PhD candidate & data scientist specializing in topological and geometric machine learning.
Founder of Krv Analytics — building agentic data engineering and federated analytics for healthcare.
- Topological & geometric machine learning
- Graph neural networks & knowledge graphs
- Federated learning & privacy-centric analytics
- Building reproducible ML tools for real-world impact
- RINGS: Evaluating graph learning datasets with topological and structural priors.
- THEMA: Topological modeling methods for energy transition planning (Nature Energy, 2025).
- APPARENT: Tools for interpretable patient representation learning in healthcare (IPLDSC 2024).
- PRESTO: Topological analysis of latent representations in deep learning (ICML 2024).
- Curvature Filtrations: Novel filtrations for probing latent space geometry (NeurIPS 2023).
- Languages: Python, Typescript
- Specialties: Graph neural networks, topological data analysis (TDA), federated learning, generative AI
- Tools: Knowledge graphs, graph databases (Neo4j), data visualization
- 🏄 Surfer
- 🎿 Skiing & Snowboarding
- 🎻 Cello player
- 🚴 Biking in Bavaria
- 🌍 Travel explorer
- 👐 Advocate for open science & reproducible ML
- 🌐 jeremy-wayland.me
- 🏢 krv.ai