I like to use AI to solve challenging problems.

• Worked 2 years in entrepreneurial roles in startups.
• Worked 3 years as an AI engineer and researcher.
• Special interest in data-centric AI, structuring ML projects, and connecting AI to business problems.

Quick overview of my pinned repos (check the repos for more details):

• LLM Trustworthiness: NoPinocchio
  Tool to add confidence scores to the output of LLMs.

• Deep Learning for omics data: Autoencodix
  Framework for multi-omics integration. Unified different autoencoder architectures from research papers into one framework.

• Computer Vision for Stem Cell Detection
  Software with a web app to detect cells in microscopy images to enhance stem cell production. Technical blog post about problems I've solved for this app, see here

• LLM Security: DeepSeek "Hack"
  Bypass censorship of DeepSeek model with prompt engineering.

• For structuring ML projects: Yearning Machine Learning by Andrew Ng
• For Active Learning: Human-in-the-Loop Machine Learning by Robert Monarch
• For working with foundation models: AI Engineering by Chip Huyen
• For an intuitive understanding of complex ML theory: everything from Luis Serrano and 3Blue1Brown
• For LLMs: Andrej Karpathy and Sebastian Raschka
• For keeping up-to-date: The Batch, Interconnects and Ahead of AI