Summary
Karlo Vrancic is a data scientist and engineer with a decade of experience blending product-minded execution and research-grade machine learning across academia and industry. Currently a Graduate Research Assistant at Harvard Medical School / MGH, he builds cross-modal deep learning models for speech reconstruction from real-time MRI while pursuing data science graduate studies. He co-founded TeeWiz, where he shipped a generative-model-based workflow that scaled to 1,000+ users and immediate revenue, and previously architected a high-precision pipeline at CERN that uncovered hundreds of predatory publishing operations. Comfortable from low-level engineering to statistical research, he pairs "vibe coding" creativity with rigorous feature engineering and LLM-enabled semantic analysis. Based in Cambridge and a longtime Vim user, Karlo brings a rare mix of scrappy product focus, academic rigor, and experience deploying ML systems into real-world workflows.
10 years of coding experience