Praveesh Valissery

postdoc @lab_egan. enjoys creating weird cell lines. hopes to clone a t-rex. DM me if u have that amber thing with the mosquito and dino blood. I'm not joking..

[Michael @MichaelLee04]

Labeling bio images for AI just got 10x faster🏎. Today, we’re releasing Biodock Autolabel, and it’s kind of magical. We trained it on thousands of bio images so you can use it without training. (1/6)

@BiodockAI #microscopy #pathology #biology

[Marilou Tetard @MarilouTetard]

The Egan lab at #MPM2023 !

[Praveesh Valissery @prvsh_v]

Hello #MP2023 people. Come and check out Marilou’s most excellent CRISPR screen in red blood cells !! Poster no. 160.

[Russ Salakhutdinov @rsalakhu]

I get asked a lot: why stay in academia, all the excitement in AI is happening in industry with massive compute. And I am seeing some profs leaving academia, but also seeing lots of researchers in industry looking to go back to academia, especially those who don’t work on LLMs.

I have spent some time and actively working with industry, and it has been a great experience, but for me the answer is simple:

1. Students: Nothing can replace working with really smart & amazing students.

2. Academic freedom: In general, industry will one way or another dictate what you should work on. Today it is LLMs, tomorrow it is something else. The good old days of "here is a cool idea, let me investigate and publish" are pretty much over. But as an academic, I can work on whatever I want: I can start working on "black holes" tomorrow if I choose to.

3. And my favourite one: No reorgs -- big tech really loves reorgs that happen every few months.

Finally, as an academic, I can always take some time off, work in industry or start-up, and come back if I want to. Going into industry is usually a one-way street: It is far easier to go to industry from academia and much harder the other way around.