hao update

README.md

@@ -1,3 +1,14 @@
 # hao-ai-lab.github.io
 
 This git repo hosts all content displayed on the website of Hao AI Lab @ UCSD.
+
+
+## How to build
+
+1. Install Hugo > 0.12
+2. Run the following commands:
+```bash
+git clone https://github.com/hao-ai-lab/hao-ai-lab.github.io.git
+cd hao-ai-lab.github.io
+hugo server
+```

content/contact.md

@@ -5,10 +5,12 @@ url: "/contact/"
 summary: contact
 ---
 
-### Contact for Prospective Lab Members
+### Prospective Lab Members
 
 {{< justify >}}
 
-Thank you for your interest in our lab at UC San Diego! If you work on machine learning systems and are interested in joining us, please first [**fill out this form**](https://forms.office.com/pages/responsepage.aspx?id=DQSIkWdsW0yxEjajBLZtrQAAAAAAAAAAAANAAa-SsTJUN0NXSDJSU0ExVVZHR0w3RDlHQVM0NDJaOS4u). After submitting the form, please drop professor Hao Zhang an email (haozhang@ucsd.edu).
+Thank you for your interest in our lab at UC San Diego! If you work on machine learning and systems, and are interested in joining us, please [**read the page**](https://cseweb.ucsd.edu/~haozhang/prospective_student) on how to get involved. 
+In general, please first [**fill out this form**](https://forms.office.com/pages/responsepage.aspx?id=DQSIkWdsW0yxEjajBLZtrQAAAAAAAAAAAANAAa-SsTJUN0NXSDJSU0ExVVZHR0w3RDlHQVM0NDJaOS4u). 
+After submitting the form, please drop an email to Prof. Hao Zhang (haozhang@ucsd.edu).
 
 {{< /justify >}}

content/home.md

@@ -10,8 +10,6 @@ cover:
   caption: "Hao AI Lab @ UCSD"
 ---
 
-### Mission Statement 
-
 {{< justify >}}
 
 Welcome to the UCSD Hao Lab website! We are passionate about designing strong, efficient, and secure machine learning models and algorithms, and in building scalable, practical distributed systems that can support real-world machine learning workloads. We also develop open-sourced models and systems to democratize the access of Large Language Models (LLMs). We are affiliated with the UCSD ML System Group.

content/people.md

@@ -26,8 +26,7 @@ summary: people
 {{< /lab_members_grid >}}
 
 ### Alumni
-
-{{< alumni category="PhD Students" >}}
+{{< alumni >}}
 {{< alumni_entry name="Hexu Zhao" description="Undergrad Intern, now PhD Student at NYU." homepage="https://github.com/TarzanZhao">}}
 {{< alumni_entry name="Runyu Lu" description="Undergrad Intern, now PhD Student at UMich." homepage="https://lry89757.github.io/">}}
 {{< alumni_entry name="Dacheng Li" description="Master's, now PhD Student at UC Berkeley." homepage="https://dachengli1.github.io/">}}

gen_publications.py

@@ -0,0 +1,45 @@
+import json
+from collections import defaultdict
+
+# Function to convert JSON to Hugo format
+def convert_json_to_hugo(publications):
+    # Organize publications by year
+    publications_by_year = defaultdict(list)
+    for publication in publications:
+        year = publication["date"].split("/")[1]
+        publications_by_year[year].append(publication)
+
+    # Sort years in descending order
+    sorted_years = sorted(publications_by_year.keys(), reverse=True)
+
+    # Format publications for Hugo
+    hugo_output = ""
+    for year in sorted_years:
+        hugo_output += f"### {year}\n\n"
+        for publication in publications_by_year[year]:
+            title = publication["title"]
+            venue = publication.get("venue", "")
+            paper_link = publication.get("pdf", "")
+            code_link = publication.get("code", "")
+            authors = publication["authors"]
+            # Assuming 'data-topic' needs to be manually adjusted or derived from 'tag'
+            data_topic = publication["tag"] # This is a placeholder, adjust as needed
+            award = publication["award"]
+            project = publication["project"]
+
+            hugo_output += (f"{{{{< publication title=\"{title}\" venue=\"{venue}\" "
+                            f"paperLink=\"{paper_link}\" codeLink=\"{code_link}\" "
+                            f"award=\"{award}\" project=\"{project}\" data-topic=\"{data_topic}\" >}}}}\n")
+            hugo_output += f"{authors}\n"
+            hugo_output += "{{< /publication >}}\n\n"
+        hugo_output += "&emsp;\n\n"
+
+    return hugo_output
+
+# Load JSON data from file
+with open('publications.json', 'r') as file:
+    publications_json = json.load(file)
+
+# Convert and print the Hugo formatted string
+hugo_format = convert_json_to_hugo(publications_json)
+print(hugo_format)

