Caio Dadauto is a senior data scientist and PhD researcher with roughly a decade of experience building statistical and deep learning solutions for anomaly and fraud detection, clustering, and dynamic graph problems in communication networks. He combines a strong academic foundation in physics and applied mathematics with hands-on engineering in Python and C/C++, leveraging TensorFlow, PyTorch and AWS ML services to move models from research to production. At Encora and now Ambush he has led feature engineering, hyperparameter tuning, and architecture design for multimodal data (audio, text, graphs), while his long-term research at Unicamp focuses on learning algorithms for temporally evolving networks like Internet core routing and VANETs. Fluent in both research and applied development, he brings an uncommon mix of convex optimization background, distributed learning experience, and low-level C++ data-processing skills gained in LHC-related work.
10 years of coding experience
11 years of employment as a software developer
Bachelor of Science - BS Physics, Bachelor of Science - BS Physics at USP - Universidade de São Paulo
Ph.D. Computer Science, Ph.D. Computer Science at Universidade Estadual de Campinas
Contributions:29 commits, 30 pushes, 1 branch in 3 years 2 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.