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Dorsa Sadigh

@DorsaSadigh · Palo Alto, CA · joined 27 Feb 2014

CS Faculty @Stanford, @StanfordAILab, @StanfordHAI Research scientist @GoogleDeepMind PhD and BS from @Berkeley_EECS

12 145Followers
399Following
579Posts total
301.6KViews on collected posts

Against accounts of the same size

4 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.

Median views21 612this account2 578median for 10K–100K
Reach, %177.95%this account7.77%median for 10K–100K
Engagement, %0.38%this account1.47%median for 10K–100K
MetricThis accountMedian for 10K–100KRatio
Median views per post21 6122 5788.38×
Reach (views ÷ followers)177.95%7.77%22.9×
Engagement rate0.38%1.47%0.26×

Others in this range →   Compare with another account →   How these benchmarks are built →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

43.1K9 Jun
5.4K10 Jun
94.7K26 Nov
14K30 Nov
53K
39.1K7 Jul
13.2K9 Jul
30K14 Jul
9.1K15 Jul

Last 9 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.78%9 Jun
0.86%10 Jun
0.62%26 Nov
0.65%30 Nov
0.66%
0.26%7 Jul
0.20%9 Jul
0.49%14 Jul
0.71%15 Jul

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.47%.

What the audience does

Likes80.1%1 474 in total
Reposts10.1%186 in total
Replies3.5%64 in total
Quotes1.7%31 in total
Bookmarks4.7%86 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Latest posts

I've spent the last year post-training LLMs, and it is very exciting to see how revolutionary AI has become. But seeing the first steps for large models to directly control robots, scale data collection, and automate a large part of the robotics pipeline is another level! 9.1K views · 57 likes · 4 reposts · 3 replies 15 Jul 2026 We gave popular agents (Claude Code & Codex) a browser-based visual interface and let them command a robot via MCP tools — like a human with a mouse and keyboard — and it worked! Introducing VIA: Visual Interface Agent for Robot Control. 🧵 https://t.co/KfTVrvBhbR 30K views · 115 likes · 18 reposts · 8 replies 14 Jul 2026 exciting work by @megha_byte on proximal state nudging -- getting humans to to learn based on estimating learnability of each state. 13.2K views · 24 likes · 2 reposts · 0 replies 09 Jul 2026 New work on reducing skill atrophy from AI overreliance! As AI tools improve capabilities, how can we use them to also support a human user’s own skill development? At #ICML2026 #AI4GOOD, I’ll present Proximal State Nudging (PSN): an assistance algorithm that balances between h 39.1K views · 77 likes · 19 reposts · 3 replies 07 Jul 2026 Just realized I haven't shared life status or been on twitter for a while, so here is a status dump 🧵 1/4 53K views · 327 likes · 3 reposts · 22 replies 30 Nov 2025 Alan Turing once said "...the machine should have a chance of finding things out for itself it should be allowed to roam the countryside.." Scanford takes a step toward roaming the countryside - giving us data beyond what's on internet to improve non-robotics capabilities 🧵⬇️ 14K views · 81 likes · 8 reposts · 2 replies 30 Nov 2025 Meet Scanford 📚🤖: a robot that improves foundation models by doing useful work in the wild. Deployed for 2 weeks in the Stanford East Asia Library, Scanford scans books, helps librarians, and continually improves the VLM it relies on. 🔗 https://t.co/r2ZXyeKaIf 🧵1/8 https://t.c 94.7K views · 483 likes · 73 reposts · 17 replies 26 Nov 2025 HoMeR brings mobile manipulators out in the wild with an efficient hybrid imitation policy that uses keypoints from a VLM. This allows for generalization to unseen scenarios in particular in near-interaction settings where it is hard to decouple mobility and manipulation! 5.4K views · 42 likes · 3 reposts · 2 replies 10 Jun 2025 How can we move beyond static-arm lab setups and learn robot policies in our messy homes? We introduce HoMeR, an imitation learning agent for in-the-wild mobile manipulation. 🧵1/8 https://t.co/IvNZCtyfGk 43.1K views · 268 likes · 56 reposts · 7 replies 09 Jun 2025

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