Bradley Gram-Hansen

AI reasearch scientist at Dataminr in NY!

Doctorate from the University of Oxford in AI & Machine Learning.

Bio

I am currently an AI Research Scientist for Dataminr , where I develop real-time AI tools that detect the earliest signals of high-impact events and emerging risks to save peoples lifes! Prior to joining Dataminr I was the CTO & Co-founder of Intelligent Networks, funded by Entrepreneur First, where I developed innovative probabilsitic machine learning solutions, using probabilistic programming, to optimise utility networks, and help alliviate the environmental effects of a warming climate on the distribution of fresh water, due to an increase in droughts and flooding - the juxtaposition! Intelligent Networks was founded towards the end of my PhD in Machine learning, which I completed at the University of Oxford in 2021 as part of the Autonomous Intelligent Machines and Systems (AIMS) program, where I was supervised by the wonderful Yee Whye Teh , Atılım Güneş Baydin, Phil Torr and Tom Rainforth . I also had the pleasure of working with Frank Wood, who introduced me to probabilistic programming at Oxford. My PhD research focused on the intersection of probabilistic programming, computational sustainability and machine learning for societal uses. I was, and still am, interested in quantum machine learning, as my background is in quantum information science. Occasionally I will write a blog post, since I am always learning and do take a lot of notes! Unfortunately, only a very small subset of those notes make it here as I like to make sure that the information is presented as clearly as possible.

Before coming to Oxford I did a Bachelors and Masters in mathematical physics at the University of Nottingham, where I had the pleasure of doing a research internship with Gerardo Adesso, Ivette Fuentes and Antony Lee on 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 and only 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, and became a local fell running champion. I am also dyslexic and dyspraxic, so I will apologise for the typos in advance!

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.

Extending Probabilistic Programming Systems and Applying Them to Real-World Simulators

Bradley Gram-Hansen

DPhil Thesis, University of Oxford, 2021.

Examined by Professor Luke Ong and Professor John Winn

Simulation-Based Inference for Global Health Decisions

Christian Schröder de Witt, Bradley Gram-Hansen , Nantas Nardelli, Andrew Gambardellla, Rob Zinkov, Puneet Dokania, N Siddharth, Ana. B Espinosa-Gonzalez, Ara Darzi, Philip HS Torr, Atılım Güneş Baydin

ICML'20: International Conference on Machine Learning Health workshop. 2020.

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

Extending Probabilistic Programming Systems and Applying Them to Real-World Simulators

Bradley Gram-Hansen

DPhil Thesis, University of Oxford, 2021.

DPhil Thesis, University of Oxford, 2021.

Examined by Professor Luke Ong and Professor John Winn

Simulation-Based Inference for Global Health Decisions

Christian Schröder de Witt, Bradley Gram-Hansen , Nantas Nardelli, Andrew Gambardellla, Rob Zinkov, Puneet Dokania, N Siddharth, Ana. B Espinosa-Gonzalez, Ara Darzi, Philip HS Torr, Atılım Güneş Baydin

ICML'20: International Conference on Machine Learning Health workshop. 2020.

ICML'20: International Conference on Machine Learning Health workshop. 2020.

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.

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.

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

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.

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

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

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

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.

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

Multi-layer Stacked Gaussian Processes.

Bradley Gram-Hansen, Stephen Roberts

Preprint

Preprint

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

Bradley Gram-Hansen

Dissertation. Supervised by Alexander Ossipov

Dissertation. Supervised by Alexander Ossipov

Thesis: An insight into Quantum random walks.

Bradley Gram-Hansen

3rd year Thesis. Supervised by Madalin Guţă

3rd year Thesis. Supervised by Madalin Guţă

Posts

How to transfer your domain to Google cloud and set-up hosting in 6 steps
Follow these 6 easy steps to move your domain to Google cloud.
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
How to transfer your domain to Google cloud and set-up hosting in 6 steps
Follow these 6 easy steps to move your domain to Google cloud.
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, updated May 2021.

Template

To build this site I have made use of a Jekyll template created by Martin Saveski. Thank you! If you would like to use this template please go to Martin Saveski's site for the Github repository.