About Me
I am a PhD student at Cambridge University supervised by Hong Ge in the Machine Learning Group, supported by the Harding Distinguished Postgraduate Scholars Programme. I am interested in neural network theory, specifically in understanding the inductive biases and using them to explain generalisation and other empirical phenomena that we observe. I am also interested in approaches that improve the robustness and safety of deep learning methods and AI in general.
My honours thesis was supervised by Michael Thielscher and Alan Blair and before that I completed research placements with Andreas Schutt and Haris Aziz.
Publications
Adrian Goldwaser and Hong Ge
Optimization for Machine Learning (OPT-ML) at Neurips 2022
[pdf] [bib] [doi] [arxiv]
Adrian Goldwaser and Michael Thielscher
AAAI 2020 (oral presentation)
[pdf] [bib] [doi]
Adrian Goldwaser and Andreas Schutt
CP 2017 - named Best Student Paper
[pdf] [bib] [doi]
Haris Aziz and Adrian Goldwaser
AAMAS 2017 (extended abstract)
[pdf] [bib] [doi]
Thibaut Feydy, Adrian Goldwaser, Andreas Schutt, Peter J. Stuckey and Kenneth D. Young.
ModRef 2017
[pdf] [bib]
Teaching
- 2023 Lent Term: Supervisor for 3F8: Inference
- 2018 semester 2: Teaching Assistant for COMP9444: Neural Networks
- 2018 semester 2: Teaching Assistant for COMP2521: Data Structures and Algorithms
- 2018 semester 1/2017 semester 1: Teaching Assistant for COMP3411: Artificial Intelligence
- 2017 semester 2: Teaching Assistant for COMP1521: Computer Systems Fundamentals
Personal
I have been juggling since 2006, you can see some projects related to that here.