Carlo Manzo

🎅 Santa came early this year!
Author copies of Deep Learning Crash Course📘 @nostarchpress.bsky.social
and the Ramón y Cajal insignia🇪🇸
Two milestones, one goal: sharing knowledge.
Grateful to students, collaborators, mentors, and institutions.
Excited for what’s next.
📚 nostarch.com/deep-learnin...

🌟 Our paper in the 𝐄𝐝𝐢𝐭𝐨𝐫𝐬’ 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬 𝐢𝐧 𝐍𝐚𝐭𝐮𝐫𝐞 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 🥳
🔗 www.nature.com/collections/...
Thank you to @qchengx1e3.bsky.social, to co-authors @giovannivolpe.bsky.social, Sergi Masó, Mattias Goksör, Montse Masoliver, Joan Bertran and especially to Jesús Pineda!

🚀 #PhD opening (FPI call, AEI)
Develop physics-informed #AI for single-molecule fluorescence microscopy.
Work with @qubilab.bsky.social + @giovannivolpe.bsky.social.
Start: March 2026
Deadline: Jan 7, 2026.
Contact: @cmanzo.bsky.social

Modern AI feels easier when you build each model yourself. This book shows you how.

https://nostarch.com/deep-learning-crash-course
Every print copy comes with a free Ebook!

Enhanced spatial clustering of single-molecule localizations with graph neural networks - Nature Communications Single-molecule localisation microscopy enables nanoscale mapping of molecular organisation, but clustering stochastic data remains challenging. Here, authors present a graph neural network method tha...

MIRO is a graph neural network method that enhances spatial clustering for single-molecule localisation microscopy datasets. #BiotechNatureComms

@cmanzo.bsky.social @qubilab.bsky.social @giovannivolpe.bsky.social

doi.org/10.1038/s414...

🎓 PhD position open!
Fully funded four-year PhD project at UVic-UCC @qubilab.bsky.social in collaboration with @giovannivolpe.bsky.social in physics-informed AI and single-molecule dynamics.
📄 The official call (currently in Catalan):
🔗 www.uvic.cat/sites/defaul...
✉️Feel free to get in touch!

📝 #AndiChallenge global competition puts tools for single-molecule motion analysis to the test, highlighting both the current strengths and the pressing challenges in this rapidly advancing field.

🔗Results in Nature Communications
Read the full story👉 bit.ly/3IPv9Wc

Quantitative evaluation of methods to analyze motion changes in single-particle experiments - Nature Communications Muñoz-Gil and colleagues report the results of an open challenge where they benchmarked algorithms for the characterization of motion changes in single-particle tracking. By ranking methods on simulat...

After more than 3 years, our journey with the 2nd AnDi Challenge has reached an exciting milestone: our work is now published in @natcomms.nature.com !
👉 www.nature.com/articles/s41...
Huge thanks to @gorkamunoz-gil.bsky.social, @giovannivolpe.bsky.social and to all participants of the Challenge!

DeepTrackAI DeepTrackAI has 16 repositories available. Follow their code on GitHub.

Just arrived in Madrid for the congress of SBE🔬!
This Friday morning, I’ll be talking about using Graph Neural Networks for microscopy 🤖 and sharing some tools we’ve built with deeptrackAI.
If you're into SPT, SMLM, and AI, come by and say hi!

💻 github.com/DeepTrackAI
🧪 sbe2025.com

Interested in the unsupervised analysis of complex systems with graph neural networks? 👾Check our latest preprint about
GAUDI: Graph Autoencoder Uncovering Descriptive Information⬇️

arxiv.org/abs/2503.05560

🚨 Incoming workshop 🚨

AnDi+: AI for Bioimaging Beyond Trajectory Analysis

About? All the results of the AnDi 2 Challenge but also other AI approaches to Bioimage Analysis🔎!

🌎 University of Gothenburg, Sweden
📆 June 2-5, 2025

All info here: tinyurl.com/4wrfb2k4

Help us spread the word!🤗

…all fun things must come to an end…
After 4 long years, it’s finally out (early access for now).
Can’t wait to hold a paper copy in my hands or spot it on a bookstore shelf!
⬇️

Diffusion models for super-resolution microscopy: a tutorial - IOPscienceSearch Diffusion models for super-resolution microscopy: a tutorial, Bachimanchi, Harshith, Volpe, Giovanni

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...