Explores fundamental principles in scientific research, the impact of computers, numerical algorithms, and deep learning in solving high-dimensional problems.
Explores perception in deep learning for autonomous vehicles, covering image classification, optimization methods, and the role of representation in machine learning.
Explores data-driven modeling of haemodynamics in vascular flows, focusing on computational challenges, reduced order modeling, FSI problems, and neural network applications.
Covers wildfire susceptibility mapping using ML-Al robotics and various related topics, including experimental protocols, DFT feature engineering, SimpedCLIP, and Covid-19 detection.
