Hi, I'm Michel Oleynik.

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I'm a computer science researcher focused on healthcare.

Machine Learning

I'm interested in supervised methods, including deep learning, to teach machines how to classify (mainly clinical) text.

Natural Language Processing

I study syntactic and semantic properties of clinical texts that affect their understanding by machines.

Information Retrieval

I'm fascinated by the different aspects that influence ranking in a biomedical search engine and affect precision and recall.


See below some of my main projects.

Pink, text, letter and magnet


Text Classification

Buying books at a store


Information Retrieval

A sign at Terminal 5 of Heathrow Airport that has the neon blue code letters for destinations around the world.


Acronym Resolution



ICD Classifier

Physician noting down symptoms of a patient


Search Engine

Bankruptcy Lawyers


Grammar Checker


My short curriculum vitae.

  • Pontifical Catholic University of Paraná


    Computer Engineering

    During my bachelor at the Paraná Catholic University (Curitiba, Brazil), I got my first contact with machine learning research and employed active learning to train natural language models for medical discharge summaries.

  • University of São Paulo


    Computer Science (MSc)

    In 2010, I moved to a larger metropolitan area and did my master's at the top-100 (Times Higher Education) University of São Paulo, with a focus on statistical text classification techniques applied to oncology pathology reports.

  • A.C.Camargo Cancer Center


    Research & Development

    In 2011, I decided to go deeper into my data and got a job at the A.C.Camargo Cancer Center (São Paulo, Brazil), where I was also involved with the design and development of a search engine to retrieve eligible patients for clinical trials.

  • Medical University of Graz


    Medical Informatics (PhD)

    Four years later, I decided to expand horizons and went abroad to do my PhD at the Medical University of Graz (Austria), where I explored deep learning models for information retrieval, text cleansing and text classification in the clinical domain.

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Michel Oleynik

Michel Oleynik