I am a PhD student in the Laboratory for Intelligent Probabilistic Systems
in the Computer Science department at Princeton University, supervised by Ryan Adams.
My interests broadly include deep learning,
probabilistic modelling, and numerical methods.
I am particularly interested in combining these to
accelerate modelling and design in machine learning, engineering, and
I spent two enjoyable summers at Google; with Google Brain
in Zurich, and with the speech recognition team in New York.
I received my Master's in Computer Science from Princeton
advised by Han Liu, and a Bachelor of Engineering from the University of Canterbury in New Zealand. Between college and graduate
school I worked on anomaly detection algorithms for the startup Cognevo, now
acquired by Telstra.
- Efficient optimization of loops and limits with randomized telescoping sums
Alex Beatson, Ryan Adams.
- Amortized Bayesian Meta-Learning
Sachin Ravi, Alex Beatson.
- Continual Learning in Generative Adversarial Nets
Ari Seff, Alex Beatson, Daniel Suo, Han Liu.
- Blind Attacks on Machine Learners
Alex Beatson, Zhaoran Wang, Han Liu.
Respiratory mechanics assessment for reverse-triggered breathing cycles using pressure reconstruction
Vincent Major, Simon Corbett, Daniel Redmond,
Alex Beatson, Daniel Glassenbury, Yeong Shiong Chiew,
Christopher Pretty, Thomas Desaive, Akos Szlavecz,
Balazs Benyo, Geoffrey M Shaw, J Geoffrey Chase.
Biomedical Signal Processing and Control, 2016.
The Clinical Utilisation of Respiratory Elastance Software (CURE Soft):
a bedside software for real-time respiratory mechanics monitoring and
mechanical ventilation management
Akos Szlavecz, Yeong Shiong Chiew, Daniel Redmond, Alex Beatson,
Daniel Glassenbury, Simon Corbett, Vincent Major, Christopher Pretty,
Geoffrey M Shaw, Balazs Benyo, Thomas Desaive, J Geoffrey Chase.
BioMedical Engineering Online, 2014.