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About Me

I am a machine learning researcher at Qualcomm AI Research, Amsterdam. Previously I was a postdoc in Max Welling's Philips group with the Amsterdam Machine Learning Lab (AMLAB) at the University of Amsterdam. I primarily work in the field of equivariance: extending convolution beyond translation to other kinds of transformation.

Other research interests include: uncertainty quantification, unsupervised representation learning, variational inference, normalizing flows, optimization, and medical imaging.

I did my PhD at UCL in the Machine Vision Group with Gabriel J. Brostow and Dr. Clare Wilson FRCOphth. Before that I studied engineering at The University of Cambridge, and am a scholar of Sidney Sussex College.

For the last two years I lectured a course in Bayesian Statistics for Machine Learning, and have been the lab manager for the Philips lab at the UvA. I am proud contributor to the UvA Inclusive AI Initiative, which seeks to promote diversity and inclusion in the academic AI world. Find me on Google Scholar, Twitter, and GitHub.


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Bio

Daniel Worrall grew up in Cambridge, going to school there and later reading Engineering at Sidney Sussex College, Cambridge University. After Cambridge he immediately began a PhD under the supervision of Gabriel J. Brostow who is Professor in Computer Vision and Computer Graphics at UCL. He is now living and working in Amsterdam as a postdoc in the newly formed Philips Group under Prof Max Welling. He works on nascent machine learning ideas and applies them to medical imaging challenges.