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Talented develepor focusing in the fields of AI, mainly in Computer Vision, Audio Recognition, and Data Analysis.
Gold Medal at Brazilian Physics Olympiad (OBF) in High School 2005
Face Reconstruction with Variational Autoencoder and Face Masks at ENIAC 2021
Generative Adversarial Networks Specialization (DeepLearning.AI / Coursera) 2021
TensorFlow: Data and Deployment Specialization (DeepLearning.AI / Coursera) 2020
TensorFlow in Practice Specialization (DeepLearning.AI / Coursera) 2020
Deep Learning Specialization (DeepLearning.AI / Coursera) 2019
Data Science Specialization (John Hopkins / Coursera) 2016
Machine Learning (Stanford / Coursera) 2016
Image and Video Processing (Duke / Coursera) 2015
Python, R, PyTorch, Tensorflow, Xgboost, OpenCV, Docker, Git, AWS
MIME - COMPUTER VISION ENGINEER 2019/Nov - 2022/Feb
• Built and trained a custom neural network to predict skin tones and complexions from selfies, achieving more
than 80% accuracy, a very high standard for color. Afterward, I deployed a server over this model that answers
more than 2k predictions daily.
• Adapted a computer vision algorithm to estimate a scene illumination using spherical harmonics radiance map-
ping and face 3D mesh, relighting the faces afterward.
• Built a face skin segmentation model that distinguished skin from face members for foundations virtual try-on.
It was gradient-boosting based and achieved more than 95% of accuracy.
• Adopted cutting-edge deep learning algorithms like Variational AutoEncoder (VAE), Weak Supervised Learning,
Physics-guided learning, and built custom architecture with multiples custom losses and multiple outputs.
ATHENA ANALYTICS - DATA SCIENTIST 2019/Sep - 2020/Feb
• Invented multiple new grade features and developed an autoregressive model that predicted grades from more
than 100k students with 93% accuracy in many Irish schools.
• Created an autoML system that generated optimum new models as more samples were added. The optimization
was based on hyper-tuning bayesian search.
• Automated crontab service to feed predictions on the database as more data were added.
KHOMP - DATA SCIENTIST 2016/Nov - 2019/May
• Developed an AI service that distinguished human voices from machine/records voices with 98% accuracy. This
service predicts more than 150k calls daily for tens of customers on production.
• Developed an autoML service for independent custom training of clients that delivered optimum models in less
than 1 hour, requiring them only to send data to the cloud.
• Implemented an autoML service that instantiated resources only by demand on Azure. Everything (Blobs and
Batch Computing) on automatically instantiated and automatically destroyed.
• Implemented a biometric voice system for more than 100 people from scratch using Gaussian Mixture Models
and Gradient Boosted Trees models, hypothesis tests, and a custom file database system.
• Trained models to recognize a speaker’s emotion, age, and gender using Gaussian Mixture Models and Gradient
• Implemented Continuous Integration and Continuous Deployment (CI/CD) configurations in five gitlab projects,
besides webhooks in the docker registries.
NEOWAY - COMPUTER VISION ENGINEER / DATA SCIENTIST 2019/Sep - 2020/Feb
• Trained more than 200 CAPTCHA’s recognition solutions, achieving performance superior to 80%. Used classical
approaches with SVM and deep learning approach with VGG19 and Caffe.
• Applied reverse engineering to formulate numbers from more than 50 Brazilian government registers of open
sources to internet bots.
• Formulated hundreds of specific queries on PostgreSQL databases to answer customers’ questions and analyses
• Conducted tens of statistical analyses of internal services to detect bottlenecks, failures, and to guide the sub-
sequent engineering decisions.