Michelle Greene @mgreenephd.bsky.social · 28/09/2026Experiencing this at all stages of the publication pipeline: * As an editor who asks 25+ people before securing two peer reviewers. * As a reviewer fielding 7-10 new requests per week. * An an author who has waited ~4 months for reviewers. AI is DDOS on actual scientific progress. 0100
Michelle Greene @mgreenephd.bsky.social · 25/09/2026Critically, height predicted observers' performance in a rapid categorization task: shorter observers performed better for faces in the upper visual field, while taller observers were better in the lower, consistent with their lived experience of faces. 5/ 2164
Michelle Greene @mgreenephd.bsky.social · 25/09/2026Fixations compensate for this, with the effect even slightly reversing for faces. 4/ 110
Michelle Greene @mgreenephd.bsky.social · 25/09/2026When we consider all faces and hands (fixated and not) in one's view, we see that taller individuals see faces lower in the visual field, and hands higher. This is consistent with shorter folks looking up at faces. 3/ 110
Michelle Greene @mgreenephd.bsky.social · 25/09/2026In this picture, two observers of different heights are walking in the same place. When creating the Visual Experience Dataset, I was often struck by how different one's experience of the same place could be. 2/ 150
Michelle Greene @mgreenephd.bsky.social · 25/09/2026Fixations compensate for this, with the effect even slightly reversing for faces. 4/ 000
Michelle Greene @mgreenephd.bsky.social · 25/09/2026When we consider all faces and hands (fixated and not) in one's view, we see that taller individuals see faces lower in the visual field, and hands higher. 3/ 100
Michelle Greene @mgreenephd.bsky.social · 25/09/2026In this picture, two observers of different heights are walking in the same place. When creating the Visual Experience Dataset, I was often struck by how different one's experience of the same place could be. 2/ 100
Michelle Greene @mgreenephd.bsky.social · 13/05/2026Excited for #VSS2026! Please come check out the work of my lab and our friends. A 🧵. 1/ 2140
Michelle Greene @mgreenephd.bsky.social · 12/04/2026It’s a shame that my students’ generation doesn’t know the joy of getting to the stage of friendship when you’re allowed to flip through your buddy’s music collection and bond over the obscure and/or cringe music you both love. 160
Michelle Greene @mgreenephd.bsky.social · 24/03/2026Yeah, the world is a dumpster fire right now. But the feeling of celebrating students’ first paper submission? Still magical! 2170
Michelle Greene @mgreenephd.bsky.social · 18/02/2026She and Rev Bayes should throw themselves a pity party! 100
Michelle Greene @mgreenephd.bsky.social · 09/02/2026Becoming a True New Yorker (TM) by bringing some truly unhinged object on the subway. 370
Michelle Greene @mgreenephd.bsky.social · 05/02/2026Definitely the raddest hotel view at a conference I’ve had! 0110
Michelle Greene @mgreenephd.bsky.social · 03/01/2026Looks like another good day to start screaming in the streets. 091
Michelle Greene @mgreenephd.bsky.social · 24/12/2025Interestingly, these metrics are not strongly correlated! 4/ 110
Michelle Greene @mgreenephd.bsky.social · 10/12/2025Happy #VSS submission day to all who celebrate! So proud of this crew (and friends!) pulling off six abstracts! See y’all in Florida! #VisionScience 0180
Michelle Greene @mgreenephd.bsky.social · 09/10/2025Another flight, another dude who feels entitled to my legroom. 🙄 351
Michelle Greene @mgreenephd.bsky.social · 01/10/2025Heading to the Bronx. Betting hard on the idea that they won’t throw punches at a middle aged professor. 040
Michelle Greene @mgreenephd.bsky.social · 29/09/2025My favorite subway graffiti right now is anti-friend hot takes. 0162
Michelle Greene @mgreenephd.bsky.social · 29/09/2025Sure. Here's Spring 2025. The first column is the project name, subsequent columns are goals for each month, color-coded by task type (data collection, analysis, dissemination, etc.) 150
