← Back to all posts
Samudyata Minasandra
Samudyata is a Software Engineer at Curlscape focused on machine learning and artificial intelligence, with a strong grounding in mathematics. Particularly interested in the mathematical foundations of learning algorithms:
Linear algebra, probability, optimization, and graph-based methods, and in applying them to build reliable, interpretable, and scalable systems.
Articles by Samudyata Minasandra
Why surrogate models fail when the geometry changes
The node count of the training mesh becomes a dimension of a learned weight matrix. Why conventional CFD surrogate models break when the geometry changes.
Fine-tuning open models in the real world: Unsloth, Axolotl, and the case for Docker
Production lessons from fine-tuning open models and why Curlscape uses Docker to ensure GPU training environments are reproducible and reliable.