Area of research
Radiology, Nuclear Medicine and Imaging · Computational Mechanics
Research interest
Research interests include Computer science, Artificial intelligence, Physics, Principal component analysis, Nonparametric statistics, and Bispectrum.
Gauge-invariant and anyonic-symmetric autoregressive neural network for quantum lattice models
Advances in Machine and Deep Learning for Modeling and Real-Time Detection of Multi-messenger Sources
Enabling real-time multi-messenger astrophysics discoveries with deep learning
Statistically-informed deep learning for gravitational wave parameter estimation
Fast Steerable Principal Component Analysis
Analog forecasting with dynamics-adapted kernels
Data-driven prediction strategies for low-frequency patterns of North Pacific climate variability
Rotationally invariant image representation for viewing direction classification in cryo-EM