New upcoming talks:
I was kindly invited to give a talk on “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! Looking forward to it.
I will be speaking at the Quality Improvement in Clinical Laboratory Congress on May 20th, 2022 and I will be teaching in the Explainable AI track of the VISUM summer school together with Prof. Henning Müller.
- July 2022: Assisting Henning Müller in the Explainable AI track of the VISUM summer school and mentorship
- 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
- 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!
- 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
Others:
Mara Graziani 