Summary
Angelo Mendes is a PhD-trained data scientist with 10 years of experience applying machine learning to real-world problems, notably in music analytics, NLP and multimodal pipelines. He combines academic rigor—international publications and awards—with hands-on product delivery across startups, consultancies and AI centers of excellence, building graph neural networks, large-scale text extraction systems and language models. Comfortable across the stack, he integrates models into cloud-native services (AWS/GCP), search platforms and distributed backends, having contributed as both researcher and backend developer. Atop applied research, he brings a pragmatic eye for turning exploratory analysis into business-ready solutions and has led cross-functional teams from prototyping to production. An often-overlooked strength is his expertise with heterogeneous graph learning (PyTorch Geometric), which underpins several of his predictive and unsupervised projects.
10 years of coding experience
4 years of employment as a software developer
Bacharel em Sistemas de Informação, Bacharel em Sistemas de Informação at Instituto Federal de Educação, Ciência e Tecnologia do Sudeste de Minas
University of São Paulo
Mestre, Computer Science, Mestre, Computer Science at Universidade Federal de Juiz de Fora
Spanish