Bradley Gram-Hansen

PhD Student in the OXCSML and Torr-Vision groups

bradley [AT] robots.ox.ac.uk

Bio

I am DPhil Student on the Autonomous Intelligent Machines and Systems (AIMS) program at the University of Oxford supervised by the wonderful Yee Whye Teh , Atılım Güneş Baydin, Phil Torr and Tom Rainforth . My research interests lie between the intersection of probabilistic programming, computational sustainability and Machine learning for societal uses. I am also interested in Quantum machine learning, as my background is in quantum information science.

Before coming to Oxford I did a research internship at the University of Nottingham, with Professor Gerardo Adesso, Professor Ivette Fuentes and Dr Antony Lee in developing quantum maps for quantum channels moving in De Sitter spacetime. I volunteered as a mathematics and disability tutor at my old high school, to give something back to the school that made me and support those from disadvantaged backgrounds (Greenwood dale school now called the Nottingham Academy). I also completed a full Iron Man, my first ever triathalon, marathon and multi-sport event with just 4 weeks of training, simply because I was given a free entry 4 weeks beforehand... it took just over 10 hours to complete . I wild camped and cycled the breadth of Scotland. I became a local fell running champion. I completed my masters in Mathematics and my undergraduate in Mathematical Physics at the University of Nottingham.

Fun fact: For most of my life I got to cycle past the birthplace and grave of the famous George Green (Green functions).

Publications

Most recent publications on Google Scholar.

Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model

Atilim Gunes Baydin, Lukas Heinrich, Wahid Bhimji, Bradley Gram-Hansen , Gilles Louppe, Lei Shao, Kyle Cranmer, Frank Wood

NeurlPS'2019: Thirty-third Conference on Neural Information Processing Systems, 2019.

Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale.

Atılım Güneş Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip Torr, Victor Lee, Kyle Cranmer, Frank Wood

SC'19: International Conference on Super Computing. 2019. Nominated for best paper award

Hijacking Malaria Simulators with Probabilistic Programming.

Bradley Gram-Hansen* , Christian Schröder de Witt*, Tom Rainforth, Philip HS Torr, Yee Whye Teh, Atılım Güneş Baydin

ICML'19: International Conference on Machine Learning AI for Social Good workshop. 2019.

LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models.

Bradley Gram-Hansen*, Yuan Zhou*, Tobias Kohn, Tom Rainforth, Hongseok Yang, Frank Wood

AISTATS'19: International Conference on Artificial Intelligence and Statistics. 2019

Mapping Informal Settlements in Developing Countries using Machine Learning and Low Resolution Multi-spectral Data.

Bradley J Gram-Hansen*, Patrick Helber*, Indhu Varatharajan, Faiza Azam, Alejandro Coca-Castro, Veronika Kopackova, Piotr Bilinski

AAAI'19: Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Generating Material Maps to Map Informal Settlements.

Bradley J Gram-Hansen*, Patrick Helber*, Indhu Varatharajan, Faiza Azam, Alejandro Coca-Castro, Veronika Kopackova, Piotr Bilinski

NeurlPS'18: NeurlPS workshop on Machine Learning for the Developing World (ML4DW), 2018

Usability of Probabilistic Programming Languages

Alan Blackwell, Tobias Kohn, Martin Erwig, Atilim Gunes Baydin, Luke Church, James Geddes, Andy Gordon, Maria Gorinova, Bradley Gram-Hansen, Neil Lawrence, Vikash Mansinghka, Brooks Paige, Tomas Petricek, Diana Robinson, Advait Sarkar, Oliver Strickson

Psychology of Programming Interest Group 30th Annual Workshop, PPIG 2019.

Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model

Atilim Gunes Baydin, Lukas Heinrich, Wahid Bhimji, Bradley Gram-Hansen , Gilles Louppe, Lei Shao, Kyle Cranmer, Frank Wood

NeurlPS'2019: Thirty-third Conference on Neural Information Processing Systems, 2019.

Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale.

Atılım Güneş Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip Torr, Victor Lee, Kyle Cranmer, Frank Wood

SC'19: International Conference on Super Computing. 2019. Nominated for best paper award

Hijacking Malaria Simulators with Probabilistic Programming.

Bradley Gram-Hansen* , Christian Schröder de Witt*, Tom Rainforth, Philip HS Torr, Yee Whye Teh, Atılım Güneş Baydin

ICML'19: International Conference on Machine Learning AI for Social Good workshop. 2019.

LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models.

Bradley Gram-Hansen*, Yuan Zhou*, Tobias Kohn, Tom Rainforth, Hongseok Yang, Frank Wood

AISTATS'19: International Conference on Artificial Intelligence and Statistics. 2019

Mapping Informal Settlements in Developing Countries using Machine Learning and Low Resolution Multi-spectral Data.

Bradley J Gram-Hansen*, Patrick Helber*, Indhu Varatharajan, Faiza Azam, Alejandro Coca-Castro, Veronika Kopackova, Piotr Bilinski

AAAI'19: Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Generating Material Maps to Map Informal Settlements.

Bradley J Gram-Hansen*, Patrick Helber*, Indhu Varatharajan, Faiza Azam, Alejandro Coca-Castro, Veronika Kopackova, Piotr Bilinski

NeurlPS'18: NeurlPS workshop on Machine Learning for the Developing World (ML4DW), 2018

Hamiltonian Monte Carlo for Probabilistic Programs with Discontinuities.

Bradley Gram-Hansen, Yuan Zhou, Tobias Kohn, Tom Rainforth, Hongseok Yang, Frank Wood

ProbProg'18: International Conference on Probabilistic Programming. 2018.

Multi-layer Stacked Gaussian Processes.

Bradley Gram-Hansen, Stephen Roberts

Preprint

Dissertation: An investigation into the creation of entanglement mediated by interaction.

Bradley Gram-Hansen

Dissertation. Supervised by Alexander Ossipov

Thesis: An insight into Quantum random walks.

Bradley Gram-Hansen

3rd year Thesis. Supervised by Madalin Guţă

posts

The PhD Life
Avoiding depression and understanding our fears and emotions
The beginners guide to Hamiltonian Monte Carlo
with an implementation in pytorch
How to use Loader Finder Objects in Python
with examples
The PhD Life
Avoiding depression and understanding our fears and emotions
The beginners guide to Hamiltonian Monte Carlo
with an implementation in pytorch
How to use Loader Finder Objects in Python
with examples
Backpacking with just hand luggage
I spent just $5 on accomedation in Hawaii... let that sink in.
An Introduction to PySPPL
an extended first-order probabilistic programming langauge

Resume

Full Resume in PDF.

  • University of Oxford 2016 - now
    Ph.D. Student
    Oxford Computational Stastics and Machine learning Group & Torr Vision Group
  • Frontier Development Lab Summer 2018
    Research Scientist, Intern
    Worked with UNICEF, NVIDIA and ESA on solving global challenges with ML
  • Mathematical physics research group Summer 2014
    Summer research intern
    Developing quantum maps in relativistic frameworks at the University of Nottingham
  • University of Nottingham Sep 2011 - Jun 2015
    MMath. Student
    Masters of Mathematics
    First Class Honours