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<!DOCTYPE html> | ||
<html lang="en"> | ||
<head> | ||
<meta charset="UTF-8" /> | ||
<meta name="viewport" content="width=device-width, initial-scale=1.0" /> | ||
<meta http-equiv="X-UA-Compatible" content="ie=edge" /> | ||
<link | ||
rel="stylesheet" | ||
href="https://use.fontawesome.com/releases/v5.4.1/css/all.css" | ||
integrity="sha384-5sAR7xN1Nv6T6+dT2mhtzEpVJvfS3NScPQTrOxhwjIuvcA67KV2R5Jz6kr4abQsz" | ||
crossorigin="anonymous" | ||
/> | ||
<link rel="stylesheet" href="style.css" /> | ||
<title>Suraj Parmar</title> | ||
</head> | ||
|
||
<head> | ||
<meta charset="UTF-8"> | ||
<meta name="viewport" content="width=device-width, initial-scale=1.0"> | ||
<meta http-equiv="X-UA-Compatible" content="ie=edge"> | ||
<link rel="stylesheet" href="https://use.fontawesome.com/releases/v5.4.1/css/all.css" | ||
integrity="sha384-5sAR7xN1Nv6T6+dT2mhtzEpVJvfS3NScPQTrOxhwjIuvcA67KV2R5Jz6kr4abQsz" crossorigin="anonymous"> | ||
<link rel="stylesheet" href="style.css"> | ||
<title>Suraj Parmar</title> | ||
</head> | ||
<body> | ||
<nav class="navigation"> | ||
<div class="nav-links"> | ||
<a href="#about">About</a> | ||
<a href="writings.html">Writings</a> | ||
<a | ||
href="https://drive.google.com/file/d/1f8oKQhlB1KE5AiOP43beUiShuKVjmUMo/view?usp=sharing " | ||
target="_blank" | ||
>Resume</a | ||
> | ||
</div> | ||
</nav> | ||
|
||
<body> | ||
<div class="grid-2"> | ||
<div class="grid-2"> | ||
<div class="section-1"> | ||
<h1>Suraj Parmar</h1> | ||
<p>Toronto, Canada</p> | ||
<a href="https://twitter.com/parmarsuraj99"><i class="fab fa-twitter"></i> </a> | ||
<a href="https://github.com/parmarsuraj99"><i class="fab fa-github"></i> </a> | ||
<a href="https://www.linkedin.com/in/parmarsuraj99/"><i class="fab fa-linkedin"></i> </a> | ||
<a href="https://parmarsuraj99.medium.com/"><i class="fab fa-medium"></i> </a> | ||
<a href="https://www.youtube.com/@parmarsuraj99"><i class="fab fa-youtube"></i></a> | ||
<a href="https://huggingface.co/surajp" class="hf | ||
emoji">HF</a> | ||
<h1>Suraj Parmar</h1> | ||
<p>Toronto, Canada</p> | ||
<a href="https://twitter.com/parmarsuraj99" | ||
><i class="fab fa-twitter"></i> | ||
</a> | ||
<a href="https://github.com/parmarsuraj99" | ||
><i class="fab fa-github"></i> | ||
</a> | ||
<a href="https://www.linkedin.com/in/parmarsuraj99/" | ||
><i class="fab fa-linkedin"></i> | ||
</a> | ||
<a href="https://parmarsuraj99.medium.com/" | ||
><i class="fab fa-medium"></i> | ||
</a> | ||
<a href="https://www.youtube.com/@parmarsuraj99" | ||
><i class="fab fa-youtube"></i | ||
></a> | ||
<a href="https://huggingface.co/surajp" class="hf emoji">HF</a> | ||
</div> | ||
<div class="section-2"> | ||
<h2>About</h2> | ||
<p>Hi, I am Suraj Parmar, currently working as a Machine Learning Engineer at a healthcare start-up in Toronto. | ||
</p> | ||
<p>I have worked on various projects involving statistical and deep learning forecasting and classification | ||
models. Building and deploying efficient Retrieval Augmented Generation (RAG) pipelines in completely | ||
offline environments. </p> | ||
</p> | ||
<p>Apart from that, I have been researching on the Numerai datasets for financial data. | ||
My main focus right now is Transformers on cross-sectional asset prediction involving self-supervised | ||
learning. Can read more about it on my blog. | ||
</p> | ||
<p>My master's thesis was on the topic of "Utilizing Deep Learning for Enhancing Performance on Encrypted Stock | ||
Market Data". | ||
The goal was to extract robust and meaningful representations for Numerai datasets to improve the GBDT | ||
