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Dr Jeremie Houssineau

I am an assistant professor in the Department of Statistics and the deputy director of the Applied Statistics & Risk Unit (AS&RU). I am also on the management committee of the Centre for Space Domain Awareness (CSDA).

My research interests cover:

  1. Representation of uncertainty, with the objective of combining probability and possibility theories in one holistic framework allowing for both random and deterministic uncertainties to be faithfully modelled.
  2. Multi-target tracking, as an application of the above-mentioned framework in a particularly complex type of system including false positives, false negatives and uncertainty in data association.
  3. Bayesian Statistics and Monte Carlo methods, in particular multilevel and multi-index Monte Carlo methods for the approximation of filtering and smoothing distributions related to differential equations with randomness.


I am teaching ST208 Mathematical Methods in 2022/23.

My office hours are:

  • Monday: 15:30 to 16:30
  • Wednesday: 9:30 to 10:30

Meetings can be booked via the Moodle page of the module. If you are unable to make it for any of these office hours, please email me to decide on another time.


  • H. Cai, J. Houssineau, B. A. Jones, M. Jah and J. Zhang: Possibility generalized labeled multi-Bernoulli filter for multi-target tracking under epistemic uncertainty. IEEE Transactions on Aerospace and Electronic Systems, accepted.
  • E. Delande and J. Houssineau: Uncertain Data Representation. In: P. Magee, M. Jah and W. Larson (eds.) Space Domain Awareness, 1st edition. Space Technology Series, 2022
  • J. Houssineau, J., Zeng, and A. Jasra: Uncertainty modelling and computational aspects of data association. Statistics and Computing, 31(59), 2021
  • Z. Chen, B. Ristić, J. Houssineau, D.Y. Kim: Observer control for bearings-only tracking using possibility functions. Automatica, 133, 109888, 2021
  • J. Houssineau: A linear algorithm for multi-target tracking in the context of possibility theory. IEEE Transactions on Signal Processing, 69, 2740-2751, 2021
  • B. Ristić, J. Houssineau and S. Arulampalam: Target tracking in the framework of possibility theory: The possibilistic Bernoulli filter. Information Fusion, 62, 81-88, 2020
  • J. Houssineau and D.E. Clark: On a representation of partially-distinguishable populations. Statistics, 54(1), 23-45, 2020
  • J. Houssineau, A. Jasra and S.S. Singh: On Large Lag Smoothing for Hidden Markov Models. SIAM Journal on Numerical Analysis, 57(6), 2812-2828, 2019.
  • J. Houssineau, S.S. Singh and A. Jasra: Identification of multi-object dynamical systems: consistency and Fisher information. SIAM Journal on Control and Optimization, 57(4), 2603-2627, 2019
  • E.D. Delande, J. Houssineau, J. Franco, C. Frueh, D.E. Clark and M. Jah: A new multi-target tracking algorithm for a large number of orbiting objects. Advances in Space Research, 64(3), 645-667, 2019
  • M. Üney, J. Houssineau, E.D. Delande, S.J. Julier and D.E. Clark: Fusion of finite set distributions: Pointwise consistency and global cardinality. IEEE Transactions on Aerospace and Electronic Systems, 55(6), 2759-2773, 2019.
  • B. Ristić, J. Houssineau and S. Arulampalam: Robust target motion analysis using the possibility particle filter. IET Radar, Sonar & Navigation, 13(1), 18-22, 2019.
  • J. Houssineau and D.E. Clark: Multi-target filtering with linearized complexity. IEEE Transactions on Signal Processing, 66(18), 4957-4970, 2018.
  • E.D. Delande, J. Houssineau and M. Jah: Physics and human-based information fusion for improved resident space object tracking. Advances in Space Research, 62(7), 1800-1812, 2018.
  • A.N. Bishop, J. Houssineau, D. Angley and B. Ristić: Spatio-temporal tracking from natural language statements using outer probability theory. Information Sciences, 463-464, 56-74, 2018.
  • J. Houssineau, A. Jasra and S.S. Singh: Multilevel Monte Carlo for Smoothing via Transport Methods. SIAM Journal on Scientific Computing, 40(4), A2315-A2335, 2018.
  • J. Houssineau and A.N. Bishop: Smoothing and filtering with a class of outer measures. SIAM/ASA Journal on Uncertainty Quantification, 6(2), 845-866, 2018.
  • With D. Crisan, P. Del Moral and A. Jasra: Unbiased Multi-index Monte Carlo. Stochastic Analysis and Applications, 36(2), 257-273, 2018.
  • I. Schlangen, E.D. Delande, J. Houssineau and D.E. Clark: A second-order PHD filter with mean and variance in target number. IEEE Transactions on Signal Processing, 66(1), 48-63, 2018.
  • E.D. Delande, C. Früh, J. Franco, J. Houssineau and D.E. Clark: Novel Multi-Object Filtering Approach for Space Situational Awareness. Journal of Guidance, Control, and Dynamics; Special Issue on Space Domain Awareness, 41(1), 59-73, 2018.
  • S. Nagappa, E.D. Delande, D.E. Clark and J. Houssineau: A tractable forward-backward CPHD smoother. IEEE Transactions on Aerospace and Electronic Systems, 53(1), 2017.
  • Y. Pailhas, J. Houssineau, Y. Petillot and D.E. Clark: Tracking with MIMO sonar systems: applications to harbour surveillance. IET Radar, Sonar & Navigation, 11(4), 629-639, 2017.
  • D.S. Bryant, E.D. Delande, S. Gehly, J. Houssineau, D.E. Clark and B.A. Jones: The CPHD filter with target spawning. IEEE Transactions on Signal Processing, 65(5), 13124-13138, 2016.
  • J. Houssineau, D.E. Clark, S. Ivekovič, C.S. Lee and J. Franco: A unified approach for multi-object triangulation, tracking and camera calibration. IEEE Transactions on Signal Processing, 64(11), 2934-2948, 2016.
  • I. Schlangen, J. Franco, J. Houssineau, E.W. Pitkeathly, D.E. Clark, I. Smal and C. Rickman: Multiple object tracking with marker-less stage drift correction in super-resolution microscopy. IEEE Journal of Selected Topics in Signal Processing, Special Issue on Advanced Signal Processing in Microscopy and Cell Imaging, 10(1), 193-202, 2016.
  • With P. Del Moral: Particle association measures and multiple target tracking. In: T. Matsui and G.W. Peters (eds.) Theoretical Aspects of Spatial-Temporal Modeling. Springer Japan, 2015.
  • E.D. Delande, M. Üney, J. Houssineau and D.E. Clark: Regional variance for multi-object filtering. IEEE Transactions on Signal Processing, 62(13), 3415-3428, 2014.
  • D.E. Clark and J. Houssineau: Faà di Bruno’s formula and spatial cluster modelling. Spatial Statistics, 6, 109-117, 2013.

For preprints and conference articles, please visit my personal web pageLink opens in a new window.


Dr Jeremie Houssineau
Department of Statistics
University of Warwick
Coventry, CV4 7AL
United Kingdom


jeremie.houssineau (at)


MSB 2.16