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Alex Kalinin

@alxndrkalinin.bsky.social
273 followers 259 following 33 posts

AI x Bioimaging @biohub.org | prev Broad Institute, CUHK-SZ & UMich

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Reposted by Alex Kalinin
Loïc A. Royer 💻🔬🧪 @loicaroyer.bsky.social · 29/06/2026
1/ 🧬🔬 How does one cell become an entire animal? We can now film it in 3D 🐟, but turning those movies into accurate cell tracks is brutally hard. Enter our new #Kaggle challenge: $60K prize pool, to help crack 3D+time cell tracking at scale! 🧵👇 www.kaggle.com/competitions... @biohub.org
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Anna Foix @afoix.bsky.social · 15/06/2026
BIC @eccv.bsky.social 2026 is OPEN! Show us your new CV, AI & Bio work🦠🔬 🚪: openreview.net/group?id=the... Thanks organisers for making it possible @alex-krull.bsky.social Peter Bajcsy @janfunkey.bsky.social @florianjug.bsky.social Qingjie Meng @virginieuhlmann.bsky.social @maweigert.bsky.social ✨
openreview.net
ECCV 2026 Workshop BIC
Welcome to the OpenReview homepage for ECCV 2026 Workshop BIC
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Beth Cimini 🔬💻📊 @bethcimini.bsky.social · 07/05/2026
The Cimini lab is hiring for both postdocs and interns! The postdoc role will cover bioimage analysis projects and educational material creation; the intern will be working on our Bilayers project for helping distribute and access deep learning tools for bioimage analysis. Click below to learn more!
forum.image.sc
Postdoctoral Associate and Data Science Intern roles - Broad Institute, Cambridge MA USA
The Broad Institute Imaging Platform (the team behind CellProfiler, Piximi, and Bilayers) is currently hiring for postdoctoral and intern roles! Postdoc role: we are looking for 1-2 candidates who ha...
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Loïc A. Royer 💻🔬🧪 @loicaroyer.bsky.social · 24/03/2026
1/ 🚀 Excited to release: napari-mcp - agentic control of napari from any MCP-capable AI assistant! Use it for interactive image processing, analysis, and visualisation! Really cool project from @ilan-theodoro.bsky.social from my team! #napari #bioimageanalysis #MCP @biohub
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Florian Jug @florianjug.bsky.social · 28/12/2025
🚨 Alarm!!! 🚨 AI/ML course for microscopy image analysis!!! 🧐 In 2026 at Janelia (@hhmijanelia.bsky.social), no tuition, housing and meals provided! Isn’t that borderline unbelievable?!? 20 students, ~14 TAs and lecturers 🗓️ June 4-18 2026 ✍️ Jan 15 2026 ✍️ 🔁 pls!! 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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EMBL-EBI @ebi.embl.org · 18/12/2025
The new ShapeEmbed deep learning method helps quantify shapes in bioimages 🔬 It learns to encode 2D object outlines into descriptors that are invariant to several geometric transformations. Great for robust cell shape analysis, classification & exploring phenotypes. neurips.cc/virtual/2025...
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Alex Kalinin @alxndrkalinin.bsky.social · 04/12/2025
Excited to be in sunny San Diego for #NeurIPS2025 🌴 Biohub @czbiohub.bsky.social has a booth! Stop by to see cool demos from our computational imaging group and chat about AI for bioimaging.
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Kevin Dean @kevin-dean.bsky.social · 11/11/2025
A game changer in our hands... www.nature.com/articles/s41...
nature.com
Universal consensus 3D segmentation of cells from 2D segmented stacks - Nature Methods
u-Segment3D is a universal framework that translates and enhances 2D instance segmentations to a 3D consensus instance segmentation without training data. It performs well across diverse datasets, inc...
