scalable_learning.sys
phd researcher & research engineer
[dkfz & embl heidelberg]
Scalable Graph Learning
Spatial Inductive Biases
Multi-Omic Foundation Models
Distributed ML Infrastructure
research_philosophy
i build learning systems that transform messy, large-scale biological data into reliable infrastructure.
my focus is designing gnn and transformer pipelines that scale to 10m+ nodes while preserving mechanistic interpretability.
[view_detailed_bio]latest_updates
- segger_framework v1.0 released
- spatial_data_standardization update
scientific_dimensions
spatial & single-cell omics
end-to-end pipelines for spatial transcriptomics and multimodal integration.
scalable graph neural networks
multi-gpu training for heterogeneous gnns on graphs with 100m+ edges.
open-source tooling
architecting frameworks (segger, sagenet, scgcn) for biological discovery.