Yu Group at Carnegie Mellon University. Neuroscience, brain-computer interfaces, machine learning
Joined February 2021
- Tweets 108
- Following 9
- Followers 2,785
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32 Photos and videos
Pinned Tweet
May 12
If you have a background in neural technologies or related disciplines, and are enthusiastic about teaching, we encourage you to apply here:
apply.interfolio.com/184248
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May 12
We (CMU Biomedical Engineering and Neuroscience Institute) are seeking to hire a new teaching-track faculty member for our new joint MS program in Neural Technologies (MiNT).
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May 12
If you have a background in neural technologies or related disciplines, and are enthusiastic about teaching, we encourage you to apply here:
apply.interfolio.com/184248
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18 Feb 2025
We are excited to share our work on dynamical constraints on neural population activity, published as a cover article in @NatureNeuro. It was led by Emily Oby, @AlanDegenhart, @ErinnGrigsby, with @aaronbatista and team.
nature.com/articles/s41593-0…
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18 Feb 2025
Thank you to @neuroamyo for a wonderful News & Views piece:
nature.com/articles/s41593-0…
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Byron Yu retweeted
17 Feb 2025
📣 The 11th Statistical Analysis of Neuronal Data (SAND11) workshop will be held June 11-13, 2025 in New York at the @FlatironInst with generous support from @SimonsFdn!
Submissions for talks posters are due March 21. See our website for details 👇
sandworkshop.github.io
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21 Jan 2025
We've posted a new paper about how to speed up statistical methods for analyzing multi-area recordings by orders of magnitude:
arxiv.org/abs/2412.16773
This work was led by Evren Gokcen, with Anna Jasper (Einstein), Adam Kohn (Einstein), and Christian Machens (Champalimaud).
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Byron Yu retweeted
17 Jan 2025
Transformative work happens through collaboration. New research from @CMUEngineering & @PittEngineering validates principles that researchers have brought out in neural network models for decades. @YuLikeNeuro @cmu_bme
engineering.cmu.edu/news-eve…
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Byron Yu retweeted
17 Jan 2025
Using a brain–computer interface to challenge monkeys to override their natural time courses of neural activity reveals that the time courses are highly robust, suggestive of network-level computational mechanisms
@aaronbatista @YuLikeNeuro @AlanDegenhart @ErinnGrigsb
nature.com/articles/s41593-0…
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Byron Yu retweeted
5 Dec 2024
I'm excited to share our #NeurIPS2024 paper with
@jsoldadomagrane @SmithLabNeuro @YuLikeNeuro!
We develop a new brain stimulation framework (MiSO) to drive neural population activity toward specified states.
Paper: openreview.net/pdf?id=Gb0mXh…
Poster Session 4 East, Dec 12 16:30
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30 Sep 2024
We are excited to share our new method, SNOPS (Spiking Network Optimization using Population Statistics), published in
@NatComputSci. It was led by @Shenghao_W, with @cc_huang11, Adam Snyder, @SmithLabNeuro, and @BrentDoiron.
nature.com/articles/s43588-0…
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30 Sep 2024
SNOPS can also identify specific combinations of activity statistics that the model cannot reproduce, thereby guiding model development.
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