Selected invited talks and lectures. For publications, see the Publications page.
2025
Foundations of Interpretable AI with Shapley Values
ICCV 2025
· Tutorial
· Oct 2025
ML TrustworthinessML Interpretability
Tutorial: Computational Inverse Problems
Plurinational Bayes
· Bogota, Colombia
· Oct 2025
Inverse ProblemsBiomedical Imaging
Machine learning interpretability to study biology?
Institute for Computational Medicine
· JHU
· Sep 2025
ML InterpretabilityBiomarker DiscoveryBiomedical Imaging
Foundations of Interpretable AI with Shapley Values
CVPR 2025
· Tutorial
· Jul 2025
ML TrustworthinessML Interpretability
Modern problems in trustworthy medical imaging
Medtronic
· Minneapolis, MN
· Jun 2025
ML TrustworthinessBiomedical ImagingML Interpretability
From data to insights: trustworthy methods for modern biomedical imaging
Penn ASSET Seminar
· University of Pennsylvania
· Mar 2025
Inverse ProblemsBiomedical ImagingML Trustworthiness
2024
Testing semantic importance via betting
IMS International Conference on Statistics and Data Science (ICSDS)
· Nice, Fr
· Dec 2024
ML TrustworthinessTheory
What has my model learned?
University of Michigan, EE seminar series
· Ann Arbor, MI
· Oct 2024
ML TrustworthinessInverse ProblemsBiomedical Imaging
Yes, my network works! But.. what did it learn?
Mathematical and Scientific Foudnations of Deep Learning, Annual Meeting
· SIMONS Founations, NYC
· Sep 2024
ML TrustworthinessInverse ProblemsML Interpretability
Yes, my network works! But.. what did it learn?
Mathematics of Deep Learning, BIRS Casa Matemática Oaxaca
· Oaxaca, MX
· Sep 2024
ML TrustworthinessInverse ProblemsTheory
Imaging, Data and Learning: Challenges in biomedical data science
Hariri Institute at Boston University
· Boston, MA
· Apr 2024
Biomedical ImagingML InterpretabilityML Trustworthiness
2023
Modern Challenges in Biomedical Imaging
Annual symposium of IBBS, Hopkins
· Baltimore, MD
· Nov 2023
Biomedical ImagingML InterpretabilityML Trustworthiness
Understanding Deep Nets: Sparse Local Lipschitz functions and Learned Proximal Networks
SILO (UW–Madison) and TTIC (Chicago)
· Madison, WI; Chicago, IL
· Nov 2023
TheoryML Generalization
Controlling for fairness with proxy sensitive attributes
Workshop on Algorithms, Fairness and Equity at SLMath (MSRI)
· Berkeley, CA
· Sep 2023
ML Trustworthiness
Estimating and controlling for fairness via sensitive attribute predictors
MSRI (Berkeley)
· Berkeley, CA
· Aug 2023
Biomedical ImagingML Trustworthiness
2022
Overparametrized and Robust Sparse Models
ICCHA 2022
· Buenos Aires, AR
· Sep 2022
TheoryML Generalization
Responsible ML: Interpretable and fair machine learning models
sinc(i), Argentina
· Argentina
· Aug 2022
ML Trustworthiness
2020
Overparameterized and Adversarially Robust Sparse Models
JHU CS Seminar
· Baltimore, MD
· Oct 2020
TheoryML Generalization
2018
Invited talk
Workshop: Integration of Deep Learning Theories (NeurIPS’18)
·
· Dec 2018
Convolutional Networks as Sparse Enforcing Algorithms
Invited lecture at Rene Vidal’s course on Mathematics of Deep Learning (JHU)
· Baltimore, MD
· Nov 2018
2017
From Shallow to Deep Sparsity with Convolutional Networks
CoSIP Intense Course on Deep Learning (TU Berlin)
· Berlin, DE
· Dec 2017