Simon Godsill
Professor
Develops Bayesian computational methods for signal processing, including sequential Monte Carlo (particle filtering), with applications to tracking, sensor fusion and music analysis and audio restoration.
Simon Godsill's lab at Cambridge works on probabilistic & causal inference, signal processing & information theory and computational imaging & photography. 25 papers since 2023, 2 at top venues, mostly ICASSP. Applications close .
At a glance
- papers, 2023–2026
- 7/ year
- at T1 venues
- 8%
- PhD students
- 0
- MS students
- 0
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 2 papers2026 · T1 0 · collecting
- 8 papers2025 · T1 0
- 8 papers2024 · T1 1
- 7 papers2023 · T1 1
T1 venuesOtherVenues: ICASSP
Research focuspaper titles that use each topic's words
- Probabilistic & causal inference8 papers
- Signal processing & information theory2 papers
- filtering1 paper
- Computational imaging & photography0 papers
- develops bayesian0 papers
Paper list
From DBLP.
20262 papers
- IEEE Trans. Aerosp. Electron. Syst.Joint Object Tracking and Intent Recognition (opens in a new tab)
- IEEE Trans. Signal Process.Real-Time Smoothing by Extremum Monte Carlo Methods (opens in a new tab)
20258 papers
- SSPAudio Signal Enhancement with Low-Rank Time-Frequency Synthesis Models (opens in a new tab)
- IEEE Trans. Signal Process.Decentralized Variational Inference Frameworks for Multi-Object Tracking on Sensor Networks (opens in a new tab)
- SSPDistributed Expectation Propagation for Multi-Object Tracking over Sensor Networks (opens in a new tab)
- FUSIONDynamics-Informed Gaussian Process Models in Stone Soup (opens in a new tab)
- FUSIONEfficient Parameter Inference for Lévy State Space Models Through GPU-Accelerated Particle MCMC (opens in a new tab)
- EUSIPCOOn the Construction of Discrete-Time Arma Models From Continuous-Time State-Space Models (opens in a new tab)
- FUSIONPiVoT: Poisson Measurements-Based Variational Multi-Object Detection and Tracking (opens in a new tab)
- CAMSAPSequential Bayesian Signal Reconstruction for Unlimited Sampling (opens in a new tab)
20248 papers
- FUSIONBimodal Multi-Object Localisation, Siteswap Inference, and Analysis for Competitive Juggling (opens in a new tab)
- FUSIONDecentralised Gradient-based Variational Inference for Multi-sensor Fusion and Tracking in Clutter (opens in a new tab)
- IEEE Trans. Intell. Veh.Driver Profiling and Bayesian Workload Estimation Using Naturalistic Peripheral Detection Study Data (opens in a new tab)
- FUSIONImplementation of Non-Gaussian Motion Models Within Stone Soup (opens in a new tab)
- FUSIONInference for Non-Gaussian Dynamical Models with Time-varying Skew (opens in a new tab)
- Stat. Comput.Point process simulation of generalised hyperbolic Lévy processes (opens in a new tab)
- ICASSP (T1)Reversible Jump Markov Chain Monte Carlo for Pulse Fitting (opens in a new tab)
- IEEE Trans. Aerosp. Electron. Syst.Variational Tracking and Redetection for Closely-Spaced Objects in Heavy Clutter (opens in a new tab)
20237 papers
- FUSIONA Scalable Rao-Blackwellised Sequential MCMC Sampler for Joint Detection and Tracking in Clutter (opens in a new tab)
- IEEE Trans. Signal Process.An Adaptive and Scalable Multi-Object Tracker Based on the Non-Homogeneous Poisson Process (opens in a new tab)
- IEEE Control. Syst. Lett.Filtering Structures for α-Stable Systems (opens in a new tab)
- FUSIONFlexible Multi-Target Tracking with Track Management Using Dirichlet and Gaussian Processes (opens in a new tab)
- ICASSP (T1)GaPP: Multi-Target Tracking with Gaussian Processes (opens in a new tab)
- FUSIONInference for Variance-Gamma Driven Stochastic Systems (opens in a new tab)
- J. Frankl. Inst.Special issue on non-deterministic machine learning (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to CambridgeMichaelmas 2027
PhD in Computer Science
- Round
- Funding round (8 Dec 2026)
- Opens
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Confirmed on the program page.
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Data
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