andreas

Welcome to my personal homepage


I am a Senior machine learning scientist at Amazon, based in Cambridge, UK.

Prior to that, I worked as a research associate in machine learning and robotics at Sheffield, and before that I pursued my PhD degree with topic Deep Gaussian Processes and Variational Propagation of Uncertainty.

My area of interest is machine learning, and more specifically: Bayesian probabilistic modeling, transfer/meta-learning, uncertainty quantification. I am applying these techniques to areas such as representation learning, decision making and automation of machine learning pipelines.



Contact


Email: lastname {at} amazon {dot} com
Twitter: @adamianou
Google Scholar


News

  • Oct. 2019: Invited talk at Univ. Manchester's Advances in Data Science Seminar Series.

  • Oct. 2019: Invited talk at the workshop on Uncertainty Propagation in Composite Models, Munich.

  • Sep. 2019: Two papers accepted at NeurIPS workshops: "Empirical Bayes Meta-Learning with Synthetic Gradients" and "On Transfer Learning via Linearized Neural Networks". With my interns Shell Xu Hu and Wesley Maddox.

  • Aug. 2019: Invited talk at the Alan Turing Institute on Deep and Multi-fidelity learning with Gaussian processes.

  • Mar. 2019: Our paper "Variational Information Distillation for Knowledge Transfer" was accepted at CVPR.