baseline model.</p> | ||
<p>I previously interned at Zujo, a Computer Vision start-up in India, | ||
and worked at RealAdvisor as a Data | ||
Scientist remotely. </p> | ||
|
||
<p>I am available for contract and freelance work. | ||
Feel free to reach out to me on my email or social media | ||
handles.</p> | ||
|
||
<h2>Contact </h2> | ||
<a href="mailto:[email protected]">[email protected]</a> | ||
<p>Say hi on Twitter, LinkedIn :)</p> | ||
<h2>About</h2> | ||
<p> | ||
Hi, I am Suraj Parmar, currently working as a Machine Learning | ||
Engineer at a medical-legal start-up in Toronto. Where I am managing | ||
the cloud infrastructure, building and scaling agentic document | ||
processing pipelines that can scales to hundreds of customers per day. | ||
</p> | ||
<p> | ||
Previously, I worked at a healthcare start-up, SpassMed in Toronto | ||
where I have worked on projects involving statistical and deep | ||
learning based forecasting and classification models. Built and | ||
deployed efficient Retrieval Augmented Generation (RAG) pipelines in | ||
completely offline environments. Published papers on the topic of | ||
early Sepsis detection. | ||
</p> | ||
<p> | ||
My master's thesis was on the topic of "Utilizing Deep Learning for | ||
Enhancing Performance on Encrypted Stock Market Data". The goal was to | ||
extract robust and meaningful representations for Numerai datasets to | ||
improve the GBDT baseline model. I have been researching on the | ||
Numerai datasets for financial data. My main focus right now is | ||
Transformers on cross-sectional asset prediction involving | ||
self-supervised learning. Can read more about it on my | ||
<a | ||
href="https://parmarsuraj99.medium.com/era-of-transformers-792e5960e287/" | ||
>blog</a | ||
>. | ||
</p> | ||
<p> | ||
I previously interned at Zujo, a Computer Vision start-up in India, | ||
and later worked at RealAdvisor as a Data Scientist remotely. | ||
</p> | ||
<p> | ||
I am available for contract and freelance work. Feel free to reach out | ||
to me on my email or social media handles. | ||
</p> | ||
|
||
<h2>Contact Me</h2> | ||
<a href="mailto:[email protected]">[email protected]</a> | ||
<p> | ||
Say hi on <a href="https://twitter.com/parmarsuraj99">Twitter</a>, | ||
<a href="https://www.linkedin.com/in/parmarsuraj99/">LinkedIn</a> :) | ||
</p> | ||
</div> | ||
</div> | ||
</body> | ||
|
||
</html> | ||
</div> | ||
</body> | ||
</html> |
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/* global */ | ||
@import url('https://fonts.googleapis.com/css?family=Roboto'); | ||
@import url("https://fonts.googleapis.com/css?family=Roboto"); | ||
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||
.grid-2{ | ||
display: grid; | ||
grid-template-columns: repeat(2,1fr); | ||
.grid-2 { | ||
display: grid; | ||
grid-template-columns: repeat(2, 1fr); | ||
} | ||
|
||
body{ | ||
margin: 0; | ||
padding: 0; | ||
font-family: 'Roboto', sans-serif; | ||
background-color: #494f5c; | ||
color: #e3e3e3; | ||
font-size: 20px; | ||
body { | ||
margin: 0; | ||
padding: 0; | ||
font-family: "Roboto", sans-serif; | ||
background-color: #494f5c; | ||
color: #e3e3e3; | ||
font-size: 20px; | ||
} | ||
|
||
h1, | ||
.white { | ||
color: #e3e3e3; | ||
} | ||
|
||
a { | ||
color: #d6d6d6; | ||
text-decoration: none; | ||
} | ||
.navigation { | ||
position: fixed; | ||
top: 0; | ||
right: 10%; | ||
padding: 20px 0; | ||
z-index: 100; | ||
} | ||
|
||
h1,.white{ | ||
color: #e3e3e3; | ||
.nav-links { | ||
display: flex; | ||
gap: 20px; | ||
} | ||
|
||
a{ | ||
color: #d6d6d6; | ||
text-decoration: none; | ||
