Michael Davies

PROF

Accepting PhD Students

PhD projects

I am currently looking for PhD students under the following themes listed below. There is the opportunity to get university funding. As these are highly competitive, you are recommended to complete a formal application as soon as possible in order to be considered for any university funding opportunities.

Current Research Themes

Machine Imaging
Computational imaging relies on the acquisition of sensor measurements that indirectly inform about the imaged object and has a broad range of applications, from computational microscopy, medical imaging (CT, MRI, ultrasound), to sonar, radar, and seismic imaging. Current state-of-the-art methods are leveraging sophisticated machine learning (ML) solutions based on deep neural networks. However, supervised ML solutions necessitate unrealistic access to a large quantity of ground truth images.

One of the aims of this theme is to develop a foundational theoretical framework and algorithmic toolbox for learning to image with limited or no ground truth data. It will lay the foundations for a new wave of unsupervised ML-based computational imaging, with potential applications across a range of settings and imaging modalities from advanced medical imaging to robotics and autonomous systems. Unleashing the ML from ground truth data will enable the algorithms to exploit the larger quantities of unsupervised measurement data available to learn more complex and effective models leading to practical benefits of accelerated acquisitions and reduced imaging artifacts, as well as totally new imaging opportunities.

Data-Driven Computational Sensing and Imaging
Today's state-of-the-art imaging and sensing rely as much on computation as they do on sensor hardware. Furthermore, computational sensing and imaging is increasingly exploiting data-driven and machine learning solutions to enhance performance and develop novel hardware/software co-designed sensing systems. However, in critical scenarios such as medicine or defence and security it is vital that verifiable algorithmic solutions are used, which places restrictions on which machine learning approaches are admissible. Importantly, fully black box machine learning solutions should be avoided. This theme will therefore focus on the development of novel algorithmic and mathematical frameworks to exploit data and machine learning for imaging and sensing within a controlled explainable and verifiable manner. There will be a specific focus on RF and electro-optic/IR sensor modalities.

Sensor and Information Fusion
Sensor networks, sensor fusion and management techniques address key challenges in intelligence, surveillance, target acquisition, and reconnaissance (ISTAR). Opportunities in adaptive data-driven sensor tasking and resource management include adaptive sensor placement, adaptive waveform design to reflect the target reflection characteristics and channel environments, and adaptive sensor selection. Although these problems have solutions in specific use cases, this theme will consider scenarios with broader applications involving multiple heterogeneous sensors on single or multiple cooperative autonomous airborne platforms.

The solutions developed in this should be robust to dynamic and congested environments, adverse weather conditions, and mutual sensor interference. A range of algorithmic and signal processing or machine learning technologies will be considered, as well as specific technical challenges. For example, projects in this theme will consider aspects related to wide area motion imaging (WAMI), position, navigation, and timing issues (PNT); robustness to adversarial attack; sensor fusion and tracking applications; use of kernel and Monte Carlo methods; outlier-robust (and other metrics) messages in belief propagation algorithms; and scheduling in large dynamic networks. Probabilistic and Bayesian frameworks will be preferred to enable uncertainty quantification and management.

Network

Mehrdad Yaghoobi Vaighan

Person: Academic: Research Active

Ian Marshall

Person: Affiliated Independent Researcher

Bill Nailon

Person: Affiliated Independent Researcher

James Hopgood

Person: Academic: Research Active

John Thompson

Person: Academic: Research Active

Dave Laurenson

Person: Academic: Research Active

Stephen McLaughlin

Person: Affiliated Independent Researcher

Geoff Simm

Person: Academic: Research Active

Rémi Gribonval

  • INRIA Institut National de Recherche en Informatique et en Automatique

External person

Ian Proudler

  • University of Strathclyde

External person

Yoann Altmann

  • Heriot-Watt University

External person

Mengwei Sun

  • University of Edinburgh, Scotland

External person

X. Zhao

  • So Methodist Univ, Southern Methodist University, Dept Phys

External person

Pedro A. Gómez

  • Technische Universität München

External person

Pierre Vandergheynst

  • EPFL, Ecole Polytechnique Fédérale de Lausanne

External person

Yves Wiaux

  • EPFL, Ecole Polytechnique Fédérale de Lausanne
  • Heriot-Watt University

External person

Remi Gribonval

  • Ctr Rech INRIA Rennes Bretagne Atlantique

External person

J. Stark

  • Univ Grenoble Alpes, Centre National de la Recherche Scientifique (CNRS), Institut National Polytechnique de Grenoble, Joseph Fourier University, Lab Phys Subatom & Cosmol, CNRS, IN2P3
  • CPPM

External person

Shaun Kelly

  • UoE (The University of Edinburgh) : Student

External person

Zhouye Chen

  • Heriot-Watt University

External person

Chunli Guo

  • Univ Edinburgh, University of Edinburgh, Inst Digital Commun
  • Univ Edinburgh, University of Edinburgh, Joint Res Inst Signal & Image Proc

