معرفی
Yoann Altmann is Professor in the School of Engineering & Physical Sciences at Heriot-Watt University and a member of the Institute of Sensors, Signals & Systems. Since 2024 he holds the Chair in Electrical, Electronic & Computer Engineering (EECE), directing a research programme that bridges statistical signal processing, computational imaging and quantum & neuromorphic sensing.
Education & career:
- 2010 – Eng. degree (Electrical Engineering), ENSEEIHT, Toulouse, France
- 2010 – M.Sc. (Signal Processing), National Polytechnic Institute of Toulouse
- 2013 – Ph.D. (Signal & Communications), IRIT Laboratory, Toulouse
- 2014-2017 – Post-doctoral Research Fellow, Heriot-Watt University
- 2017 – Royal Academy of Engineering Research Fellow & Assistant Professor, HWU
- 2024 – promoted to Professor, School of Engineering & Physical Sciences, HWU
Research interests:
Prof. Altmann develops mathematical and algorithmic tools for Bayesian inverse problems, with emphasis on single-photon LiDAR, low-illumination imaging, neuromorphic computational sensing, variational inference and sparse reconstruction. His work combines principled statistical modelling with efficient computational schemes to enable imaging in extreme scenarios such as underwater scattering, photon-starved environments, quantum metrology and real-time 3-D scene reconstruction.
Publication trends:
Across 160 outputs (2011-2025) his recent articles reveal a clear trajectory toward integrating modern machine-learning paradigms—variational autoencoders, diffusion generative models, spiking neural networks—with rigorous physics-based forward models. Applications span quantum parameter estimation, multimode-fiber endoscopy, hyperspectral & Compton imaging, nuclear safeguards and cultural-heritage spectroscopy, demonstrating both methodological breadth and high-impact interdisciplinary deployment.
Honours & recognition:
- Royal Academy of Engineering Research Fellowship – competitively awarded (2017)
Grants & datasets:
He has generated four open datasets supporting reproducible research in quantum sensing, variational autoencoders, underwater single-photon LiDAR and multispectral fluorescence imaging, reflecting sustained funding and commitment to open science. Continuous peer-review service for IEEE and Elsevier journals since 2013 underlines his standing within the signal-processing community.
Labs & teams:
He leads the Bayesian Imaging & Sensing Computing (BISC) group (https://bisc.site.hw.ac.uk) which hosts post-docs, PhD researchers and international visitors working on statistical machine-learning for imaging, sensing and quantum technologies.