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Rita Strack @ritastrack.bsky.social · 06/11/2025
Janelia is hosting a course on DL for bioimage analysis 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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Alex Kalinin @alxndrkalinin.bsky.social · 31/10/2025
Today is the last chance to register for #CytoData2025. Don’t miss a fantastic program covering the full spectrum of image-based profiling! cytodata25.eu-openscreen.eu
cytodata25.eu-openscreen.eu
Cytodata
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Alex Kalinin @alxndrkalinin.bsky.social · 23/10/2025
💡Just presented our new paper at the @iccv.bsky.social BioImage Computing workshop: cubic: CUDA-accelerated 3D Bioimage Computing. We introduce a simple way to add GPU acceleration to scikit-image–based bioimage processing pipelines by swapping import statements. 🧵 1/6 #iccv2025
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ilastik-team.bsky.social @ilastik-team.bsky.social · 09/10/2025
Segment large images without tiling artifacts: sharing our work that should have been presented at ICCV in 2 weeks - the brilliant first author Elena can’t go because of visa issues. The paper: arxiv.org/abs/2503.19545 1/🧵
Large images have to be broken into tiles both for training and inference with neural networks. The tile predictions then need to be merged to produce the final volume prediction.
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Niranj Chandrasekaran @niranjchandrasekaran.com · 07/08/2025
Morph Map is now published in Nature Methods. Excited to see what the community discovers with this resource mapping ~15,000 human genes! rdcu.be/ezGre
rdcu.be
Morphological map of under- and overexpression of genes in human cells
Nature Methods - This Resource presents the genetic subset of the 136,000 chemical and genetic perturbations tested by the Joint Undertaking for Morphological Profiling (JUMP) Cell Painting...
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Eric Topol @erictopol.bsky.social · 10/09/2025
Today @nature.com www.nature.com/articles/d41...
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Alex Kalinin @alxndrkalinin.bsky.social · 10/07/2025
🔬🤖 Introducing Spotlight: virtual staining (VS) improved by focusing on cells VS models often learn to predict both cells and noisy background, because training treats all pixels equally. We address this by explicitly training models to prioritize foreground. 1/5
Figure 1:A schematic overview of Spotlight. a: Typical virtual staining models are trained using a pixel-wise loss such as mean squared error (MSE) on the whole image. b: Spotlight uses foreground estimation obtained by histogram thresholding to restrict pixel-wise loss to foreground areas and also employs soft-thresholding of the prediction to compute segmentation loss.
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Alex Kalinin @alxndrkalinin.bsky.social · 08/07/2025
🔬API-first feature extraction for image-based profiling workflows If you need to obtain interpretable features from your segmented microscopy images, but want to do it in a fully automated way, we know the struggle. 1/6
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Anne Carpenter @drannecarpenter.bsky.social · 02/07/2025
If you’re interested in single cell data analysis, come give Image based profiles a try! Huge dataset being made available for exploration at this hackathon (+ symposium): Berlin, November cytodata25.eu-openscreen.eu
cytodata25.eu-openscreen.eu
Cytodata
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AI4Life @ai4life.bsky.social · 27/06/2025
The 2nd AI4Life Challenge is live! Calling the AI & bioimaging community to tackle a key microscopy challenge: removing noise while preserving detail. 📦 Paired noisy/clean datasets 📈 Ground-truth evaluation 🧠 DL focus Build, test, compete 👉 ai4life.eurobioimaging.eu/challenge-2/
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Alex Kalinin @alxndrkalinin.bsky.social · 23/06/2025
There is still time to submit an abstract to CytoData 2025!
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Alexander Krull @handle.invalid · 10/06/2025
The submission for 2025's BioImage Computing @iccv.bsky.social is now open. If things go like the last years, I am looking forward to all you brilliant submissions. www.bioimagecomputing.com
bioimagecomputing.com
BioImage Computing
a truly interdisciplinary workshop
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Alex Kalinin @alxndrkalinin.bsky.social · 10/06/2025
🚨 New paper alert! We developed a versatile information retrieval framework that uses mean average precision (mAP) to robustly quantify sample activity and similarity in large-scale profiling data. Now out ‪@natcomms.nature.com: doi.org/10.1038/s414... More in the 🧵 below: 1/7
doi.org
A versatile information retrieval framework for evaluating profile strength and similarity - Nature Communications
Profiling assays measure thousands of features to uncover biological insights but lack reliable methods for quality evaluation. Here, the authors develop a versatile information retrieval framework to...