External person

Sylvain Meignen

  • Université Joseph Fourier

External person

Pascal Frossard

  • Ecole Polytech Fed Lausanne, Swiss Federal Institute of Technology Lausanne, Signal Proc Lab LTS4

External person

Mark D. Plumbley

  • Queen Mary University of London

External person

Stephen McLaughlin

  • Heriot-Watt University

External person

Gian.Franco Piredda

  • Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
  • LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland,
  • Department of Radiology, University Hospital Lausanne (CHUV), Lausanne

External person

Quentin Legros

  • Heriot-Watt University

External person

Marion K Campbell

  • University of Aberdeen
  • NHS Grampian

External person

Reto Meuli

  • Department of Radiology, University Hospital Lausanne (CHUV), Lausanne

External person

Tim Sprenger

  • GE Global Research, Munich

External person

Mohammad Golbabaee

  • IDCOM, University of Edinburgh, Kings Buildings

External person

Gilles Puy

  • Technicolor R and D

External person

Tobias Kober

  • Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
  • LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland,
  • Department of Radiology, University Hospital Lausanne (CHUV), Lausanne

External person

Angela Di Fulvio

  • University of Illinois

External person

Jean-Philippe Thiran

  • LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland,

External person

Tom Hilbert

  • Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
  • LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland,
  • Department of Radiology, University Hospital Lausanne (CHUV), Lausanne

External person

S. Bhattacharya

  • Saha Inst Nucl Phys, Saha Institute of Nuclear Physics
  • Brown University
  • University of Aberdeen
  • Aberdeen Maternity Hospital

External person

Gilles Puy

  • EPFL, Ecole Polytechnique Fédérale de Lausanne

External person

Marc Paff

  • Los Alamos National Laboratory

External person

Julian Tachella

  • Heriot-Watt University

External person

Samarth Varma

  • University of Edinburgh

External person

Nicolas Chetry

  • Queen Mary University of London

External person

Denggao Yao

  • Heriot-Watt University

External person

Roberto Duarte

  • Heriot-Watt University

External person

Sara Pozzi

  • University of Michigan

External person

Di Wu

  • University of Edinburgh

External person

marion menzel

  • Technical University of Munich

External person

W. Haresign

  • Aberystwyth University, Institute of Biological, Environmental and Rural Sciences

External person

Audrey Repetti

  • Heriot-Watt University

External person

L. Bünger

  • SRUC, Scotland’s Rural College

External person

Di Wu

  • University of Edinburgh

External person

pedro gomez

  • Technische Universität Munchen

External person

Mark Sandler

  • Queen Mary University of London

External person

Ebtihal H G Yousif

  • IDCOM, University of Edinburgh, Kings Buildings
  • Institute for Digital Communications (IDCOM), University of Edinburgh

External person

Richard Hodgskin-Brown

  • University of Manchester

External person

R. Roehe

  • SRUC, Anim & Vet Sci Res Grp
  • Scottish Agricultural College
  • Scottish Agr Coll, Sustainable Livestock Syst Grp
  • Scottish Agr Coll, Sustainable Livestock Syst
  • SRUC, Scotland’s Rural College

External person

Carolin Pirkl

  • Technical University of Munich

External person

Pedro Gomez

  • Technical University of Munich

External person

Roberto De Jesus

  • Heriot-Watt University

External person

Alexander Jung

  • Vienna University of Technology

External person

Sankar Andiappa

  • Western Gen Hosp, Edinburgh Canc Ctr, NHS Lothian
  • Western General Hospital

External person

Ahmed Karam Eldaly

  • Heriot-Watt University

External person

S. Wang

  • University of Tartu
  • University of Tartu

External person

Silvia Gazzola

  • University of Bath

External person

Rhea Clewes

  • DSTL Porton Down, Defence Science & Technology Laboratory

External person

James Wright

  • Defence Science and Technology Laboratory

External person

Di Wu

  • University of Edinburgh

External person

Karen Egiazarian

  • Tampere University

External person

Bjoern Menze

  • Technical University of Munich
  • Chair for Process Systems Engineering, Technische Universitat Munchen, Freising, Germany

External person

Y Traonmilin

  • Centre Inria Rennes-Bretagne Atlantique

External person

Gilles Puy

  • Ctr Rech INRIA Rennes Bretagne Atlantique

External person

Guido Buonincontri

  • GE Healthcare, Waukesha, WI, USA.

External person

Chris Duxbury

  • Queen Mary University of London

External person

Shaun Clarke

  • University of Michigan

External person

Aongus McCarthy

  • Heriot-Watt University

External person

Gerald S. Buller

  • Heriot-Watt University

External person

G. C. Márquez

  • ABS Global Inc.
  • Virginia Tech

External person

Andy Stove

  • Thales UK

External person

Ana Casado

  • Univ Edinburgh, University of Edinburgh, Ctr Clin Brain Sci

External person

Marion Menzel

  • GE Global Research, Munich

External person

Rhea Clewes

  • DSTL Porton Down, Defence Science & Technology Laboratory

External person