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<!DOCTYPE HTML>
<html lang="en">
<head>
<!-- Google tag (gtag.js) -->
<script async src="https://www.googletagmanager.com/gtag/js?id=G-LKXJ49X3W5"></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag(){dataLayer.push(arguments);}
gtag('js', new Date());
gtag('config', 'G-LKXJ49X3W5');
</script>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<title>Aryan Jain</title>
<meta name="author" content="Jon Barron">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="google-site-verification" content="K9KgflCc4PXSuzi-3eiiT6miTv4jD6uq5sGknNQjSKs" />
<link rel="stylesheet" type="text/css" href="stylesheet.css">
<link rel="icon"
href="data:image/svg+xml,<svg xmlns=%22http://www.w3.org/2000/svg%22 viewBox=%220 0 100 100%22><text y=%22.9em%22 font-size=%2290%22>🌐</text></svg>">
</head>
<body>
<table
style="width:100%;max-width:800px;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
<tbody>
<tr style="padding:0px">
<td style="padding:0px">
<table
style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
<tbody>
<tr style="padding:0px">
<td style="padding:2.5%;width:63%;vertical-align:middle">
<p style="text-align:center">
<name>Aryan Jain</name>
</p>
<p>
I am student at UC Berkeley, majoring in <a href="https://eecs.berkeley.edu">Electrical Engineering
and Computer Sciences (EECS)</a> and graduating in 2024.
</p>
<p>
I am also an undergraduate researcher in the <a href="https://rll.berkeley.edu">Robot Learning
Lab</a>, where I am advised by <a href="https://people.eecs.berkeley.edu/~pabbeel/">Pieter
Abbeel</a> and <a href="https://aravindr93.github.io">Aravind Rajeswaran</a>.
Previously, I was an undergraduate researcher at the <a href="http://www.lbl.gov">Lawrence Berkeley
Lab</a>, where I was advised by <a href="https://sites.google.com/usfca.edu/neuralens">Xiaosheng
Huang</a>.
</p>
<p style="text-align:center">
<a href="mailto:[email protected]">Email</a>  / 
<a href="https://scholar.google.com/citations?user=d2CAfg4AAAAJ&hl=en">Google Scholar</a>
 / 
<a href="https://github.com/Aryan9101">Github</a>  / 
<a href="https://www.linkedin.com/in/aryan-jain-9101/">LinkedIn</a>
</p>
</td>
<td style="padding:2.5%;width:40%;max-width:40%">
<a href="images/aryan-jain.jpeg"><img style="width:100%;max-width:100%" alt="profile photo"
src="images/aryan-jain.jpeg" class="hoverZoomLink circle"></a>
</td>
</tr>
</tbody>
</table>
<table
style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
<tbody>
<tr>
<td style="padding:20px;width:100%;vertical-align:middle">
<heading>Research</heading>
<p>
I'm broadly interested in robot learning, offline reinforcement learning, generative modeling and
self-supervised representation learning.
In particular, I hope to build complex intelligent agents that can generalize to and solve a wide
variety of tasks in the real world.
My current research revolves around visual representation learning and domain adaptation for
embodied intelligence.
</p>
</td>
</tr>
</tbody>
</table>
<table
style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
<tbody>
<!--
<tr bgcolor="#ffffd0">
<td style="padding:20px;width:25%;vertical-align:middle">
<img src='images/dreamfusion.jpg' width="160">
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://dreamfusion3d.github.io/">
<papertitle>DreamFusion: Text-to-3D using 2D Diffusion</papertitle>
</a>
<br>
<a href="https://cs.stanford.edu/~poole/">Ben Poole</a>,
<a href="https://www.ajayj.com/">Ajay Jain</a>,
<strong>Jonathan T. Barron</strong>,
<a href="https://bmild.github.io/">Ben Mildenhall</a>
<br>
<em>arXiv</em>, 2022
<br>
<a href="https://dreamfusion3d.github.io/">project page</a>
/
<a href="https://arxiv.org/abs/2209.14988">arXiv</a>
/
<a href="https://dreamfusion3d.github.io/gallery.html">gallery</a>
<p></p>
<p>
We optimize a NeRF from scratch using a pretrained text-to-image diffusion model to do text-to-3D generative modeling.
