Richard Gao

@rdgao.bsky.social

W1 (Assistant) Professor of CS & Math at Goethe University Frankfurt. AI x neuroscience. 🌊 https://www.gao-unit.com/

this paper encapsulated some of our (my) really great times in Tübingen, and it's truly about the friends you make along the way. also, I think the cool thing about this is that if you replace "timescales" with any other signature of brain activity, it still outlines a coherent research program

Roxana Zeraati@roxana-zeraati.bsky.social · 4w ago

Our paper "Neural timescales from a computational perspective" is finally out in @natneuro.nature.com: www.nature.com/articles/s41... We discuss how computational models and methods can distill empirical observations on neural timescales into quantitative, testable theories of brain computation.

it took me so damn long to write this thing that the field actually became real in the 2.5 years hooooly anyway, here's another book: 100% grass-fed human-written down to every single letter, though probably for AI consumption only at this point. www.rdgao.com/blog/2026/06...

Beyond #NeuroAI, we need #AI4Neuro—and we’re going to suck at it (at first). [Part 3]

The fundamental principle of using AI for science is that it can help us do some things extremely efficiently, but it usually requires an ‘oracle’ or verifier. I’m of the opinion that we simply don’t ...

rdgao.com

New paper out in PLOS Computational Biology! We introduce iSTTC, a robust method to estimate intrinsic neural timescales from single-unit recordings. Congrats to Irina Pochinok for leading the project! Package: github.com/iinnpp/isttc Paper: journals.plos.org/ploscompbiol...

GitHub - iinnpp/isttc: iSTTC: intrinsic neural timescales estimation

iSTTC: intrinsic neural timescales estimation. Contribute to iinnpp/isttc development by creating an account on GitHub.

github.com

For this year's Neuromatch Computation Neuroscience course, the Curriculum Team is adding a new Day 🥁🥁🥁 Time series analysis and signal processing! We're looking for 5-10 content contributors with relevant neuro+DSP experience for various tasks: co-Day Lead, video, slides, code tutorials, etc.

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Once you get past the first 5 minutes of me bumbling around clearly in need of media training, we settle into a nice groove talking about fitting mechanistic models, ML/AI for neuroscience, underconstrainedness vs. degeneracy, and its potential benefits for biology (plus some good chuckles).

Gaute Einevoll@gauteeinevoll.bsky.social · 5mo ago

Episode #38 in #TheoreticalNeurosciencePodcast: On extracting spiking network models from experiments - with Richard Gao @rdgao.bsky.social theoreticalneuroscience.no/thn38 How to fit spiking network models to experimental data when there is no unique parameter set giving the best fit.

Finally got the job ad—looking for 2 PhD students to start spring next year: www.gao-unit.com/join-us/ If comp neuro, ML, and AI4Neuro is your thing, or you just nerd out over brain recordings, apply! I'm at neurips. DM me here / on the conference app or email if you want to meet 🏖️🌮

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Just 1 week to apply! 4 year @erc.europa.eu funded PhD position working in an interdisciplinary team to study #culturalEvolution as a process of reuse, recombination, and creative re-engineering of past solutions. Details 👉 hmc-lab.com/ERCPhDCultur... 🙏Please share!

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Charley Wu@thecharleywu.bsky.social · 10mo ago

Fully-funded 4-year #PhD in Cultural Evolution! Join my @erc.europa.eu project exploring how compression & compositionality drive cultural innovation: hmc-lab.com/ERCPhDCultur... Apply by Nov 12! Maybe of interest to folks from #COSMOS2025 or @eslr.bsky.social? Please feel free to share! 🙏

Manuel Brenner and I managed to organize this workshop not knowing we were gonna end up being new neighbors this month. The lineup speaks for itself. There were some last minute cancellations so we jumped in to fill their big shoes and will talk about the future directions of the new labs too!

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