Below is a list of my past and future talks. Links to slides, posters and recordings are provided.
Future Talks
SIAM Conference on Applications of Dynamical Systems, Portland, OR May 2023
ICERM's Workshop Optimal Transport in Data Science, Providence, RI May 2023
IPAM's Computational Microscopy Seminar, Los Angeles CA Nov 2022
Past Talks
Rising Stars Workshop for Women in Computational and Data Sciences, Albuquerque, NM April 2022
Special Session on Geometric measure theory, JMM, Virtual April 2022
Machine Learning Seminar, University of Massachusetts Amherst, Virtual April 2022
PDE and Differential Geometry seminar, University of Connecticut, Virtual March 2022
Special Session on Analysis and Probability in Sub-Riemannian Geometry,
AMS Spring Central Sectional Meeting, Virtual March 2022
Machine Learning seminar, Boston College Jan 2022
IPAM's High Dimensional Hamilton-Jacobi PDEs Reunion Program, Los Angeles, CA Jan 2022
Machine Learning + X Seminar, Brown University, Virtual Nov 2021
SIAM Annual Meeting 2021, Virtual Conference Jul 2021
A Neural Network Ensemble Approach to System Identification, Sildes
Summer Analysis on Metric Spaces Seminar, OIST, Okinawa, Japan Jul 2021
Machine Learning Reading group, Worcester, MA Nov 2020-Apr 2021
Data-driven Solutions and Discovery Non-Linear Partial Differential Equations, by Raissi et al., Sildes
A description of CLIP and DALL.E by OpenAI, Sildes
45th New York State Regional Graduate Mathematics Conference, Syracuse, NY Mar 2020
Seminar in Linear Algebra in Big Data, Worcester, MA Oct 2019
Universal Approximation Theorem, by G. Cybenko, Sildes
Ph.D. Weekly Seminar, Worcester MA Aug 2017-present
An Introduction to Physics Informed Deep Learning
System Identification through Lipschitz Regularized Deep Neural Networks
Topological Data Analysis on Bioreactor Data
A Mathematical Introduction to Deep Learning
Why Deep Neural Networks do not overfit?
Laplacian Eigenmaps and Diffusion Maps and Applications
Harnack Inequality and Maximum principle
Dimension Reduction and Classification on Small Images
Predicting Crime in Worcester using Statistical Learning Methods
Riesz Representation Theorem on locally compact and separable metric spaces
Master Student Seminar, University of Bologna, Bologna, Italy Sep 2015- May 2017
Riesz Representation Theorem on locally compact and separable metric spaces
Mean Value Theorem for Harmonic Functions
Inverse Problem for the Curie-Weiss Model
Poster Presentations
Workshop IV: Multi-Modal Imaging with Deep Learning and Modeling, Nov 2022
IPAM, Los Angeles, CA
Graduate Research Innovation Exchange, Worcester MA. Video Feb 2022
Virtual Poster Session Computing Sciences Summer Program, Berkeley CA. Video Aug 2021
Graduate Research Innovation Exchange, Worcester MA. Video Apr 2021
Women in Machine Learning Workshop, co-located with NeurIPS, Virtual. Poster Dec 2020
Optimal Control, Optimal Transport, and Data Science, IMA, Minneapolis, MI. Video Nov 2020
Workshop II: PDE and Inverse Problem Methods in ML, IPAM, Los Angeles, CA. Video Apr 2020