• Distributed multi-sensor processing within the UDRC research programme.
  • Demonstration of Advanced Distributed Tracking Algorithms in collaboration with BAE Systems ATC and University College London.
  • Multi-sensor Registration for Passive Sensors
  • Generic Distributed Target Tracking Algorithms in Sensor Networks
  • Communication Constrained Inference
  • NewSense
  • Brief Research Statement
    I am interested in the analysis and design of algorithms that extract actionable information from data and signals. Data driven inference involves learning mechanisms that relate data to the "world state" we are interested in, using mathematical frameworks from, for example, the theory of probability, optimisation and computational statistics.
    Two important processing challenges that motivate my research are: i) the limited resources (e.g. computational budget, access to storage, communication bandwidth etc.) available to update a sufficiently complex model. ii) Complex environments -by definition- cannot be modelled by building upon naive assumptions. These models ought to be learned from and/or verified using previously recorded data which is a scarse resource. Trade-offs in data size and model complexity is the second research theme I am interested in.
    My research objective is to contribute to the understanding and methodological aspects of these challenges for general cybernetic systems.
    The fields of study I am interested in are:
  • Statistical inference, signal processing and information fusion; Bayesian paradigms; Variational approaches, probabilistic graphical models and message passing algorithms; Dynamic system models, population processes (e.g. Random finite sets); Machine learning.
  • Please check my publications each of which is built upon a combination of the above elements.
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