Luis Oala

Head of Machine Learning @ Dotphoton building towards metrological.ml
PhD Student @ Department of Artificial Intelligence | Fraunhofer Heinrich Hertz Institute (HHI)

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Hi ūüĎč I am Luis Oala. I am a PhD research scientist at the Department of Artificial Intelligence of Wojciech Samek at Fraunhofer HHI in Berlin, Germany.

Together with my students and collaborators, I work at the intersection of uncertainty quantification, robustness and interpretability to understand and detect failure modes of deep neural networks.

Our mission is to develop methods, standards and software for AI auditing that will eventually allow the reliable application of AI technology even in high-stakes applications such as medicine.

For that purpose, I co-chair a group of more than 30 contributors from across the world working on data and AI solution assessment methods at the ITU/WHO Focus Group on Artificial Intelligence for Health (FG-AI4H) and co-organize a growing, open research network at aiaudit.org.

If you are interested to collaborate I invite you to take a look here.

news

Aug 30, 2021 The site for our Lens to Logit project, a framework to address camera hardware-drift, is up complete with code and data. Learn more
Aug 25, 2021 Our paper on uncertainty quantification, interval neural networks and failure mode detection has appeared in International Journal of Computer Assisted Radiology and Surgery. Learn more
Aug 20, 2021 I am co-organizing ML4H 2021. Learn more
Aug 18, 2021 I am guest-editing a special collection on ‚ÄúMachine Learning for Health: Algorithm Auditing & Quality Control‚ÄĚ in the Journal of Medical Systems. Submit your work here
Aug 15, 2021 The second iteration of ML4H trial audits has started. Learn more

selected publications

  1. NeurIPS
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    ML4H Auditing: From Paper to Practice
    Luis Oala, Jana Fehr, Luca Gilli, Pradeep Balachandran, Alixandro Werneck Leite, Saul Calderon-Ramirez, Danny Xie Li, Gabriel Nobis, Erick Alejandro Munoz Alvarado, Giovanna Jaramillo-Gutierrez, Christian Matek, Arun Shroff, Ferath Kherif, Bruno Sanguinetti, and Thomas Wiegand
    In Proceedings of the Machine Learning for Health NeurIPS Workshop, 11 dec 2020
  2. ICML
    Detecting Failure Modes in Image Reconstructions with Interval Neural Network Uncertainty
    Luis Oala, Cosmas Heiß, Jan Macdonald, Maximilian März, Wojciech Samek, and Gitta Kutyniok
    In ICML 2020 Workshop on Uncertainty & Robustness in Deep Learning, 11 dec 2020
  3. ICLR
    Post-Hoc Domain Adaptation via Guided Data Homogenization
    Kurt Willis, and Luis Oala
    In ICLR 2021 Workshop on Robust and Reliable Machine Learning in the Real World Workshop (RobustML), 11 dec 2021
  4. ICLR
    More Than Meets The Eye: Semi-supervised Learning Under Non-IID Data
    Saul Calderon-Ramirez, and Luis Oala
    In ICLR 2021 Workshop on Robust and Reliable Machine Learning in the Real World Workshop (RobustML), 11 dec 2021
  5. BVM
    Interval Neural Networks as Instability Detectors for Image Reconstructions
    Jan Macdonald, Maximilian März, Luis Oala, and Wojciech Samek
    In Bildverarbeitung f√ľr die Medizin 2021, 11 dec 2021
  6. IJCARS
    Detecting failure modes in image reconstructions with interval neural network uncertainty
    Luis Oala, Cosmas Heiß, Jan Macdonald, Maximilian März, Gitta Kutyniok, and Wojciech Samek
    International Journal of Computer Assisted Radiology and Surgery, 11 dec 2021