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Walter Scheirer @wjscheirer.bsky.social · 03/06/2025
The #CVPR2025 main conference open access proceedings is up: openaccess.thecvf.com/CVPR2025 Workshop papers will be posted shortly. Stay tuned...
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Inês Cunha @inesmcunha.bsky.social · 14/05/2025
Our work “AI4CellFate: Interpretable Early Cell Fate Prediction with Generative AI” is finally out in @biorxivpreprint.bsky.social !!! 😍❤️ biorxiv.org/content/10.1... @scilifelab.se , @crick.ac.uk . More about it in the thread #AI4CellFate (1/n)⬇️
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Sam Berry @sberry.bsky.social · 13/05/2025
Lovely article from our colleague Kseniia Petrova, who has been wrongfully imprisoned for months: www.nytimes.com/2025/05/13/o...
nytimes.com
Opinion | The Science I Would Be Doing if I Weren’t in ICE Detention
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Alex Kalinin @alxndrkalinin.bsky.social · 06/05/2025
CytoData is going to Berlin this November! Submit an abstract for oral presentation by June 25, 2025.
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Alex Kalinin @alxndrkalinin.bsky.social · 05/05/2025
Turns out Transformers do outperform Cellpose when trained by Marius and Carsen 😄 Super exiting to see this being released and can't wait to try it out on our data!
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cytodata.bsky.social @cytodata.bsky.social · 09/04/2025
🌟 Call for Proposals: Host CytoData 2026! 🌟 We invite North American institutions to submit proposals for the 2026 symposium, whether in-person or hybrid. Nominate your institution by September 1, 2025. Join us in shaping the future of image-based profiling! docs.google.com/forms/d/e/1F...
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cytodata.bsky.social @cytodata.bsky.social · 31/03/2025
👋 We are CytoData Society (CytoDS)! 🌟 We build and maintain an active community around image-based profiling of biological phenotypes induced by genetic, chemical, or other perturbations of biological systems. Join us to explore, share, and innovate together! #CytoData #Community
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psteinb.bsky.social @psteinb.bsky.social · 31/03/2025
Great to see that many noise2void inspired denoising algorithms have been ported to @pytorch.org! Kudos to @florianjug.bsky.social and many others ... github.com/CAREamics/ca...
github.com
GitHub - CAREamics/careamics: A deep-learning library for denoising images using Noise2Void and friends (CARE, PN2V, HDN etc.), with a focus on user-experience and documentation.)
A deep-learning library for denoising images using Noise2Void and friends (CARE, PN2V, HDN etc.), with a focus on user-experience and documentation.) - CAREamics/careamics
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Simon F. Nørrelykke @simonfn.bsky.social · 24/03/2025
This summer, we are running a one-week intensive workshop on Python-based BioImage Analysis. Are there better ways to spend 6 days in mid-July in Boston?Probably. Would you learn as much as you will here? Probably not. Apply here: iac.hms.harvard.edu/bobiac/2025
iac.hms.harvard.edu
BoBiAC | 2025
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Magdalena Skipper @magdalenaskipper.bsky.social · 25/02/2025
Inexplicably, US administration has launched an unprecedented assault on science, on research institutions & on vital international organizations & initiatives. An assault on science anywhere is an assault on science everywhere; the global community must unite 🧪 www.nature.com/articles/d41...
nature.com
Trump 2.0: an assault on science anywhere is an assault on science everywhere
US President Donald Trump is taking a wrecking ball to science and to international institutions. The global research community must take a stand against these attacks.