layouts/shortcodes/publication.html

@@ -1,6 +1,18 @@
 <div class="publication-reference" style="text-align: justify;" data-topic="{{ .Params.topic }}">
-    <p><strong>{{ .Get "title" }}</strong><br>
+    <p>
+    <a href="{{ .Get "paperLink" }}">{{ .Get "title" }}</a><br>
     {{ .Inner }}<br>
-    <em>{{ .Get "venue" }}</em> (<a href="{{ .Get "paperLink" }}">Paper</a>, <a href="{{ .Get "codeLink" }}">Code</a>)
+    <strong>{{ .Get "venue" }}</strong>
+    {{ with .Get "award" }}
+        <strong style="color: red;">({{ . }})</strong>
+    {{ end }}
+
+        <br>
+    {{ with .Get "codeLink" }}
+        [<a href="{{ . }}">code</a>]
+    {{ end }}
+    {{ with .Get "project" }}
+        [<a href="{{ . }}">project</a>]
+    {{ end }}
     </p>
 </div>

public/contact/index.html

@@ -166,9 +166,11 @@ <h1 class="post-title entry-hint-parent">
 
 </div>
   </header> 
-  <div class="post-content"><h3 id="contact-for-prospective-lab-members">Contact for Prospective Lab Members<a hidden class="anchor" aria-hidden="true" href="#contact-for-prospective-lab-members">#</a></h3>
+  <div class="post-content"><h3 id="prospective-lab-members">Prospective Lab Members<a hidden class="anchor" aria-hidden="true" href="#prospective-lab-members">#</a></h3>
 <div style="text-align: justify;">
-    Thank you for your interest in our lab at UC San Diego! If you work on machine learning systems and are interested in joining us, please first <a href="https://forms.office.com/pages/responsepage.aspx?id=DQSIkWdsW0yxEjajBLZtrQAAAAAAAAAAAANAAa-SsTJUN0NXSDJSU0ExVVZHR0w3RDlHQVM0NDJaOS4u"><strong>fill out this form</strong></a>. After submitting the form, please drop professor Hao Zhang an email (<a href="mailto:haozhang@ucsd.edu">haozhang@ucsd.edu</a>).
+    Thank you for your interest in our lab at UC San Diego! If you work on machine learning and systems, and are interested in joining us, please <a href="https://cseweb.ucsd.edu/~haozhang/prospective_student"><strong>read the page</strong></a> on how to get involved.
+In general, please first <a href="https://forms.office.com/pages/responsepage.aspx?id=DQSIkWdsW0yxEjajBLZtrQAAAAAAAAAAAANAAa-SsTJUN0NXSDJSU0ExVVZHR0w3RDlHQVM0NDJaOS4u"><strong>fill out this form</strong></a>.
+After submitting the form, please drop an email to Prof. Hao Zhang (<a href="mailto:haozhang@ucsd.edu">haozhang@ucsd.edu</a>).
 </div>
 
 

public/home/index.html

@@ -169,8 +169,7 @@ <h1 class="post-title entry-hint-parent">
 <figure class="entry-cover"><img loading="eager" src="//localhost:1313/img/ucsd-geisel.jpg" alt="Hao AI Lab @ UCSD">
         <p>Hao AI Lab @ UCSD</p>
 </figure>
-  <div class="post-content"><h3 id="mission-statement">Mission Statement<a hidden class="anchor" aria-hidden="true" href="#mission-statement">#</a></h3>
-<div style="text-align: justify;">
+  <div class="post-content"><div style="text-align: justify;">
     Welcome to the UCSD Hao Lab website! We are passionate about designing strong, efficient, and secure machine learning models and algorithms, and in building scalable, practical distributed systems that can support real-world machine learning workloads. We also develop open-sourced models and systems to democratize the access of Large Language Models (LLMs). We are affiliated with the UCSD ML System Group.
 </div>
 

public/index.html

@@ -2,7 +2,7 @@
 <html lang="en" dir="auto">
 
 <head>
-	<meta name="generator" content="Hugo 0.123.0"><script src="/livereload.js?mindelay=10&amp;v=2&amp;port=1313&amp;path=livereload" data-no-instant defer></script><link rel="stylesheet" href="/css/style.css">
+	<meta name="generator" content="Hugo 0.123.8"><script src="/livereload.js?mindelay=10&amp;v=2&amp;port=1313&amp;path=livereload" data-no-instant defer></script><link rel="stylesheet" href="/css/style.css">
 <link rel="stylesheet" href="/css/custom.css">
 <link href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.3/css/all.min.css" rel="stylesheet">
 <meta charset="utf-8">
@@ -181,8 +181,7 @@ <h1 class="post-title entry-hint-parent">
 </figure>
             <h1></h1>
             <div class="post-content">
-              <h3 id="mission-statement">Mission Statement</h3>
-<div style="text-align: justify;">
+              <div style="text-align: justify;">
     Welcome to the UCSD Hao Lab website! We are passionate about designing strong, efficient, and secure machine learning models and algorithms, and in building scalable, practical distributed systems that can support real-world machine learning workloads. We also develop open-sourced models and systems to democratize the access of Large Language Models (LLMs). We are affiliated with the UCSD ML System Group.
 </div>
 

public/people/index.html

@@ -483,7 +483,7 @@ <h3 id="alumni">Alumni<a hidden class="anchor" aria-hidden="true" href="#alumni"
 </head>
 
 <div class="alumni-section">
-    <h2>PhD Students</h2>
+    <h2></h2>
     <ul>
 
 <head>