Contributed spotlights
Presentations selected from submitted papers during the workshop.
Machine Learning/CORE Unranked
ML4SpatialBio 2026
NeurIPS Workshop on Machine Learning for Spatially Resolved High-dimensional Biology
ML4SpatialBio 2026 is a one-day NeurIPS workshop focused on advancing machine learning for spatially resolved high-dimensional biology. It brings together ML researchers and experimental biologists to address methodological challenges in analyzing spatial multiomics and tissue-scale data, with an emphasis on developing novel models for spatial representation, multimodal integration, and benchmarking in spatial biology.
Key deadlines
Verified August 30, 2026Full paper
September 4, 2026
AoE
Workshop timeline
Submission and decisions
Full paperKey deadline
September 4, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Contributed talks
Oral presentations selected from submitted papers during the workshop.
Posters
Poster presentations selected from submitted papers during the workshop.
Research areas in scope
01
Topics of Interest
Learning biologically meaningful spatial representations that hold across scales, from molecules to niches to organsIntegrating transcriptomic, proteomic, imaging, and clinical modalities into a single coherent modelModeling cell-cell communication and tissue dynamics over timeBuilding interpretable and uncertainty-aware spatial models that biologists can trustDesigning benchmarks, datasets, and evaluation standards specific to spatial tasksDeveloping novel ML and foundation models for spatial biology by integrating prior biological knowledge and inductive biases to improve interpretability and generalization across platforms, tissues, and speciesHandling data sparsity, noise, batch effects, and limited annotationsScaling learning to atlas-scale and whole-slide datasets
Policies worth checking twice
- Submissions are managed via OpenReview
- Submissions should address open problems requiring novel ML methods rather than incremental applications
- All submission deadlines are in AoE (Anywhere on Earth) timezone
- The program committee will be finalized and potentially expanded based on the number of submissions
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified August 30, 2026