Summary
Leylane Ferreira is a data scientist and researcher with 11 years of professional experience and five years focused specifically on data analysis and machine learning, currently working at Compass UOL and pursuing a PhD in Computer Science at UFPE. She combines practical skills in Python, SQL, PySpark, BigQuery and deep learning frameworks (TensorFlow, Keras) with a research background in resource allocation and optimization for data centers, applied now to distributed training and Deep Federated Learning. As a former university instructor she has hands-on experience teaching Big Data, ML and databases, mentoring student projects and translating complex concepts into practical solutions. Her work spans from production-ready ETL and visualization to metaheuristic optimization and distributed model training, and she is actively expanding expertise in Transformers, LLMs and cloud tooling. Notably, her academic and industrial work converges on optimizing compute allocation for large-scale model training, bridging theoretical research with applied engineering.
11 years of coding experience
Bacharelado em Sistemas de Informação, Bacharelado em Sistemas de Informação at Universidade de Pernambuco
Doutorado, Computer Science, Doutorado, Computer Science at Universidade Federal de Pernambuco