Luis Oala

PhD Student @ Department of Artificial Intelligence | Fraunhofer Heinrich Hertz Institute (HHI)
WG Chair @ ITU/WHO Focus Group on AI for Health
Co-organizer @ aiaudit.org

Hi 👋 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 “Machine Learning for Health: Algorithm Auditing & Quality Control” 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. IJCARS
    Detecting failure modes in image reconstructions with interval neural network uncertainty
    Oala, Luis, Heiß, Cosmas, Macdonald, Jan, März, Maximilian, Kutyniok, Gitta, and Samek, Wojciech
    International Journal of Computer Assisted Radiology and Surgery 2021
  2. ICLR
    Post-Hoc Domain Adaptation via Guided Data Homogenization
    Willis, Kurt, and Oala, Luis
    In ICLR 2021 Workshop on Robust and Reliable Machine Learning in the Real World Workshop (RobustML) 2021
  3. ITU/WHO
    Good practices for health applications of machine learning: Considerations for manufacturers and regulators
    Johner, Christian, Balachandran, Pradeep, Oala, Luis, Lee, Aaron .Y., Leite, Alixandro Werneck, Murchison, Andrew, Lin, Anle, Molnar, Christoph, Rumball-Smith, Juliet, Baird, Pat, Goldschmidt, Peter. G., Quartarolo, Pierre, Xu, Shan, Piechottka, Sven, and Hornberger, Zack
    In Proceedings of the ITU/WHO Focus Group on Artificial Intelligence for Health (FG-AI4H) - Meeting K 2020
  4. NeurIPS Spotlight
    Top 10%
    ML4H Auditing: From Paper to Practice
    Oala, Luis, Fehr, Jana, Gilli, Luca, Balachandran, Pradeep, Leite, Alixandro Werneck, Calderon-Ramirez, Saul, Li, Danny Xie, Nobis, Gabriel, Alvarado, Erick Alejandro Munoz, Jaramillo-Gutierrez, Giovanna, Matek, Christian, Shroff, Arun, Kherif, Ferath, Sanguinetti, Bruno, and Wiegand, Thomas
    In Proceedings of the Machine Learning for Health NeurIPS Workshop 2020
  5. ICML Spotlight
    Top 10%
    Detecting Failure Modes in Image Reconstructions with Interval Neural Network Uncertainty
    Oala, Luis, Heiß, Cosmas, Macdonald, Jan, März, Maximilian, Samek, Wojciech, and Kutyniok, Gitta
    In ICML 2020 Workshop on Uncertainty & Robustness in Deep Learning 2020