</p>
</td>
</tr>
<tr onmouseout="pnf_stop()" onmouseover="pnf_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<img src='images/pnf_after.jpg' width="160">
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="TODO">
<papertitle>Polynomial Neural Fields for Subband Decomposition</papertitle>
</a>
<br>
<a href="https://www.guandaoyang.com/">Guandao Yang*</a>,
<a href="https://sagiebenaim.github.io/">Sagie Benaim*</a>,
<a href="https://varunjampani.github.io/">Varun Jampani</a>,
<a href="https://www.kylegenova.com/">Kyle Genova</a>,
<strong>Jonathan T. Barron</strong>,
<a href="https://www.cs.princeton.edu/~funk/">Thomas Funkhouser</a>,
<a href="http://home.bharathh.info/">Bharath Hariharan</a>,
<a href="https://sergebelongie.github.io/">Serge Belongie</a>
<br>
<em>NeurIPS</em>, 2022
<p>
Representing neural fields as a composition of manipulable and interpretable components lets you do things like reason about frequencies and scale.
</p>
</td>
</tr>
<tr onmouseout="refnerf_stop()" onmouseover="refnerf_start()" bgcolor="#ffffd0">
<td style="padding:20px;width:25%;vertical-align:middle">
<img src='images/refnerf.jpg' width="160">
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://dorverbin.github.io/refnerf/index.html">
<papertitle>Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields</papertitle>
</a>
<br>
<a href="https://scholar.harvard.edu/dorverbin/home">Dor Verbin</a>,
<a href="https://phogzone.com/">Peter Hedman</a>,
<a href="https://bmild.github.io/">Ben Mildenhall</a>, <br>
<a href="Todd Zickler">Todd Zickler</a>,
<strong>Jonathan T. Barron</strong>,
<a href="https://pratulsrinivasan.github.io/">Pratul Srinivasan</a>
<br>
<em>CVPR</em>, 2022   <font color="red"><strong>(Oral Presentation, Best Student Paper Honorable Mention)</strong></font>
<br>
<a href="https://dorverbin.github.io/refnerf/index.html">project page</a>
/
<a href="https://arxiv.org/abs/2112.03907">arXiv</a>
/
<a href="https://youtu.be/qrdRH9irAlk">video</a>
<p></p>
<p>Explicitly modeling reflections in NeRF produces realistic shiny surfaces and accurate surface normals, and lets you edit materials.</p>
</td>
</tr>
-->
</tbody>
</table>
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<tr>
<td>
<heading>Teaching</heading>
</td>
</tr>
</tbody>
</table>
<table width="100%" align="center" border="0" cellpadding="20">
<tbody>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img src="images/berkeley_eecs.jpg" alt="EECS" class="icon" width="200px" height="auto">
</td>
<td width="75%" valign="center">
<p>
<b>EECS 127: Optimization Models in Engineering</b>
<br>
Teaching Assistant: <a href="https://inst.eecs.berkeley.edu/~ee127/fa22/">Fall 2022</a>, <a
href="https://inst.eecs.berkeley.edu/~ee127/sp23/">Spring 2023</a>
<br>
Reader: Spring 2022
</p>
<p>
<b>CS 198-126: Modern Computer Vision and Deep Learning</b>
<br>
Facilitator/Instructor: <a href="http://ml.berkeley.edu/decal/modern-cv">Fall 2022</a>
</p>
<p>
<b>CS 70: Discrete Mathematics and Probability Theory</b>
<br>
Reader: <a href="http://www.fa21.eecs70.org">Fall 2021</a>, <a
href="http://www.sp21.eecs70.org">Spring 2021</a>
</p>
</td>
</tr>
</tbody>
</table>
<table
style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
<tbody>
<tr>
<td style="padding:20px;width:100%;vertical-align:middle">
<heading>Course Notes</heading>
<p>
I like to typeset my course notes in LaTeX!
Here are some from a few classes I've taken:
</p>
<a href="data/EECS_126_Notes.pdf">EECS 126: Probability and Random Processes</a>
<br>
<a href="data/Math_110_Notes.pdf">Math 110: Linear Algebra</a>
</td>
</tr>
</tbody>
</table>
<table
style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
<tbody>
<tr>
<td style="padding:0px">
<p style="text-align:right;font-size:small;">
<br>
Website template taken from <a href="https://jonbarron.info">Jon Barron</a>.
</p>
</td>
</tr>
</tbody>
</table>
</td>
</tr>
</table>
</body>
</html>