Abhishek Divekar adivekar-utexas

Question

Hi Claude, analyze this post as a world-class expert and present the most value insights, objectively and rigorously, and explain why:

VCs and recruiters seem unaware that a NeurIPS workshop paper is not the same as a NeurIPS main conference paper.
1) Workshop = 3-4 weeks of work. 20-40% rejection rate. 
2) Main conf = 5-6 months of work. 70-80% rejection rate. Tiers are Oral > Spotlight > Poster. Oral = top 3-5% of papers, very prestigious (a few in your career). Poster/Findings is still strong research.
This applies to all A* conferences (ICLR, ICML, AAAI, CVPR, ICCV, ACL, EMNLP, etc).

Also, authorship matters.

The Situation

Suppose you've got a team of 2+ people who are working on an AI project (research, business, etc). and they need a common Jupyter machine where they can run notebooks. You have two common options:

A common JupyterLab: this has the issue that everyone uses the same UI, leading to conflicts. Example: Amazon Sagemaker Notebooks.
A JupyterHub install: this needs a bit more setup, but gives much better separation.

The rest of this post is going to discuss how to setup JupyterHub in a way that:

Everyone gets their user on the machine and their own home directory, which only they have permissions to.
No one can access any one else's home directories or files.

(Reproduced from https://mscshub.com/)

Background: I work as an ML Scientist at FAANG. I started the UT Austin MSCSO program in Fall'2020, and this review was written in Dec'2023. This review is very specific, so a motivated person can probably find me. Let me save you the trouble, here is my LinkedIn: linkedin.com/in/ardivekar/ . Feel free to reach out with questions. I'm usually also on the MSCSO Slack.

I applied for UT Austin's MSCS Thesis in Dec'2022, and completed the Thesis over 3 semesters (Spring'23 to Spring'24). My thesis was in the NLP domain, during 2023 when AI went mainstream via ChatGPT, and new LLMs were released every single week. As you can expect, this makes my experience unique. But I expect everyone's thesis experience will be unique since it depends on your personal strengths and interests.

Another thing which I did different from other students is that I framed my own research problem. This is recommended only if you're really dead-set on one idea, like I was. Otherwise it's okay t

🚨 (Update June 2025) 🚨 This little post has gained a huge amount of interest, for which I am very grateful. However, it's been overwhelming to keep up with 40-50 reachouts per week. To make things manageable, I am selectively focusing on referrals for full-time Applied Scientist and Data Scientist roles only. The rest of this post still contains tips for other tech roles (Software Engineer, Data Engineer, BIE, etc) and details on the hiring process in general; I hope these are valuable for you. Good luck on your journey!

I am always happy to provide referrals for folks applying to Amazon for a variety of roles. Amazon is a FAANG, so I know that landing a job there can make a big difference to someone's career, and I am happy to spend the time to provide a referral.

If you are interested, please read the points below very carefully before reaching out (I only accept requests via LinkedIn). This is to save time on both sides 😄 I usually check around

Submission Steps

Download source code from Overleaf if you use it: menu -> download -> source.
Strip comments and combine all tex files (f01-main.tex, f02-intro.tex, etc.) into one file arxiv_main.tex.

# Replace f01-main.tex with the main tex file in your overleaf project
latexpand --empty-comments f01-main.tex > arxiv_main.tex

	from typing import *
	import hvplot

	def plotsum(
	plots_list: Union[List[Tuple[str, Any]], List[Any]],
	*,
	order: Optional[List[str]] = None,
	how: Literal["overlay", "grid"] = "grid",
	legend: Literal["first", "last", "none"] = "none",
	update_layout: Optional[Dict] = None,

	import pandas as pd
	import hvplot
	import holoviews as hv
	import hvplot.pandas
	hvplot.extension("bokeh")
	from bokeh.themes.theme import Theme
	hv.renderer('bokeh').theme = Theme(json={
	'attrs': {
	'Figure': {
	'background_fill_color': '#2F2F2F',

	@media print {

	/* ---------- wrap long code lines ---------- */
	pre,
	/* standalone code blocks */
	code,
	/* inline snippets <code>like this</code> */
	pre code {
	/* <pre><code> … </code></pre> combos */
	white-space: pre-wrap !important;

	from typing import *
	import ctypes
	from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor

	def stop_executor(
	executor: Optional[Union[ThreadPoolExecutor, ProcessPoolExecutor]],
	force: bool = True, ## Forcefully terminate, might lead to work being lost.
	):
	if executor is not None:
	if isinstance(executor, ThreadPoolExecutor):

	"""A collection of utilities to augment the Python language:"""
	from typing import *
	import time, traceback, random, sys
	import math, gc
	from datetime import datetime
	from math import inf
	import numpy as np
	from threading import Semaphore
	import multiprocessing as mp
	from concurrent.futures._base import Future