Daniel Beck
Senior Lecturer at RMIT University
Melbourne, Victoria, Australia
Summary
👤
Senior🎓
Top SchoolDaniel Beck is a Senior Lecturer and applied machine learning researcher based in Melbourne with 12 years of experience bridging NLP, healthcare applications, and rigorous evaluation methods. With a PhD from Sheffield and a track record spanning research fellowships and industry internships, he combines deep Gaussian process and warped GP expertise (notably contributions to the widely used GPy library) with practical work on machine translation and language modeling. He has chaired and organized major NLP venues (ALTA, COLING, ACL) and is passionate about teaching core CS topics like algorithm design and computing theory at both undergraduate and postgraduate levels. An active advocate for diversity in AI, he contributes to the Queer in AI collective and has delivered invited keynotes, reflecting a commitment to inclusive multidisciplinary research and community service.
12 years of coding experience
2 years of employment as a software developer
Undergraduate, Computer Science, Undergraduate, Computer Science at Federal University of Rio Grande do SulDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at The University of SheffieldTechnician, Electronics, Technician, Electronics at Escola Técnica José Cesar de MesquitaM. Sc., Computational Lingustics, Machine Translation, M. Sc., Computational Lingustics, Machine Translation at UFSCar
portuguese (brazil), english (uk), spanish (latin america), French
Github Skills (6)
machine-learning10
python10
machine-learning-models10
numpy10
gaussian-processes10
model-testing8
Programming languages (2)
Github contributions (5)
SheffieldML/GPy
Jul 2015 - Apr 2016
Gaussian processes framework in python
Role in this project:
ML Engineer
ML EngineerContributions:43 commits, 3 PRs, 21 comments in 8 months
Contributions summary:Daniel made significant contributions to the `gpy` repository, focusing on the implementation and enhancement of Warped Gaussian Processes (WarpedGP) models. They added new methods for predicting quantiles and calculating the log predictive density within the WarpedGP framework. The user's work also included the incorporation of Gauss-Hermite quadrature for improved mean and variance calculations in warped space, demonstrating expertise in Gaussian process modeling. Additionally, the user modified plotting functionalities to correctly display warped GP results.
gaussiangaussian-processespython
beckdaniel/GPy
Feb 2015 - Dec 2016
Contributions:37 pushes, 8 branches in 1 year 10 months
gaussiangaussian-processespython
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