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Janelia Research Campus @hhmijanelia.bsky.social · 05/02/2025
📢 Submissions are now open for the CellMap Segmentation Challenge. Build the best method for segmenting cellular organelles in vEM using our 289 annotated volumes, 40 organelle classes, and 22 diverse cell and tissue types. 🔗 hhmi.news/410evJQ
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Ben Recht @beenwrekt.bsky.social · 05/02/2025
As the aughties fade into history, let's recount the many lessons of the first leaderboard competition: The Netflix Prize.
argmin.net
Prediction Games
The Netflix Prize and the structure of machine learning competition
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Ben Recht @beenwrekt.bsky.social · 31/01/2025
Many still believe in overfitting. Here’s a post trying to pin down what they mean and reach some common ground. www.argmin.net/p/flavors-of...
argmin.net
Flavors of overfitting
Contextual overfitting and the Soviet Tank Problem
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Ben Recht @beenwrekt.bsky.social · 30/01/2025
Overfitting, as it is colloquially described in data science and machine learning, doesn’t exist. www.argmin.net/p/thou-shalt...
argmin.net
Thou Shalt Not Overfit
Venting my spleen about the persistent inanity about overfitting.
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Melanie Mitchell @melaniemitchell.bsky.social · 30/01/2025
Very good (technical) explainer answering "How has DeepSeek improved the Transformer architecture?". Aimed at readers already familiar with Transformers. epoch.ai/gradient-upd...
epoch.ai
How has DeepSeek improved the Transformer architecture?
This Gradient Updates issue goes over the major changes that went into DeepSeek’s most recent model.
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Jay Alammar @jayalammar.bsky.social · 27/01/2025
The Illustrated DeepSeek-R1 Spent the weekend reading the paper and sorting through the intuitions. Here's a visual guide and the main intuitions to understand the model and the process that created it. newsletter.languagemodels.co/p/the-illust...
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Giovanni Volpe @giovannivolpe.bsky.social · 25/01/2025
Excited to announce the publication of "Diffusion models for super-resolution microscopy" in JPhysPhoton! Work led by @harshithb.bsky.social with a step-by-step guide to building diffusion models to transform microscopy images from low- to high-resolution. iopscience.iop.org/article/10.1...
iopscience.iop.org
Diffusion models for super-resolution microscopy: a tutorial - IOPscienceSearch
Diffusion models for super-resolution microscopy: a tutorial, Bachimanchi, Harshith, Volpe, Giovanni
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Inês Cunha @inesmcunha.bsky.social · 02/01/2025
And to start 2025 strong… Our work #NanoPyx is out in Nature Methods 😍❤️ DOI: doi.org/10.1038/s415... #NanoPyx is a Python framework that uses the #LiquidEngine to efficiently accelerate bioimage analysis for any user! (1/n) ⬇️
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ayakimovich.bsky.social @ayakimovich.bsky.social · 30/12/2024
Happy to share our last contribution for this year! As it turns out a spoonful of physics helps mitigate hallucinations in computational super-resolution microscopy achieved through gen #AI www.nature.com/articles/s44... @hzdr.bsky.social @mdc-berlin.bsky.social
nature.com
Microscopy image reconstruction with physics-informed denoising diffusion probabilistic model - Communications Engineering
Rui Li, Gabriel della Maggiora and co-authors present a deep learning approach for attenuating diffraction and optical imperfections in light microscopy images. By incorporating the underlying physics...
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Shantanu Singh @shantanu-singh.cc · 19/12/2024
Taking pictures of cells with a microscope, then extracting thousands of features from them is uncannily effective for quantifying cell state, esp. for genes and chemicals (e.g., Cell Painting). But we often average the rich single-cell data to simplify analysis. Can we do better? #bioML 🧪 1/n
(a) Human U2OS cells treated with dimethyl sulfoxide (DMSO) and stained using the Cell Painting assay, which employs six dyes in five channels to label eight cellular compartments. The top row (from left to right) shows mitochondrial staining; actin, Golgi, and plasma membrane staining; and nucleolar and cytoplasmic RNA staining. The bottom row (from left to right) displays endoplasmic reticulum staining, DNA staining, and a montage of all five channels (from Cimini et al. [21]). (b) Thousands of features are extracted from each segmented cell in microscopy images of wells. A learned function f(x) (CytoSummaryNet) aggregates this data into a single feature vector: the sample’s profile. (c) An in-depth look at the model architecture used in this study. The model consists of three elements: a function φ(x), which maps the input data from ℝD to ℝL space, a summation, which collapses the cell dimension, and ρ(z), which maps the collapsed representation from ℝN to ℝL space. (d) During training, replicate compound profiles are forced to attract each other (green arrows) and simultaneously repel every other compound (red arrows) in the learned feature space. Here, all forces are drawn for a single profile of compound B.
