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Tal Daniel
@TalDaniel8
Postdoc @ CMU Robotics Institute Ph.D. from the Technion ECE Research interests include self-supervsied learning, generative modeling, RL, robotics.
taldatech.github.io
Joined November 2019
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    Tal Daniel
    @TalDaniel8
    Mar 6
    🚀 #ICLR2026 Oral 💥 How can we design world models that capture object interactions directly from pixels? Introducing Latent Particle World Models-the first end-to-end self-supervised, object-centric world model, trained from videos, supporting action/img/lang conditioning. 1/n
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    Tal Daniel
    @TalDaniel8
    Jun 24
    Self-supervised object-centric learning goes 3D! Get KP, BB and segmentations directly in 3D with 0 annotaions, super useful for robotic manipulation! Amazing work by @EllinaZhang (she will be at #ICML2026 in-person)!
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    Ellina Zhang
    @EllinaZhang
    Jun 24
    🧩 #ICML2026 💥 How can a model discover the 3D objects in a scene—their shape, color, and position—without any labels? Introducing 3D-DLP, a self-supervised object-centric model that decomposes colored 3D scenes (RGB-D and voxels) into a set of 3D latent particles.
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    Tal Daniel
    @TalDaniel8
    Jun 16
    Object-centric representations for tactile data! And for a good cause! Great work!
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    Zohar Rimon
    @ZoharRimon
    Jun 16
    Excited to present the first-ever 3D, generalizable, handheld tactile imaging system! 👇 Our system learns to visualize the inner structure of soft objects purely through touch - "More with LESS: Local Scene Representation for Tactile Imaging," has been accepted to #RSS2026 🇦🇺
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    Tal Daniel
    @TalDaniel8
    Apr 22
    I’m attending #ICLR2026 in Rio this week to present LPWM! Friday April 24 Poster Session 3 10:30, Oral Session 4B 3:15p. Happy to chat about self-sup object-centric learning and world models. I’ll be on the job market soon and looking for exciting opportunities! #ICLR @iclr_conf
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    Tal Daniel
    @TalDaniel8
    Mar 6
    🚀 #ICLR2026 Oral 💥 How can we design world models that capture object interactions directly from pixels? Introducing Latent Particle World Models-the first end-to-end self-supervised, object-centric world model, trained from videos, supporting action/img/lang conditioning. 1/n
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