Michelle Greene @mgreenephd.bsky.social · 12/08/2025Really excited for #CCN2025! Come see our poster (A58). We asked people to describe the same pictures with different task instructions and trained a CNN to learn these sentence embeddings. Both networks learned task-relevant visual features that humans also needed for the same tasks! 0121
Michelle Greene @mgreenephd.bsky.social · 08/07/2025Experiment 1 used @martinhebart.bsky.social's odd-one-out triplet task, but with a twist: each pair within a triplet was selected to be an outlier in one of three feature spaces: ✅ Affordances ✅ Surfaces ✅ Materials People picked the affordance outlier as being the most different most often. (3/7) 110
Michelle Greene @mgreenephd.bsky.social · 28/06/2025Heading to the NYC Dyke March! Who else is going? 070
Michelle Greene @mgreenephd.bsky.social · 18/05/2025Come chat with Carina about scene-word EEG decoding! #VSS2025 030
Michelle Greene @mgreenephd.bsky.social · 18/05/2025Come chat with Carina about object-word EEG cross decoding, now in Banyan. 021
Michelle Greene @mgreenephd.bsky.social · 16/05/2025And Amy and Vivian will present on EEG decoding of visual and semantic scene information. 5/5 040
Michelle Greene @mgreenephd.bsky.social · 16/05/2025Skylar used an SSVEP "sweep" paradigm to examine the information accumulation of visual and semantic information. 4/5 120
Michelle Greene @mgreenephd.bsky.social · 16/05/2025Our other posters will be on Tuesday afternoon (pregame for Club Vision with us). Sage and Hooriya will present some interesting double dissociations between detection and categorization for two types of complexity, visual and semantic. 3/5 120
Michelle Greene @mgreenephd.bsky.social · 16/05/2025Carina will present Sunday in the Undergraduate Just in Time session. Her work considers the neural correlates of word-picture congruence in scene recognition. 2/5 100
Michelle Greene @mgreenephd.bsky.social · 30/04/2025I have no idea what’s going on in this chaotic discarded painting, but I’ve never felt more seen. 040
Michelle Greene @mgreenephd.bsky.social · 05/04/2025Amazing turnout for #handsoff NYC. The second photo is the crowd waiting to start marching after I had "salmoned" back to the start. Wall to wall to wall from 40th to 25th! 0100
Michelle Greene @mgreenephd.bsky.social · 05/04/2025Exit to *exit* the subway 30 minutes before #handsoff starts. Good job, NYC! 092
Michelle Greene @mgreenephd.bsky.social · 29/03/2025Portrait of the artist in college at a protest against G.W. Bush's appearance on campus. My sign (not pictured) read "L.A.B.I.A.: Lesbians Against Bush's Idiotic Administration. Read our lips". Thinking a lot about how my students don't have the same freedom to be young & opinionated. 1/3 1172
Michelle Greene @mgreenephd.bsky.social · 23/03/20255/ Even within affluent countries like the US, these biases persist. Homes from wealthier US counties were classified with higher confidence. The models implicitly equate "affluent" with "clear," "legitimate," and "recognizable." 1131
Michelle Greene @mgreenephd.bsky.social · 23/03/20252/ Here are the top five classifications from a leading CNN (Resnet-50). As you can see, not only are the images misclassified, but they're misclassified in ways that connote death, disrepair, and decay. 1162
Michelle Greene @mgreenephd.bsky.social · 23/03/2025🚨New publication alert!🚨 Our latest paper explores socioeconomic biases in AI—but this time, it's not about people directly. It's about homes. Consider these images: it's clear to us that they're all bathrooms. 1/ 49129
Michelle Greene @mgreenephd.bsky.social · 07/03/2025It was a no-good, terrible, very bad week. But I got flowers for my lab to celebrate International Women’s Day tomorrow. 0111
Michelle Greene @mgreenephd.bsky.social · 26/02/2025Feeling this extra hard in the US. View from my lab last night. 190
Michelle Greene @mgreenephd.bsky.social · 21/02/2025Back in my body after grinding on a deadline. Cold, but stunning! 080