Theoretical and applied artificial intelligence, statistical machine learning, unsupervised methods, reinforcement learning, neural network theory. Experimental and computational physics, data science, statistics.

Languages:
[always] Python (PyTorch, Numpy/Scipy stack, Pyro), Bash;
[often] C/C++ (>= 2011), R, Julia, Mathematica;
[sometimes] MATLAB, F#, Stan.

Adversarially-robust machine learning, graph neural networks.
Rust for scientific computing.