Applied AI / Machine Learning Engineer & Researcher

Rafael Luiz Testa, PhD

I develop and evaluate AI systems in computer vision, generative models, natural-language analytics, and machine learning engineering.

What I work on

I combine model development with data, software, and evaluation. I focus on failures that are easy to miss when a system is assessed only through its final output.

01

Generative Vision

Video synthesis, temporal coherence, facial analysis, and synthetic media.

02

Reliable AI Systems

LLMs, Text-to-SQL, evaluation, validation, and deterministic fallbacks.

03

Research Engineering

Reproducible experiments, data systems, backend engineering, and operational reliability.

Selected work

These projects cover generative video, facial analysis, deepfake detection, and LLM-based analytics. Each project began with a specific failure mode and required an implementation and evaluation designed around that failure.

Selected publications

My publications cover temporal coherence in generative video, synthetic-media analysis, facial-expression synthesis, and efficient facial-expression classification.

  1. Enhancing Temporal Coherence in Image-to-Video Facial Expression Synthesis: A Dual-Loss Framework for Smoother Generation
    Rafael Luiz Testa, Ariane Machado-Lima, and Fátima L. S. Nunes
    IEEE Access, 2025
  2. Deepfake Detection on Videos Based on Ratio Images
    Rafael Luiz Testa, Ariane Machado-Lima, and Fátima L. S. Nunes
    In 2022 12th International Congress on Advanced Applied Informatics, 2022
  3. Facial Expression Synthesis Based on Similar Faces
    Rafael Luiz Testa, Ariane Machado-Lima, and Fatima L. S. Nunes
    Multimedia Tools and Applications, 2021

View all publications →

Current direction

In my current work, I develop an internal natural-language analytics platform for public-sector data. The system grounds questions in data semantics, validates candidate SQL, restricts database execution, and checks presentation choices independently.

GroundConnect language to schemas and domain concepts.
GenerateProduce structured candidates with bounded responsibilities.
ValidateCheck structure, references, and allowed behavior.
ExecuteUse restricted roles and bounded operations.
EvaluateTest failures, fallbacks, and regressions.

Contact

I am available to discuss applied AI, research engineering, and technical collaboration.