Extract value from Academic twitter
productivity researchOur power is in our tools. Twitter is a great microblogging platform and a great academic tool. Probably, you see it as some virtual water cooler where you can grab some ideas from your colleagues, but it is more than that. With proper attitude and usage it can considerably broaden your perspective of the AI terrain.
Curating your “twitter bubble” and directing it to better direction can be a good investment of time. To create your “academic bubble” you can start with a small set of top researchers in your area. And then progressively through twitter feed (where you see likes and retweets). Don’t worry if will not be able to find examples of some types of tweets in your feed right away. It might take some time.
Don’t forget to filter your feed from time to time, because not all people separate their personal and professional/academic accounts (there are pros and cons of that separation that we will not discuss here)
In this blogpost we will consider some kinds of tweets that I find useful.
- Promote and share your preprints/papers/projects
- Get new ideas/models/tools, be in the heart of events
- Conferences
- Summer schools
- Internships / Residency programs
- Post-doc / Research positions / Industry hiring
- “Peer-review” / Discussions (well if things goes serious, those tweets will just contain a link to outside posts )
- Nice every day ideas to expand your solution space
Some examples:
Job posting / Internships
Want to build infrastructure for Robots and AI instead of only focusing on web services?
— Pieter Abbeel (@pabbeel) August 28, 2019
Come join our team as our first Site Reliability Engineer!
For more information, check out our job description at https://t.co/Fw2fm67RcV
Paging all current PhD students: apps now open for NVIDIA’s 2020-21 PhD fellowship (post-1st and pre-last yr eligible)! $50k award supporting research in AI, DL, autonomous driving, etc. H/T @AlisonBLowndes, [ping @mldcmu] https://t.co/GUTQJ4zvkf
— Zachary Lipton (@zacharylipton) August 14, 2019
Share papers / projects
Code for "Learnable Triangulation of Human Pose" is released: https://t.co/GosMD32Lth. SOTA in 3D human pose estimation! #ICCV19 pic.twitter.com/NBr4vgRJ6d
— Dmitry Ulyanov (@DmitryUlyanovML) October 9, 2019
We release the largest publicly available language model: CTRL has 1.6B parameters and can be guided by control codes for style, content, and task-specific behavior. Incredible generations!
— Richard Socher (@RichardSocher) September 11, 2019
Paper https://t.co/0Wr2XiOl2V
Github https://t.co/PA8GxqtS9V
Blog https://t.co/Q2xQFtKQQE pic.twitter.com/PRidiAzJOM
This is SO meta 🤓
— Hugging Face (@huggingface) September 5, 2019
We trained a generative language model on a dataset of ArXiv NLP papers. You can now get a neural net to write your papers for (with?) you 🔥.
We heard from a few researchers that they're already using it in submitted papers.https://t.co/oK6hEHQLpz pic.twitter.com/t6T9SoEVaS
Promoting courses and gather cool ideas
Excited to announce that I am teaching a *new* course on ML interpretability and explainability at Harvard this semester. Course webpage: https://t.co/jXNJjYuWy7. Lecture slides and background materials are being uploaded as the class progresses. Lecture videos coming soon!
— Hima Lakkaraju (Recruiting Students and Postdocs) (@hima_lakkaraju) October 8, 2019
Lab events announcements
Next on our research seminar Sergey Troshin gave a talk covering the "Deep Equilibrium Models" paper (by @shaojieb)https://t.co/aLvjoiXp7H
— Bayesian Methods Research Group (@bayesgroup) October 8, 2019
Share success
NeurIPS 2019 here we come! 😍🤓 We're excited about 8 accepted papers with WhiRL members and look forward to discussing our work at @NeurIPSConf #NeurIPS2019. See you in Vancouver! Paper thread 👇👇👇
— WhiRL (@whi_rl) September 6, 2019
#NeurIPS2019 made my day today!!! 3 acceptations out of 3 submissions, from this one oral presentation, another spotlight. Plus a bonus of one free registration for my refereeing work. And invitations to 3 NeurIPS workshops. Looking forward to one hell of a week in December :)!
— Lenka Zdeborova (@zdeborova) September 3, 2019
Conferences
Applications for travel scholarships and student volunteers are now open! We also plan to offer scholarships to students and non-students with a demonstrated financial need.
— emnlp2019 (@emnlp2019) August 30, 2019
Application deadline is September 12.https://t.co/3sGwmLiRc1 pic.twitter.com/5ZEjuZw9NV
Ask for a help
Does anyone have any detailed tips, walkthrus, or tutorials on how to profile @PyTorch code running on the GPU?
— Jeremy Howard (@jeremyphoward) October 25, 2019
I'm trying to optimize efficientnet and want to see exactly where the time is spent.
Other
Episode 1
— TalkRL (@TalkRLPodcast) September 3, 2019
Lucky to chat with @natashajaques about PhD, her papers on Social Influence in Multi-Agent RL, ML & Climate Change, Sequential Social Dilemmas, internships at DeepMind and Google Brain, Autocurricula, and more! https://t.co/5Ct0UYqomT
Yes, @GoogleAI (well, all of @AlphabetINC) produces a lot of awesome AI research, but @Stanford + @MIT together produce more (judging by @NeurIPSConf papers!), and @Stanford + @MIT + @UCBerkeley + @CarnegieMellon produces more than @AlphabetINC + @Microsoft + @facebook pic.twitter.com/uocyccgXUx
— Stanford NLP Group (@stanfordnlp) September 8, 2019
Congratulations, if you made it here. To finish this post with something really usefull and more importantly actionable I’d like to propose to you a starter list for AI researchers/engineers. You can checkout complete list of my Following
.
AI starter list ))
- Yann LeCun
- Soumith Chintala created and lead PyTorch at Facebook
- Jeremy Howard Founding Researcher: http://fast.ai )
- François Chollet Creator of Keras, author of ‘Deep Learning with Python’.
- Russ Salakhutdinov Director of AI Research at Apple
- Chelsea Finn Research scientist @GoogleAI.
- Olivier Grisel Engineer at @Inria, scikit-learn developer
- Lex Fridman Researcher at MIT, Tesla
- Nando de Freitas Principal Scientist at DeepMind
- Alexander Novikov Research scientist at DeepMind
- OpenAI
- DeepMind
- Ben Poole research scientist at google brain
- BAIR
- Facebook AI
- Dmitry Ulyanov PhD student @ Skoltech
Well you get the point, there are many cool people and organizations that will be happy to share their bright observations and ideas. You can go through the list of their Following
s to find more interesting people.
In the next posts I will try to provide some twitter usage tips and tricks and introduce some other types of academic tweets.