iiinova — where your digital self keeps evolving

Reposted by Ed Hirata

Anna Foix @afoix.bsky.social · 14/06/2026

We work hard but also we have a lot of fun together @albertdm.bsky.social @edhirata.bsky.social #dljanelia2026

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Reposted by Ed Hirata

Albert Dominguez Mantes @albertdm.bsky.social · 15/01/2026

Last call! This is a great opportunity for those interested in learning and applying SOTA ML/DL models to microscopy data with the leading experts in the field. Personally super excited to be a lead TA along with the amazing @afoix.bsky.social and @edhirata.bsky.social! Hope to see you there :)

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Reposted by Ed Hirata

Biohub @biohub.org · 05/01/2026

WaveOrder is a powerful new #microscopy tool from Biohub that helps researchers reconstruct messy microscope data into clean, quantitative maps. It’s grounded in physics & it’s already changing how we see biology. 📚 Preprint bit.ly/4jgDJLB 🔬WaveOrder: czi.co/4pMwGgb

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Reposted by Ed Hirata

Jan Funke @janfunkey.bsky.social · 17/11/2025

We moved the AI@MBL course "Deep Learning for Microscopy Image Analysis" to HHMI Janelia (@hhmijanelia.bsky.social). Join us for two weeks of intense lectures, exercise, and hands-on project work! Course dates: June 4-18 2026 Application by: January 15 2026 www.janelia.org/you-janelia/...

janelia.org

Deep Learning for Microscopy Image Analysis

Topics The following will be covered extensively during lectures, exercises, and project work: Image denoising and restoration (fully supervised and self-supervised) Image translation (e.g.,

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Ed Hirata @edhirata.bsky.social · 07/11/2025

📢 Apply now for the first DL@Janelia Bootcamp (June 4–18, 2026)! 2 weeks of hands-on deep learning for microscopy: train models on your own data, Python needed (no ML experience), housing + meals included, no registration fee 📍 Janelia Research Campus, VA 🗓️ Apply by Jan 15, 2026 🔗 shorturl.at/j4sgY

shorturl.at

Deep Learning for Microscopy Image Analysis

Topics The following will be covered extensively during lectures, exercises, and project work: Image denoising and restoration (fully supervised and self-supervised) Image translation (e.g.,

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Reposted by Ed Hirata

Anna Foix @afoix.bsky.social · 06/11/2025

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Reposted by Ed Hirata

Anna Foix @afoix.bsky.social · 17/10/2025

We’ve upgraded ShapeEmbed 🎉 ShapeEmbedLite decodes latent codes via an MLP to guarantee valid EDMs, making it lighter and ideal for small microscopy datasets or limited compute. Hear more at my BIC workshop talk or poster at #ICCV2025! Try it out at github.com/uhlmanngroup...

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Reposted by Ed Hirata

Gal Haspel @galhaspel.bsky.social · 15/08/2025

Finally, a fun collaboration published in Optica: opg.optica.org/optica/fullt... Fun times at the @mblscience.bsky.social , playing with optical toys with @edhirata.bsky.social and others :)

opg.optica.org

Optica Publishing Group

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Reposted by Ed Hirata

Ed Hirata @edhirata.bsky.social · 06/07/2025

Excited to share an update on #DynaCLR—a self-supervised method to learn dynamic cell & organelle embeddings from time-lapse microscopy using contrastive learning. DynaCLR combines single-cell tracking & time-aware sampling for robust representations. arxiv.org/abs/2410.11281

arxiv.org

DynaCLR: Contrastive Learning of Cellular Dynamics with Temporal Regularization

We report DynaCLR, a self-supervised method for embedding cell and organelle Dynamics via Contrastive Learning of Representations of time-lapse images. DynaCLR integrates single-cell tracking and time...

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Ed Hirata @edhirata.bsky.social · 06/07/2025

Grateful to our incredible collaborators! This work wouldn’t have been possible without the deep interdisciplinary collaboration across CZ Biohub teams. These fast iterations and bold ideas are only possible because of you! 🙏 #CZBiohub @czbiohub.bsky.social #science #CellBiology #AI #microscopy

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Ed Hirata @edhirata.bsky.social · 06/07/2025

We provide a: - PyTorch code for training & inference: github.com/mehta-lab/Vi... - A GUI to visualize trajectories in real and embedding space - Tools for efficient human-in-the-loop annotation

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Ed Hirata @edhirata.bsky.social · 06/07/2025

DynaCLR’s temporally consistent embeddings enable in silico synchronization of asynchronous dynamics like infection & mitosis, along with organelle responses, enabling pseudotime estimation across multiple imaging channels. 5/⏳

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Ed Hirata @edhirata.bsky.social · 06/07/2025

We introduce a strategy to accelerate label-free cell state analysis: cross-modal knowledge distillation transfers labels from easy-to-annotate fluorescence sensors to unlabeled phase images, unlocking multi-state measurements from label-free data. 4/🧑‍🏫

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Ed Hirata @edhirata.bsky.social · 06/07/2025

DynaCLR embeddings enable efficient classification of cell states, including mitosis and viral infection, with a few thousand point annotations of cell state, which speeds up measurement of complex cell state dynamics. 3/🦠

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Ed Hirata @edhirata.bsky.social · 06/07/2025

DynaCLR learns embeddings from 3D multi-channel movies and enables: 1) cell state classification 2) fluorescence-to-label-free label transfer 3) alignment of dynamics. This update adds knowledge distillation and temporal alignment for even richer analysis. 2/🔬

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Ed Hirata @edhirata.bsky.social · 06/07/2025

arxiv.org

DynaCLR: Contrastive Learning of Cellular Dynamics with Temporal Regularization

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Ed Hirata @edhirata.bsky.social · 25/03/2025

We're looking for a software engineer (recent grad BS/MS) excited to build and deploy high-performance tools for dynamic imaging of cells, tissues, and organs 🐟🦠🔬 — think terabytes of image data, cell phenotyping, and high-throughput microscopy. job-boards.greenhouse.io/chanzuckerbe...

job-boards.greenhouse.io

Software Engineer, Computational Microscopy Platform (Biohub SF)

San Francisco, California, United States

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