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Anne Carpenter @drannecarpenter.bsky.social · 18/12/2024
We've a postdoc opening for our lab at the Broad: Cambridge MA! Must have experience in toxicology + data science Work on the wonderful OASIS dataset we are producing... Cell Painting, transcriptomics, proteomics in various liver cell and tissue models! broad.io/mlcbpostdoc
Image of the job posting (see URL for full text instead)
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Beth Cimini 🔬💻📊 @bethcimini.bsky.social · 16/12/2024
New Year, new job? Delighted to announce two early-career-level (post-BA/BS or MA) positions in my lab, and an open call for computational postdocs at the Broad! First, an image analysis associate - work on high content screens for all kinds of cells and dimensionalities! See more at link (1/4)
docs.google.com
Image analysis associate job description
Image Analysis Associate Broad Institute of MIT and Harvard, Cambridge, MA Impact the discovery of new disease therapies in the Cimini laboratory at the Imaging Platform Join our vibrant, world-clas...
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John Arevalo @johnarevalo.bsky.social · 13/12/2024
Excited to present our spotlight paper at #NeurIPS! MOTIVE is a new dataset + benchmark for predicting drug-target interactions, using Cell Painting data Location: Fri 13 Dec 4:30 p.m. PST @ East Exhibit Hall A-C #4208 Poster: neurips.cc/virtual/2024... Paper: arxiv.org/abs/2406.08649
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Jess Ewald @ewaldlab.org · 13/12/2024
🎉 I'm starting my own lab at EMBL-EBI (Cambridge, UK; June 2025) 🎉 We will focus on identifying and characterizing chemical hazards to humans and ecosystems using computational biology methods. I am beginning the search for two postdocs now - stay tuned for more details! ewaldlab.org
ewaldlab.org
Ewald Lab
@ EMBL-EBI. We identify and characterize chemical hazards to both humans and ecosystems with cell profiling data, machine learning, and integrative data analysis.
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Tanishq Mathew Abraham @iscienceluvr.bsky.social · 10/12/2024
Inventors of flow matching have released a comprehensive guide going over the math & code of flow matching! Also covers variants like non-Euclidean & discrete flow matching. A PyTorch library is also released with this guide! This looks like a very good read! 🔥 arxiv: arxiv.org/abs/2412.06264
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FocalPlane @focalplane.bsky.social · 29/11/2024
Our preprint list is now up on FocalPlane. This week we focus on research in #bioimageanalysis. Drop us a message if we’re missing any preprints that you’ve been reading or writing! focalplane.biologists.com/2024/11/29/m...
focalplane.biologists.com
Microscopy preprints - bioimage analysis - FocalPlane
Microscopy preprints - bioimage analysis - Discussions
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Beth Cimini 🔬💻📊 @bethcimini.bsky.social · 06/11/2024
Made a starter pack for microscopy and image analysis - please (self-)nominate additions! go.bsky.app/Nwa91pC
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Srijit Seal 🇺🇸🇬🇧🇩🇪🇯🇵🇮🇳 @srijitseal.com · 05/12/2024
We’re thrilled to share our Nature Methods review on #CellPainting — your go-to resource for mastering Cell Painting! From MOA and toxicity prediction to contributing to candidate drugs in clinical trials, we’ve distilled 10 years of insights!
nature.com
Cell Painting: a decade of discovery and innovation in cellular imaging - Nature Methods
This Review synthesizes the literature from over 10 years of Cell Painting for image-based profiling and highlights how advances in this technology enable new biological discovery of cellular phenotyp...
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