Marcelo Pereyra | BLOOM

Maxwell Insitute for Mathematical Sciences
School of Mathematical and Computer Sciences, Heriot-Watt University

BLOOM: Bayesian computation for low-photon imaging


BLOOM is a 4-year project funded by UKRI EPSRC (EP/V006134/1 and EP/V006177/1) to develop new computational imaging methodology for low-photon imaging problems, with special attention to quantum-enhanced approaches that seek to exploit the quantum nature of light in order to dramatically advance imaging sciences. The methods will be rooted in the Bayesian framework and combine ideas from applied mathematics, computational statistics and artificial intelligence.

We will focus on the development of scalable Bayesian computation techniques for image reconstruction, uncertainty quantification, and automatic model calibration, and study their application to low-photon multispectral single-pixel imaging, high-resolution passive gamma emission tomography, and single-photon 3D LIDAR with array sensors.

The project started in Nov. 2021. It is led by Heriot-Watt University and the University of Edinburgh in partnership with the UK Quantum Enhanced Imaging Hub (QUANTIC), the University of Illinois, and the aerospace company Leonardo.


Dr Yoann Altmann, Heriot-Watt University (web)
Dr Kostas Zygalakis, University of Edinburgh (web)

Postdocs and PhD students:

Dr Cecilia Tarpau, Dr Paul Dobson, Savvas Melidonis, and Teresa Klatzer.


Prof. Derryck Reid, Heriot-Watt University (web)
Prof. Gerald Buller, Heriot-Watt University (web)
Prof. Miles Pagett (web)
Prof. Daniele Faccio (web)
Dr. Angela Di Fulvio, University of Illinois (web)
Dr. Alain Durmus, Centre Borelli, ENS Paris-Saclay (web)
Dr. Valentin De Bortoli, University of Oxford (web)
UK Quantum Enhanced Imaging Hub (QUANTIC)
Leonardo UK (web)

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