Find me at beamaia.com 🧠
I am a Machine Learning Engineer specializing in Computer Vision and Generative AI, with a background blending academic research and software engineering. I believe a strong theoretical foundation is essential for building reliable applications, especially when working with complex visual data and open-source tools.
- Medical Image Analysis: Working on advanced feature extraction techniques for complex histopathology images, and researching causal AI methods to improve cancer classification.
- Model Architecture: Investigating reasoning models and testing different approaches for model optimization.
- Continuous Learning: Wrapping up my Computer Science thesis (TCC II) at UFES, while actively reading the latest papers on LLMs, autonomous agents, and computer vision applied to healthcare.
- Computer Vision: PyTorch, Transformers, YOLO, and CNNs for image classification, object detection, and digital pathology.
- Generative AI & NLP: LLM Orchestration, RAG, and Agentic AI workflows (Agno, CrewAI, LangChain).
- MLOps & Backend: Building FastAPI backends and managing AWS/GCP cloud infrastructure.
- Academic Research: Deep Learning applied to complex medical datasets at the Bio-Inspired Lab (UFES).
I have a strong interest in applied research, particularly where Computer Vision intersects with healthcare. Check out my published work under the Bio-Inspired Lab:
- Bilingual: I was raised in both Brazil and the United States, and am fluent in both languages.
- Advocacy: Navigating life as an autistic individual with fibromyalgia and chronic fatigue, I am a strong proponent of work-health balance. I actively advocate for awareness around invisible disabilities, because while it can be tough, being disabled hasn't stopped me from pursuing my goals 😺.
- Interests: When I'm not coding, I'm watching Asian Dramas, walking near the beach, or hanging out with my eternal kitten, Mei 🐈.
