My research focus is on machine learning models that learn reusable abstractions and that generalize from few training examples by incorporating various forms of prior knowledge. My work is at the intersection of deep learning, reinforcement learning, program induction, logic, and natural language processing.
I did my Ph.D. in the Machine Reading group at University College London under the supervision of Sebastian Riedel. I was a recipient of a Google Ph.D. Fellowship in Natural Language Processing and a Microsoft Research Ph.D. Scholarship. I worked as a Research Intern at Google DeepMind in Summer 2015. In 2012, I received my Diploma (equivalent to M.Sc) in Computer Science from the Humboldt-Universität zu Berlin. Between 2010 and 2012, I worked as a student assistant and in 2013 as a research assistant in the Knowledge Management in Bioinformatics group.
e−SNLI: Natural Language Inference with Natural Language Explanations
Oana−Maria Camburu‚ Tim Rocktäschel‚ Thomas Lukasiewicz and Phil Blunsom
In Samy Bengio‚ Hanna Wallach‚ Hugo Larochelle‚ Kristen Grauman‚ Nicolò Cesa−Bianchi and Roman Garnett, editors, Proceedings of the 32nd Annual Conference on Neural Information Processing Systems‚ NeurIPS 2018‚ Montreal‚ Canada‚ December 3−8‚ 2018. Pages 9560–9572. Curran Associates‚ Inc.. December, 2018.