2>
 
   <span class="middot-divider"></span>
   <span class="article-date">
-    <time>TBD</time>
+    <time>12:30 - 1:45</time>
   </span>
 
 
   <span class="middot-divider"></span>
   <span class="article-date">
-    <time>TBD</time>
+    <time>PSY-E 3834</time>
   </span>