Talks

PAST TALKS

• AIBIA 2026

• PanoramAI 2024

• IBM Think On Tour 2024

• November 2023: Radio Television Suisse - L'invitée de la matinale: Here the interview.

• November 2023: University of Geneva Latsis Prize. I gave a heartfelt speech at the award ceremony

• CVPR 2023: Go pay a visit to Laura’s poster “Disentangling Neuron Representations with Concept Vectors” at the Explainable AI for Computer Vision Workshop

• ISMRM 2023: Natliia’s work is in the top 5% of the conference! Yay!

• MICCAI 2023: I’m co-organizing two thrilling events: iMIMIC workshop and a [NEW!] Tutorial on Uncertainty Quantification

• May 2023: Awarding Ceremony and Closure of the Shifts Challenge 2023

• May 1-5 2023: Concept Discovery and Dataset Exploration with SVD at ICLR Trust (un)Limited

• March 2023: Concept discovery with Singular Value Decomposition at the Tübingen AI Explainability Workshop

• March 2023: AI Interpretability: Road to Mastery at the BIAS Symposium in Bern

• March 2023: Explainability in AI for pathology: the human-AI horizon at the European Cancer Research Association

• February 2023: The human – AI horizon in microscopy imaging for the Royal Society of Medicine Symposium on Unleashing the edge power of pathology

• November 2022: “Reliable AI in healthcare: from model validation to hypothesis generation” 1st Nice workshop on Interpretability

• November 2022: Online Meetup on “XAI for Segmentation models” with Nataliia Molchanova for the AIDA school on Introduction to Interpretable AI

• September 2022: “Don’t mind the gap: women in IT“ Women in IT lunch at the Silicon Valais event organized by Hes-so. Here my speech. 

• September 2022: “Attention-based Interpretable Regression of Gene Expression in Histology” at iMIMIC MICCAI 2022. 

• September 2022: “Interpretability of Deep Learning for Microscopy Imaging: from model validation to knowledge discovery”. Invited webinar at the ExaMode Consortium. Message me for a video recording of the talk! 

• July 2022: Hands-on tutorial on Explainable AI at the VISUM summer school and mentorship. *best tutorial award and best mentorship pitch award! Here the repo.

• May 2022: Invited Lecture at the Pathology congress on “Quality Improvement in Clinical Laboratories”, in the session on Artificial Intelligence, Data Science and Laboratory Medicine. Here the slides. 

• May 2022: “DL Interpretability for the discovery of biomedical patterns” at the Interpretability in AI Workshop at Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

• February 2022: “Interpretability of Deep Learning for Medical Image Classification: My Ph.D. Thesis in less than 10 slides” at the DACH symposium on digital pathology and AI. https://www.dach-pathology.org

• December 2021: Ph.D. Thesis Defense! *IEEE TCCLS best thesis award 

• November 2021: The course “Introduction to AI Interpretability” of the AIDA program (AI4Media) goes for another semester. Registration to watch-anytime videos and light supervision at introinterpretableai.wordpress.com

• October 2021: “Sharpening LIME for Histopathology: Improved Understandability and Reliability” at MICCAI2021 and at the Visual Intelligence Initiative of the Norwegian center for research-based innovation. 

• June 2021: “Interpretability of Deep Learning for Medical Imaging: Improved Understandability and Generalization” at IBM Research Zurich

• May 2021: “Crash course: Introduction to AI Interpretability”. Part of the AIDA program within AI4Media. Get accesso to watch-anytime videos and light supervision at introinterpretableai.wordpress.com

• April 2021: “Introduction to AI Interpretability” at the Applied Machine Learning Days 2021 – Workshop on Building Interpretability for Digital Pathology. Check the slides, the log of the chat with questions and answers and the GitHub repo of the experiments.

• March 2021: Better Model Interpretability for Digital Pathology: “Adapting” rather than “Applying” for the Swiss Digital Pathology Consortium

• February 2021: Presentation at the XAI Workshop AAAI21 “Evaluation and Comparison of CNN Visual Explanations for Histopathology“

• January 2021: A myth-busting attempt for DL interpretability: discussing taxonomies, methodologies and applications to medical imaging. at the CIBM Centre d’Imagerie Biomedicale de Lausanne.

• Invited talk at the SANO Computational Medicine Center on the Emerging Needs of AI for Digital Pathology.

• October 2020: Workshop on Interpretability of Machine Intelligence in Medical Imaging Computing at MICCAI 2020: Interpretable Network Pruning

• Human-centric interpretability of deep learning for digital pathology for the Swiss Digital Pathology Consortium

• Machine Learning Interpretability Inside Out e-talk at IBM Zurich on how to interpret AI models

• PhD First year exam: an extract of my slides

• Improving the interpretability of Retinopathy of Prematurity: a summary on this Medium post of my research published by SPIE Medical Imaging in Computer Assisted Diagnosis

• Swiss Machine Learning Days 2018 Regression Concept Vectors

• August 2018: Seminar at the Argonne National Laboratory

• June 2018: Visit as alumni to the Cambridge Engineering Dept

• Workshop on Interpretability of Machine Intelligence in Medical Imaging Computing at MICCAI 2018. *best paper award