Bradley Gram-Hansen
AI reasearch scientist at Dataminr !
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 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! Unfortunately, we failed in finding the revenue growth we needed, nonetheless it was a fantastic experience and everyone should have a go at creating their own company - it is an ever evolving process. I continue to think of ideas everyday and I definitely want to give it another go. I completed my PhD in Machine Learning 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 would say my true academic love still lies in physics, it is my bread and butter. If you are not enchanted by the physical world, then watch the following at some point: Fun to Imagine with Richard Feynman.
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
Follow these 6 easy steps to move your domain to Google cloud.
Avoiding depression and understanding our fears and emotions
with an implementation in pytorch
with examples
I spent just $5 on accomedation in Hawaii... let that sink in.
an extended first-order probabilistic programming langauge
Follow these 6 easy steps to move your domain to Google cloud.
Avoiding depression and understanding our fears and emotions
with an implementation in pytorch
with examples
I spent just $5 on accomedation in Hawaii... let that sink in.
an extended first-order probabilistic programming langauge
Resume
Full Resume in PDF .
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Dataminr 2022 - NowAI Research Scientist II
Promoted! Develop state-of-the-art AI and probabilistic programming driven machine learning algorithms to save peoples lifes! -
Dataminr 2021 - NowAI Research Scientist I
Develop state-of-the-art AI and probabilistic programming driven machine learning algorithms to save peoples lifes! -
Intelligent Networks 2020 - 2021Co-founder & Chief technology officer
Develop and deployed all of the AI solutions and built all the data pipelines. -
University of Oxford 2016 - 2020Ph.D. Student / AI Research Scientist
Oxford Computational Stastics and Machine learning Group & Torr Vision Group -
Frontier Development Lab Summer 2018Research Scientist, Intern
Worked with UNICEF, NVIDIA and ESA on solving global challenges with ML -
Mathematical physics research group Summer 2014Summer research intern
Developing quantum maps in relativistic frameworks at the University of Nottingham -
Classical Foundations Sep 2011 - Jul 2015Mathematics and Physics tutorer
Taught high-school and advance manths. -
University of Nottingham Sep 2011 - Jun 2015MMath. Student
Masters of Mathematics
First Class Honours -
Primark Sep 2008 - Jun 2011Manager
Supervised people in the fast-fashion retailer. I learnt a lot about retail and worked with some great people
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