I am a Ph.D. candidate in Machine Learning at the School of Computer Science and the School of Social Statistics at University of Manchester. I focus on deep learning and explore ways of making neural networks adaptive to changes in the generative process, for instance by adapting their parameterization during inference. I'm interested in few-show learning and meta-learning, transfer learning, reinforcement-learning, and Bayesian methods for inference and decision making under uncertainty.

I'm currently working at Amazon's CoreML lab in Cambridge.

I used to work at The Boston Consulting Group Gamma, where I applied Machine Learning to develop prediction models for business intelligence, and before turning to Machine Learning studied Economics at the Stockholm School of Economics, where I focused on game theory, development economics and political economy.

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