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Title: Elyas Heidari — machine learning for spatial biology

Description: I'm Elyas Heidari, a PhD researcher at DKFZ and EMBL in Heidelberg building machine-learning systems for spatial biology.

Mail addresses
elyas.heidari@dkfz-heidelberg.de

direct link

Domain: elihei2.github.io

Links:

Elyas Heidarihttps://elihei2.github.io/
Workhttps://elihei2.github.io/#work
Publicationshttps://elihei2.github.io/#publications
Writinghttps://elihei2.github.io/blog
CVhttps://elihei2.github.io/CV_Elyas_Heidari.pdf
https://github.com/EliHei2
https://scholar.google.com/citations?user=1tjJjf8AAAAJ
https://x.com/heidarielyas
https://www.linkedin.com/in/elyas-heidari-71024a42
Oliver Steglehttps://www.embl.org/groups/stegle/
Moritz Gerstunghttps://www.dkfz.de/en/AI-in-Oncology/index.php
realist evaluationhttps://en.wikipedia.org/wiki/Realist_Evaluation
Seggerhttps://elihei2.github.io#work
AlphaEarthhttps://deepmind.google/blog/alphaearth-foundations-helps-map-our-planet-in-unprecedented-detail/
German Cancer Research Centerhttps://www.dkfz.de/en/index.html
Sharif University of Technologyhttps://en.wikipedia.org/wiki/Sharif_University_of_Technology
Ali Sharifi-Zarchihttps://scholar.google.com/citations?user=GbJMZLIAAAAJ
MUVishttps://baio-lab.github.io/muvis
ETH Zürichhttps://ethz.ch/en/
ETH Medalhttps://ethz.ch/en/the-eth-zurich/education/awards/eth-medal.html
EMBLhttps://www.embl.org/
Wolfgang Huberhttps://www.embl.org/groups/huber/
scPotterhttps://f1000research.com/slides/9-1469
Mark Robinsonhttps://robinsonlabuzh.github.io/
SageNethttps://github.com/MarioniLab/sagenet
John Marionihttps://www.ebi.ac.uk/research/marioni/
Shila Ghazanfarhttps://shazanfar.github.io/
Cancer Research UK Cambridge Institutehttps://www.cruk.cam.ac.uk/
Paperhttps://www.biorxiv.org/content/10.1101/2025.03.14.643160v1
Docshttps://elihei2.github.io/segger_dev/
Codehttps://github.com/EliHei2/segger_dev
Dana Pe’er’s labhttps://www.mskcc.org/research/ski/labs/dana-pe-er
Docshttps://sagenet.readthedocs.io
Codehttps://github.com/MarioniLab/sagenet
Paperhttps://www.biorxiv.org/content/10.1101/2022.04.14.488419v1
Segger: Fast and accurate cell segmentation of imaging-based spatial transcriptomics datahttps://www.biorxiv.org/content/10.1101/2025.03.14.643160v1
SpatialData: an open and universal data framework for spatial omicshttps://doi.org/10.1038/s41592-024-02212-x
Integrated in vivo combinatorial functional genomics and spatial transcriptomics of tumourshttps://doi.org/10.1038/s41551-025-01437-1
Supervised spatial inference of dissociated single-cell data with SageNethttps://www.biorxiv.org/content/10.1101/2022.04.14.488419v1
scPotter: geometric deep learning on single-cell gene networkshttps://f1000research.com/slides/9-1469
MUVis: learning dependency structure in mixed-type datahttps://baio-lab.github.io/muvis
All publications →https://elihei2.github.io/publications
Google Scholarhttps://scholar.google.com/citations?user=1tjJjf8AAAAJ
Why Picasso Made 147,000 Things (And Why You Should Too)https://elihei2.github.io/blog/picasso-volume
Bioinformaticians' Tale: From Pipeline Plumber to Architects of Agentic Bot-Labshttps://elihei2.github.io/blog/bioinformaticians-tale
More writing →https://elihei2.github.io/blog
GitHubhttps://github.com/EliHei2
LinkedInhttps://www.linkedin.com/in/elyas-heidari-71024a42
Mashhadhttps://www.google.com/maps/search/?api=1&query=Mashhad%2C+Iran
Dastjerdhttps://www.google.com/maps/search/?api=1&query=Dastjerd%2C+Iran
Iranhttps://www.youtube.com/watch?v=rWj9UdYknlI
GitHubhttps://github.com/EliHei2
Scholarhttps://scholar.google.com/citations?user=1tjJjf8AAAAJ
Readinghttps://elihei2.github.io/reading

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