update descriptions and imgs

tianalei · Nov 23, 2024 · 3976639 · 3976639
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diff --git a/_bibliography/papers.bib b/_bibliography/papers.bib
@@ -8,5 +8,6 @@ @unpublished{lei2025TROVE
   langid = {english},
   selected={true},
   abbr={Manuscript},
-  preview={traj_visualize.png}
+  preview={traj_visualize.png},
+  abstract={Travel Mode Identification (TMI) has emerged as a crucial research topic in intelligent transportation. Accurate TMI automatically identifies travel modes from large-scale GPS trajectory datasets, which is essential for traffic management and travel planning. Conventional methods have improved accuracy by fusing spatial patterns and kinematic attributes at the input level. However, feature-level fusion approaches, which independently extract high-level trajectory features and align these complementary representations for cross-view semantic comprehension, remain underexplored. To address this gap, we propose MVCF-TMI, a novel framework that enhances TMI accuracy and model generalizability by aligning the kinematic and spatial views of GPS data through Multi-View Contrastive learning. Specifically, our framework exploits comprehensive spatial and kinematic characteristics leveraging a multi-view paradigm. Then, to enable better cross-view semantic understanding, we engage an inter-view contrastive loss function, optimizing feature alignment toward more effective view-specific representations within a shared subspace. This technique facilitates feature interaction, enhances feature consistency, and captures complementary information across distinct multi-view trajectory representations. Extensive experiments demonstrate that MVCF-TMI outperforms baseline approaches with a competitive accuracy of 86.45% on the large-scale dataset Geolife, demonstrating our method's ability to learn more discriminative and robust representations for the TMI task. The robust generalization capability of the proposed method was also observed. The MVCF-TMI model, pre-trained using self-supervised and supervised paradigms on the large-scale dataset, was transferred to low-data scenario on the SHL dataset, and demonstrated improved accuracy and robustness in this challenging setting.}
 }
diff --git a/_config.yml b/_config.yml
@@ -53,7 +53,7 @@ socials_in_search: true
 bib_search: true
 
 # Dimensions
-max_width: 800px
+max_width: 1000px
 
 # TODO: add layout settings (single page vs. multi-page)
 

diff --git a/_includes/projects.liquid b/_includes/projects.liquid
@@ -2,7 +2,11 @@
   <!--
   <a href="{% if project.redirect %}{{ project.redirect }}{% else %}{{ project.url | relative_url }}{% endif %}">
   -->
-  <a href=""></a>
+  {% if project.redirect %}
+    <a href="{{ project.redirect }}">
+  {% else %}
+    <a href="">
+  {% endif %}
     <div class="card h-100 hoverable">
       {% if project.img %}
         {%
@@ -16,6 +20,18 @@
       {% endif %}
       <div class="card-body">
         <h2 class="card-title" style="font-size:1.2em">{{ project.title }}</h2>
+
+        <!-- Add tags as badges -->
+        {% if project.tags %}
+          <div class="badges mb-2">
+            {% assign tag_string = project.tags | join: " " %}
+            {% assign tags = tag_string | split: ","| where_exp: "item", "item != ''" %}
+            {% for tag in tags %}
+              <span class="badge bg-light text-dark">{{ tag }}</span>
+            {% endfor %}
+          </div>
+        {% endif %}
+
         <p class="card-text">{{ project.description }}</p>
         <div class="row ml-1 mr-1 p-0">
           {% if project.github %}

diff --git a/_includes/projects_horizontal.liquid b/_includes/projects_horizontal.liquid
@@ -1,7 +1,11 @@
 <div class="col mb-4">
   <!-- <a href="{% if project.redirect %}{{ project.redirect }}{% else %}{{ project.url | relative_url }}{% endif %}">
   -->
-  <a href="">
+  {% if project.redirect %}
+    <a href="{{ project.redirect }}">
+  {% else %}
+    <a href="">
+  {% endif %}
     <div class="card h-100 hoverable">
       <div class="row no-gutters">
         {% if project.img %}
@@ -12,6 +16,18 @@
         <div class="{% if project.img %}col-md-6{% else %}col-md-12{% endif %}">
           <div class="card-body">
             <h3 class="card-title" style="font-size:1.2em">{{ project.title }}</h3>
+
+            <!-- Add tags as badges -->
+            {% if project.tags %}
+              <div class="badges mb-2">
+                {% assign tag_string = project.tags | join: " " %}
+                {% assign tags = tag_string | split: ","| where_exp: "item", "item != ''" %}
+                {% for tag in tags %}
+                  <span class="badge bg-light text-dark">{{ tag }}</span>
+                {% endfor %}
+              </div>
+            {% endif %}
+
             <p class="card-text">{{ project.description }}</p>
             <div class="row ml-1 mr-1 p-0">
               {% if project.github %}

diff --git a/_pages/about.md b/_pages/about.md
@@ -28,4 +28,4 @@ My research interests include:
 - trajectory representation learning
 - intelligent transportation systems
 
