Talks and presentations

1. Building Multiscale Representations and Surrogate Using a Greedy Approach, at the SIAM Conference on Uncertainty Quantification (UQ22), Atlanta, USA (April 2022): Invited Talk.
2. Ensemble Methods: Boosting, at Data Science and Machine Learning, Warwick Manufacturing Group, University of Warwick, Coventry, UK (April 2022): Invited Talk.
3. Multiscale Models for Sparsity Constrained Data Reduction, at the AMS Sectional Meeting: Special Session on Mathematics of Data Science, Boston, USA (March 2022): Invited Talk.
4. Greedy Multiscale Surrogates for Uncertainty Quantification, at the Annual Fall Meeting for American Geophysical Union, New Orleans, USA (Dec 2021).
5. Greedy Multiscale Strategies for Sparse Modeling and Emulation Tasks, at the $16^{th}$ US National Congress on Computational Mechanics, (July 2021).
6. Multiscale models for sparsity constrained data reduction, at the Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, USA (May 2021).
7. Hierarchical Regularization and Sparse Representation of Noisy Data sets, at Data-driven science with uncertainty quantification, machine learning, and optimization, 14th World Congress in Computational Mechanics and ECCOMAS Congress, Paris (Jan 2021).
8. Model Selection in Machine Learning, at Warwick Manufacturing Group, University of Warwick, Coventry, UK (Nov 2020): Invited Talk.
9. A Novel Hierarchical Learning Method for Remote Sensing Data, with Applications of Greenland Ice Sheet Changes from Laser Altimetry, at the Annual Fall Meeting for American Geophysical Union, San Francisco USA (Dec 2019).
10. ALPS: A framework for modeling time series of land ice changes, at Department of Geology, SUNY Buffalo, Buffalo, USA (Nov 2019): Invited Talk.
11. Exploiting the Redundancy in ICESat-2 Geolocated Photon Data (ATL03), a Multiscale Data Reduction Approach, at the Annual Fall Meeting for American Geophysical Union, San Francisco USA (Dec 2020).
12. Hierarchical Regularization Networks for Learning on Noisy Datasets, at Graduate Student Poster Session, School of Engineering and Applied Sciences, SUNY Buffalo, Buffalo, NY, USA (April 2019).
13. A Novel Approach Using Localized Time Series for Modeling Greenland Ice Sheet Elevation Changes from Long-Term Altimetry Record, at the Annual Fall Meeting for American Geophysical Union, Washington DC, USA (Dec 2018).
14. Localized Time Series Modeling of Greenland Ice sheet Elevation Changes, at 8th International Workshop on Climate Informatics: CI 2018, Boulder Colorado, USA (Sept 2018).
15. Localized Statistical Modeling for Elevation Change Time Series Data in Parts of Greenland Ice-Sheet, at International Symposium on Timescales, Processes and Ice Sheet Changes, Buffalo, NY, USA (June 2018).
16. Multi-scale Modeling for Data Sparsification, at Graduate Student Poster Session, School of Engineering and Applied Sciences, SUNY Buffalo, Buffalo, NY, USA (April 2018).
17. Multi-Scale approaches for Data Sparsification and Modeling, at CDSE days, Institute for Computational and Data Sciences, SUNY Buffalo, Buffalo, NY, USA (April 2018).