-
concentration/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical
-
via nonlinear parametrizations such as deep networks, dynamical systems and control, Bayesian inference and generative modeling, and randomized linear algebra. Applications of interest are transport
-
statistical modeling and analysis of human performance data (reaction time, workload, situation awareness), including mixed-effects/multilevel models. Programming proficiency in Python, R, and/or MATLAB
Searches related to network analysis
Enter an email to receive alerts for network-analysis positions