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Talks
Evaluating Unsupervised Denoising Requires Unsupervised Metrics
Communications and Signal Processing Seminar, University of Michigan, February 2023
MATH + X Symposium on Inverse Problems and Deep Learning, Costa Rica, November 2022
Special Semester on Tomography Across the Scales, Radon Institute of the Austrian Academy of Sciences, October 2022
Deep Probability Estimation
AAAI 2022 Workshop “Trustworthy AI for Healthcare”, March 2022
Deep Denoising for Scientific Discovery
Data-Enabled Science Seminar. University of Houston, October 2021
Seminar on Mathematics of Information. University of Cambridge, December 2021
Computational Mathematics + X (CMX), Caltech, May 2022
Deep Denoising for Scientific Discovery
Data-Enabled Science Seminar. University of Houston, October 2021
Seminar on Mathematics of Information. University of Cambridge, December 2021
Early-Learning Regularization Prevents Memorization of Noisy Labels (video)
Workshop on Seeking Low-dimensionality in Deep Neural Networks, November 2020
Deep learning for signal processing and medical applications
Invited seminar, Radiology department, NYU School of Medicine, December 2019
MATH + X Symposium on Inverse Problems and Deep Learning, Mitigating Natural Hazards, Costa Rica, January 2020
Neural networks for signal processing reinvent (and improve) the wheel
Workshop on Low-dimensional Models and Deep Neural Networks, Columbia University, November 2019
Optimization methods for inverse problems: The times they are a-changin’
Special seminar in machine learning and optimization, Duke University, October 2019
Separable nonlinear inverse problems in theory and practice
Applied math seminar, Courant Institute, September 2019
Asilomar Conference on Signals, Systems, and Computers, November 2019
A Sampling Theorem for Deconvolution in Two Dimensions
Imaging and Applied Optics Congress, Munich, June 2019
Sparse Recovery Beyond Compressed sensing (video)
Applied Math Colloquium, MIT, April 2018
Harmonic Analysis Seminar, CUNY, April 2019
A Sampling Theorem for Deconvolution (video)
Ecole des Mines, Paris, June 2017
Summer School on Structured Regularization for High-Dimensional Data Analysis, Paris, June 2017
12th International Conference on Sampling Theory and Applications (SampTA), Tallinn (Estonia), July 2017
55th Annual Allerton Conference on Communication, Control, and Computing, October 2017
Demixing Sines and Spikes: Spectral Super-resolution in the Presence of Outliers
ECE Seminar, Tandon School of Engineering, NYU, September 2016
Analysis seminar, Courant Institute, December 2016
Statistics seminar, Columbia University, March 2017
IDeAS seminar, Program in Applied and Computational Mathematics, Princeton University, April 2017
From seismography to compressed sensing and back: a brief history of optimization-based signal processing
Natural Sciences and Data Sciences Interface Workshop, Columbia, September 2015
Special seminar, UPenn SEAS, September 2015
Conference on Information Sciences and Systems, Princeton, March 2016
Applied math seminar, Courant Institute, March 2016
Signal and Information Processing Seminar, Rutgers, April 2016
International Workshop on Mathematical Imaging and Emerging Modalities, Osnabrueck (Germany), June 2016
Universidad de Malaga, March 2017
Optimization-based sparse recovery: Compressed sensing vs super-resolution
Workshop on Computational Photography and Intelligent Cameras, IPAM, UCLA, February 2015
Super-resolution from noisy data
SIAM Conference on Imaging Science, Hong Kong, May 2014
A convex-programming framework for super-resolution
Invited talk at UCLA Math, MIT Math, Berkeley EECS (Networking, Communications and DSP Seminar), Princeton EE, UCLA EE, Caltech EE, Center for Imaging Science at JHU, MIT EECS, UPenn EE, Courant Institute at NYU and Columbia EE. February-March 2014
Towards a mathematical theory of super-resolution
Information Theory Forum, Stanford, October 2013
Robust super-resolution via convex programming
International Conference on Continuous Optimization (ICCOPT), Lisbon (Portugal), July 2013
Support detection in super-resolution
10th International Conference on Sampling Theory and Applications (SampTA), Bremen (Germany), July 2013
Super-resolution via convex optimization
Workshop on Structure and Randomness in System Identification and Learning, IPAM, UCLA, January 2013
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