-I am actively seeking PhD opportunities in related fields starting in Fall 2025.
+I am actively seeking PhD or Research Assistant opportunities in related fields.
diff --git a/_projects/project_1_5G.md b/_projects/project_1_5G.md
@@ -1,9 +1,9 @@
 ---
 layout: page
 title: A Localization Approach Based on 5G Cellular Signaling Data and Individual Spatio-temporal Behavior
+tags: Python, QGIS, Data Analysis
 description: >
-    #Python, #QGIS
-    This project addressed the industrial challenge of low accuracy in building-level indoor user positioning using 5G data.
+    We developed a two-stage approach that significantly improved building-level user positioning accuracy using 5G mobile signal data. The solution combines cellular signal metrics with users' spatio-temporal behavior patterns and building functionalities, effectively addressing the challenge of low-precision 5G MR data for accurate building-user linking.
 importance: 1
 related_publications: false
 img: assets/img/5g_preview.png

diff --git a/_projects/project_2_OGE.md b/_projects/project_2_OGE.md
@@ -1,10 +1,12 @@
 ---
 layout: page
 title: OGE - a Platform for Earth Observation, Spatial Data Processing and Analysis
+tags: JAVA, PostgreSQL, Database
 description: >
-    #JAVA, #PostgreSQL
-    Designed and implemented a PostgreSQL database to store global geospatial vector data, including database schemas, partitioning strategies, and table structures with appropriate fields and attributes.
+    I designed and implemented a PostgreSQL database to store global geospatial vector data, including database schemas, partitioning strategies, and table structures with appropriate fields and attributes.
 importance: 2
 related_publications: false
+img: assets/img/OGE.png
+redirect: http://openge.org.cn/en-US
 category: Participant
 ---
diff --git a/_projects/project_3_BSc_Thesis.md b/_projects/project_3_BSc_Thesis.md
@@ -1,9 +1,9 @@
 ---
 layout: page
 title: A GIS-based Method for Subgrade Compaction Management (BSc. Thesis)
+tags: PostgreSQL, PL/pgSQL, WebGIS
 description: >
-    #PL/pgSQL, #PostgreSQL
-    Developed a dynamic system for tracking and visualizing compaction passes with spatial vector data.
+    I developed a GIS-based real-time monitoring system that enables dynamic quality assessment of subgrade compaction through spatial analysis of compactor trajectories. The system features an innovative incremental update algorithm that dramatically improved geometric data processing efficiency from minutes to milliseconds, along with a web-based platform for real-time visualization and anomaly detection.
 importance: 3
 related_publications: false
 img: assets/img/compaction_visualize.png

diff --git a/_projects/project_4_Bus.md b/_projects/project_4_Bus.md
@@ -1,9 +1,9 @@
 ---
 layout: page
 title: An Automated Bus Payment System Based on Geo-fencing
+tags: JAVA, PostgreSQL, WebGIS
 description: >
-    #JAVA, #PostgreSQL
-    This system implemented automatic payment for buses to alleviate congestion at the entrance.
+    We developed an intelligent ticketing system that enables automatic ticket verification through real-time BeiDou positioning and geofencing algorithms, eliminating manual ticket checking at scenic spots. The system features a modular design that ensures reliable performance and seamless tourist experience. I implemented API development for frontend-backend interaction, along with comprehensive database design and development.
 importance: 4
 related_publications: false
 img: assets/img/bus_preview.png

diff --git a/_projects/project_5_RS.md b/_projects/project_5_RS.md
@@ -1,9 +1,10 @@
 ---
 layout: page
 title: An Agricultural Greenhouse Extraction Method Based on Sentinel-2 Data
+tags: Python, PyTorch, Remote Sensing
+img: assets/img/greenhouse.png
 description: >
-    #Python, #PyTorch
-    This method utilized a ResNet34 network pre-trained on ImageNet to achieve high-precision identification of agricultural greenhouses
+    We proposed a novel approach combining Convolutional Neural Networks (CNN) with transfer learning, utilizing a ResNet34 network pre-trained on ImageNet to achieve high-precision identification of agricultural greenhouses using Sentinel-2 high-resolution imagery.
 importance: 5
 related_publications: false
 category: Participant

diff --git a/_sass/_base.scss b/_sass/_base.scss
@@ -179,10 +179,14 @@ ul.task-list input[type="checkbox"] {
   }
 
   .card-body {
-    padding: 1.25rem 1.25rem 1.25rem 1.25rem;
+    padding: 0.2rem 0.8rem 0.8rem 0.8rem;
   }
 }
 
+p.card-text {
+  margin-bottom: 0.2rem;
+}
+
 // Citation
 
 .citation,
@@ -654,6 +658,17 @@ footer.sticky-bottom {
   }
 }
 
+.badges {
+  .badge {
+    margin-right: 0.5rem;
+    padding: 0.4em 0.8em;
+    font-size: 0.75rem;
+    font-weight: 600;
+    border: 1px solid #dee2e6;
+    color: var(--global-text-color-light) !important;
+  }
+}
+
 // Publications
 
 .publications {
@@ -668,7 +683,7 @@ footer.sticky-bottom {
   }
 
   h2 {
-    margin-bottom: 1rem;
+    margin-bottom: 0rem;
 
     span {
       font-size: 1.5rem;
@@ -834,7 +849,10 @@ footer.sticky-bottom {
 
 // Rouge Color Customization
 figure.highlight {
-  margin: 0 0 1rem;
+  margin: 0 0 0.2rem;
+}
+figure {
+  margin: 0 0 0.3rem;
 }
 
 pre {

diff --git a/assets/img/5g_preview.png b/assets/img/5g_preview.png
diff --git a/assets/img/OGE.png b/assets/img/OGE.png
diff --git a/assets/img/greenhouse.png b/assets/img/greenhouse.png
diff --git a/assets/json/resume.json b/assets/json/resume.json
@@ -5,7 +5,7 @@
     "image": "",
     "email": "[email protected]",
     "phone": "(+86) 18851084890",
-    "url": "https://luciatl.github.io",
+    "url": "https://tianalei.github.io",
     "summary": "MSc candidate in GIS at Wuhan University, with a passion for research and programming",
     "location": {
       "address": "G9P7+CP8, Wuchang District",