Edinburgh Research Explorer

Dr James Hopgood

Senior Lecturer

Profile photo

Willingness to take Ph.D. students: Yes

Offering projects in Machine Learning and Statistical Signal Processing. Please see my range of interests below.

Education/Academic qualification

Doctor of Philosophy (PhD), University of Cambridge
Nonstationary Signal Processing with Application to Reverberation Cancellation in Acoustic Environments
Master of Arts, University of Cambridge
Master of Engineering, University of Cambridge
Electrical and Information Sciences (EIST)

Positions available

NEW OCTOBER 2018: We are recruiting: position available for a postdoctoral research associate to work into developing algorithms for Approximate Bayesian Computation in resource constrained distributed and modular sensor networks. The post is for 30 months in the School of Engineering at the University of Edinburgh.

A research associate position for 30 months is available on the University Defence Research Collaboration (UDRC) phase 3 project jointly funded by EPSRC and UK Ministry of Defence. This research associate position will contribute to the UDRC3 under Work Package 2.1, and will work within the Institute for Digital Communications at the University of Edinburgh.

This Research Associate position provides a unique opportunity to develop novel message passing algorithms for inference in distributed and modular sensor networks. The project is hosted by the Institute for Digital Communications (IDCOM) in the School of Engineering at the University of Edinburgh.

Bayesian hierarchical graphical models provide a powerful framework for representing structure in distributions over many heterogeneous variables. Scalable solutions focus on approximate inference, utilising: bespoke approximations, Gaussian-mixture Belief Propagation (BP), particle BP, kernel BP, expectation particle BP, and approximate message passing algorithms. This research will investigate: (1) trade-offs between accuracy, complexity, convergence, and communication-bandwidth for resource-constrained scenarios and high-volumes of data; (2) improving efficiency in settings with mixed-integer/non-Gaussian continuous variables.

This post is full time and fixed term for 30 months.

For further information and full details, please see: https://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.jobspec?p_id=044881





James Hopgood is a Senior Lecturer in the Institute for Digital Communications, within the School of Engineering, at the University of Edinburgh, Scotland. He works in the disciplines of Data Science and Machine Learning within the field of Statistical Signal Processing, a branch of Electronic Engineering. 

James's research specialisation include model-based Bayesian signal processing, speech and audio signal processing in adverse acoustic environments, including blind dereverberation and multi-target acoustic source localisation and tracking, single channel signal separation, distant speech recognition, audio-visual fusion, medical imaging, blind image deconvolution, and general statistical signal and image processing.

James received the M.A., M.Eng. degree in Electrical and Information Sciences in 1997 and a Ph.D. in July 2001 in Statistical Signal Processing, part of Information Engineering, both from the University of Cambridge, England. He was then a Post-Doctoral Research Associate for the year after his Ph.D within the same group, at which point he became a Research Fellow at Queens’ College continuing his research in the Signal Processing Laboratory in Cambridge. James joined the University of Edinburgh in April 2004.

Since September 2011, he is Editor-in-Chief for the IET Journal of Signal Processing. James is the Programme Director for the MSc in Signal Processing and Communications at the University of Edinburgh. 

Research Interests

James’s interest in audio-signal processing in adverse acoustic environments covers a variety of research topics including: acoustic source localisation and tracking; blind enhancement of de-reverberation of speech and music; environmental noise reduction for acoustic sensing from remote mobile platforms; acoustic weapons fire and gunshot localisation; intelligent sensing form mobile robots; and ad-hoc acoustic sensor networks.

You can listen to some of James's recent work in his short public lecture talk from Edinurgh's Innovative Learning Week entitled "Separation and Marriage: Signal Processing for Life Science".

Positions available

PhD Position Available: Microphone array based acoustic event analysis, Distributed Source Localisation. Please contact me for further information.


Teaches two undergraduate courses, Signals and Communications 2 and Signals and Communications 3, in the second and third year respectively. James has almost 15 years experience of teaching undergraduate and masters students, and is Programme Director for the MSc in Signal Processing and Communications

Also teaches two full Masters course on "Probability, Random Variables, and Estimation Theory", and "Statistical Signal Processing". Extremely comprehensive courses notes are available for all four courses, along with a series of lecture recordings, tutorial questions, and solutions.

