AWARDS
Gold Medal at Brazilian Physics Olympiad (OBF) in High School 2005

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PUBLICATIONS
Face Reconstruction with Variational Autoencoder and Face Masks at ENIAC 2021

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MOOC CERTIFICATIONS
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

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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.

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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.

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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
Boosted Trees.
• 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
automatically.

• Conducted tens of statistical analyses of internal services to detect bottlenecks, failures, and to guide the sub-
sequent engineering decisions.

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