João Pereira

Data Scientist at adidas | EngD Data Science

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Amsterdam ❌❌❌

The Netherlands

I am a Data Scientist at adidas in Amsterdam where I work on demand forecasting. Prior to joining adidas, I completed my Engineering Doctorate (EngD) in Data Science at Eindhoven University of Technology, where I worked on data science projects for multiple companies: ASML (2x), Van Lanschot, TE Connectivity, Heijmans, and FIOD-Belastingdienst (final project). Before the EngD, I conducted deep learning research focusing on anomaly detection in time series data and completed my Master’s and Bachelor’s degree in Electrical & Computer Engineering at Instituto Superior Técnico. I am broadly interested in the field of machine learning and its endless applications and passionate about turning cutting-edge research into products.

In my free time, I enjoy working out, meeting friends, traveling, and cooking new dishes.

Feel free to reach out to me with any queries!

News

Mar 15, 2021 I joined adidas as a Data Scientist in Amsterdam.
May 20, 2020 Talk on "Anomaly Detection with Variational Autoencoders".
Dec 1, 2019 Gave a workshop on deep learning for the EngD Data Science. Check out the materials here.
Oct 27, 2019 We introduce Solar Scan! Check out the blog post.
Jul 1, 2019 I’ll be lab monitor at the Lisbon Machine Learning School - LxMLS’19. Join us in Lisbon!

Selected Publications

  1. Unsupervised Anomaly Detection in Energy Time Series Data Using Variational Recurrent Autoencoders with Attention   94 citations
    Pereira, João,  and Silveira, Margarida
    In 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA) Dec 2018
  2. Learning Representations from Healthcare Time Series Data for Unsupervised Anomaly Detection   32 citations
    Pereira, João,  and Silveira, Margarida
    In 2019 IEEE International Conference on Big Data and Smart Computing (BigComp) Feb 2019
  3. EngD Thesis
    FIOD Image Intelligence: An Application for Large-Scale Object Detection and Analysis
    Pereira, João
    Feb 2021