I also teach on the UDRC Summer School at Master's level. For more information, watch this video!

James has been using lecture recording technologies for the last seven years for supporting the student experience. His pedagogical approach is to provide visualisation, intuition, and real-world examples for describing complex topics, while providing teaching materials suitable for a range of learning needs.

Research Groups

Post Doctoral Researchers (Past)

  1. Steven Herbert, now with DAMPT, University of Cambridge. Worked on Adaptive Waveform Design.
  2. Christine Evers, now at Imperial College.

Research students

Current PhD Students (as First Supervisor or Lead co-supervisor)

  1. Student name: David Cormack
    Provisional thesis title: Multi-sensor multi-modality multi-object tracking.
    Dates: Commenced 1st October, 2016

  2. Student name: Saleh Hanano
    Provisional thesis title: Machine Learning for Real-time Classification of Liver Disease using Ultrasound & Opto-acoustic Imaging
    Dates: Commenced 1st October, 2017
    Funding: Optical Medical Imaging CDT (Optima)

Completed PhDs (as First Supervisor)

  1. Student name: Tom Bishop
    Thesis title: Blind Image Deconvolution: Nonstationary Bayesian approaches to restoring blurred photos
    Dates: Commenced October 2004, submitted November 2008, viva March 2009.
    External Examiner: Prof Nick Kingsbury, University of Cambridge
    Funding: EPSRC DTA

  2. Student name: Yan Yan
    Thesis title: Statistical signal processing for echo signals from ultrasound linear and nonlinear scatterers
    Dates: Commenced October 2005, submitted, September 2009, viva 10th December, 2009.
    External Examiner: Prof Paul White, University of Southampton
    Funding: 50% by BIAS grant, 50% by Institute for Digital Communications funds.

  3. Student name: Sharad Nagappa
    Submitted thesis title: Time-Varying Frequency Analysis of Bat Echolocation Signals using Monte Carlo Methods
    Dates: Commenced October 2005, submitted December 2009, viva 6th April, 2010.
    External Examiner: Prof Mark Plumbley, Queen Mary University
    Funding: BIAS grant.

  4. Student name: Christine Evers
    Thesis title: Blind Dereverberation of Speech From Moving and Stationary Speakers Using Sequential Monte Carlo Methods
    Dates: Commenced October 2006, submitted March 2010, viva 10th June, 2010
    External Examiner: Prof Simon Godsill, University of Cambridge
    Funding: ERP Prize Scholarship.

  5. Student name: Xionghu Zhong
    Thesis title: A Bayesian framework for multiple acoustic source tracking
    Dates: Commenced October 2006, submission May 2010, viva 13th October, 2010.
    External Examiner: Dr Wenwu Wang, University of Surrey
    Funding: University of Edinburgh Chinese Scholarship.

  6. Student name: Ashley Hughes
    Thesis title: Acoustic Source Localisation and Tracking Using Microphone Arrays
    Dates: Commenced 4th October, 2010, submmitted June 2015, viva 2nd October, 2015.
    External Examiner: Dr Wenwu Wang, University of Surrey
    Funding: 50% doctoral-training grant (DTG), 50% scholarships from Maxwell Advanced Technology Fund and Maxwell Fondation.

  7. Student name: Saurav Sthapit
    Thesis title: Computation offloading for algorithms in absence of the Cloud
    Dates: Commenced 1st January, 2014, submitted January 2018, viva 27th March 2018.
    External Examiners: Prof Andrea Cavallaro, Queen Mary, University of London, and Prof Stephan Weiss, University of Strathclyde.
    Funding: UDRC related PhD (see EPSRC Standard Research: EP/K014277/1)

Administrative Roles

Research activities & awards

  1. European Signal Processing Conference, EUSIPCO (Publisher)

    Activity: Publication peer-review and editorial workPublication peer-review

  2. Conference proceedings: IEEE International Conference on Acoustics, Speech and Signal Processing (Publisher)

    Activity: Publication peer-review and editorial workPublication peer-review

  3. IEEE Statistical Signal Processing Workshop (Event)

    Activity: Publication peer-review and editorial workPublication peer-review

View all (22) »

ID: 21945