.nav-links a { | ||
color: #e3e3e3; | ||
font-size: 1.1rem; | ||
text-decoration: none; | ||
transition: color 0.3s; | ||
} | ||
|
||
.nav-links a:hover { | ||
color: #fff; | ||
} | ||
|
||
/* section 1 */ | ||
.section-1{ | ||
padding-top: 35vh; | ||
text-align: center; | ||
.section-1 { | ||
padding-top: 35vh; | ||
text-align: center; | ||
} | ||
|
||
.section-1 p{ | ||
font-size: 1.2rem; | ||
padding-bottom: 10px; | ||
margin:0; | ||
.section-1 p { | ||
font-size: 1.2rem; | ||
padding-bottom: 10px; | ||
margin: 0; | ||
} | ||
|
||
.section-1 h1{ | ||
font-size: 1.rem; | ||
margin-bottom: 10px; | ||
.section-1 h1 { | ||
font-size: 2.5rem; | ||
margin-bottom: 10px; | ||
} | ||
|
||
.section-1 a{ | ||
font-size: 2rem; | ||
padding: 12px; | ||
.section-1 a { | ||
font-size: 2rem; | ||
padding: 12px; | ||
} | ||
/* section 2 */ | ||
.section-2{ | ||
padding-top: 15vh; | ||
width: 90%; | ||
.section-2 { | ||
padding-top: 15vh; | ||
width: 80%; | ||
} | ||
|
||
.section-2 h2 { | ||
font-size: 1.7rem; | ||
margin-bottom: 10px; | ||
} | ||
|
||
.section-2 h2{ | ||
font-size: 1.7rem; | ||
margin-bottom: 10px; | ||
.section-2 p { | ||
font-size: 1.1rem; | ||
padding-bottom: 10px; | ||
margin: 0; | ||
color: #dadada; | ||
} | ||
|
||
.section-2 p{ | ||
font-size: 1.1rem; | ||
padding-bottom: 10px; | ||
margin:0; | ||
color: #dadada; | ||
.section-2 a { | ||
display: inline-block; | ||
padding: 5px 0; | ||
font-size: 1.2rem; | ||
margin-right: 10px; | ||
} | ||
|
||
.section-2 a{ | ||
display: block; | ||
padding: 5px; | ||
font-size: 1.2rem; | ||
padding-left: 0; | ||
width: 100px; | ||
.section-2 p a { | ||
display: inline; | ||
padding: 0; | ||
text-decoration: underline; | ||
margin-right: 0; /* Remove the right margin for inline links */ | ||
} | ||
/* animations / utilities */ | ||
.section-2 a:hover{ | ||
font-size: 1.3rem; | ||
color: #fff; | ||
cursor: pointer; | ||
transition: 0.2s; | ||
|
||
.section-2 a:hover { | ||
color: #fff; | ||
cursor: pointer; | ||
transition: 0.2s; | ||
text-shadow: 0 0 1px #fff; | ||
} | ||
|
||
.section-1 a:hover { | ||
color: #fff; | ||
cursor: pointer; | ||
transition: 0.3s; | ||
} | ||
|
||
.white:hover { | ||
position: relative; | ||
padding-left: 10px; | ||
} | ||
.content { | ||
padding: 120px 10% 50px; | ||
max-width: 800px; | ||
margin: 0 auto; | ||
} | ||
|
||
.section-1 a:hover{ | ||
color: #fff; | ||
cursor: pointer; | ||
transition: 0.3s; | ||
.writings-list { | ||
margin-top: 30px; | ||
} | ||
|
||
.white:hover{ | ||
position: relative; | ||
padding-left: 10px; | ||
.writing-link { | ||
display: block; | ||
padding: 15px 0; | ||
font-size: 1.2rem; | ||
transition: 0.2s; | ||
} | ||
|
||
.writing-link:hover { | ||
color: #fff; | ||
transform: translateX(10px); | ||
} | ||
|
||
/* media queres */ | ||
@media(max-width:768px){ | ||
.grid-2{ | ||
grid-template-columns: 1fr; | ||
} | ||
.section-1{ | ||
padding:0; | ||
padding-top: 5rem; | ||
} | ||
.section-2{ | ||
padding-top: 5%; | ||
padding-left: 12%; | ||
padding-right: 10%; | ||
max-width: 80%; | ||
margin-bottom: 10%; | ||
} | ||
} | ||
@media (max-width: 768px) { | ||
.navigation { | ||
position: static; | ||
text-align: center; | ||
padding: 20px 0; | ||
} | ||
|
||
.nav-links { | ||
justify-content: center; | ||
} | ||
.grid-2 { | ||
grid-template-columns: 1fr; | ||
} | ||
.section-1 { | ||
padding: 0; | ||
padding-top: 5rem; | ||
} | ||
.section-2 { | ||
padding-top: 5%; | ||
padding-left: 12%; | ||
padding-right: 10%; | ||
max-width: 80%; | ||
margin-bottom: 10%; | ||
} | ||
} |
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