Hello!

Hi, welcome to my website! My name is Jasmijn (she/her), and I’m a research engineer at Google. Currently I’m interested in the following topics:

Interpretability
Machine Learning for NLP (e.g., deep latent variable models)
Neural Machine Translation (e.g., with linguistic priors)

I received my PhD from ILLC, University of Amsterdam, where I was advised by Wilker Aziz, Ivan Titov and Khalil Sima’an.

Publications

You can find my publications on Google Scholar.

Talks

ACL 2019. Interpretable Neural Predictions with Differentiable Binary Variables (Google Slides)
EMNLP 2017. Graph Convolutional Encoders for Syntax-Aware Neural Machine Translation (Google Slides)

CV

2006-2009, BSc in AI, Utrecht University.
2009-2012, MSc in AI, University of Amsterdam.
2015-2020. PhD in AI, ILLC, University of Amsterdam. Defended 8 October 2020.*
2019-Now, Research Engineer, Google.

Reviewing

I reviewed for the following conferences and workshops:

ACL (2019, 2020)
EMNLP (2018, 2019, 2020)
CoNNL (2018, 2019)
ICLR (2020)
MT Summit (2019)
WMT (2018, 2019)
Analyzing and interpreting neural networks for NLP (BlackboxNLP, 2019, 2020)
Debugging Machine Learning Models (Debug ML, ICLR Workshop, 2019)
Workshop on Neural Generation and Translation (WNGT, 2018, 2019, 2020)
Workshop on Representation Learning for NLP (RepL4NLP, 2020)
Workshop on Structured Prediction for NLP (SPNLP, 2019)

Supervision

During my PhD I supervised the following students:

J. Baptist (MSc Thesis)
Laura Ruis (Honours Project)

Projects

Interpretable Neural Predictions with Differentiable Binary Variables contains the HardKuma distribution that allows (hybrid) binary samples (with true zeros and ones) that allow gradients to pass through.
Joey NMT is an easy-to-use, educational, and benchmarked NMT toolkit for novices that I developed with Julia Kreutzer.
FREVAL is an all-fragments parser evaluation metric that I developed with Khalil Sima’an.

Contact

You can find me on Twitter: @bastings_nlp.
My code is on Github: github.com/bastings.