Lars Ankile

Before starting at Stanford, I interned at Amazon FAR (Frontier AI & Robotics) working on residual off-policy RL with Anusha Nagabandi, Pieter Abbeel, Guanya Shi, and Rocky Duan.

Before that, I was a visiting researcher at the Improbable AI Lab at MIT CSAIL working on robot learning with Prof. Pulkit Agrawal.

I completed an M.Eng. in Data Science at Harvard University, where I did my thesis work in the Improbable AI group on sample-efficient imitation learning. I also spent a year in the Data to Actionable Knowledge Lab at Harvard, working with Profs. Weiwei Pan and Finale Doshi-Velez on applying RL and Bayesian inference to model human decision-making for frictionful tasks in healthcare settings. I also spent a summer and fall interning with Prof. David Parkes and Matheus Ferreira in the EconCS Lab at Harvard working on detecting manipulation in multi-agent settings.

I did my undergrad at the Norwegian University of Science and Technology (NTNU) and did my thesis work on applying Deep Learning to econometric forecasting of complex and multivariate time series, supervised by Prof. Sjur Westgaard.