Dr Mike Edwards

Research Highlights

1. Thomas, L., Edwards, M., Capsey, A., Rahat, A., & Roach, M. (2022). Deep Visual Place Recognition for Waterborne Domains. In 2022 IEEE International Conference on Image Processing (ICIP). 16-19th October Bordeaux, France.IEEE.

   https://doi.org/10.1109/icip46576.2022.9897962, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60685

   https://ieeexplore.ieee.org/xpl/conhome/9897158/proceeding
2. Edwards, M., Edwards, M., & Xie, X. (2014). Footstep pressure signal analysis for human identification. In Int'l Conf. BioMedical Engineering and Informatics (pp. 307-312). 7th International Conference on Biomedical Engineering and Informatics.

   https://doi.org/10.1109/BMEI.2014.7002790, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa20982
3. Edwards, M., Edwards, M., Deng, J., & Xie, X. (2016). From pose to activity: Surveying datasets and introducing CONVERSE. Computer Vision and Image Understanding, 144, 73-105.

   https://doi.org/10.1016/j.cviu.2015.10.010, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa26730
4. Edwards, M., Deng, J., Xie, X., & Edwards, M. (2016). Combining Stacked Denoising Autoencoders and Random Forests for Face Detection. Advanced Concepts for Intelligent Vision Systems (pp. 349-360).

   https://doi.org/10.1007/978-3-319-48680-2_31, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa32104
5. Edwards, M., Deng, J., & Xie, X. (2017). Labeling subtle conversational interactions within the CONVERSE dataset. In 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) (pp. 140-145). IEEE.

   https://doi.org/10.1109/percomw.2017.7917547, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa33105

All Research

• Visual Analytics for Explainable Graph-Based Machine Learning (current)

  PhD

  Other supervisor: Dr Daniel Archambault

• Human Interfaces with Machine Learning Recognition Systems (current)

  PhD

• Reinforcement Learning Invariants from State Space Observations (current)

  PhD

  Other supervisor: Prof Xianghua Xie

  Other supervisor: Dr Phillip James

• Machine Learning for geospatial placement (current)

  PhD

  Other supervisor: Prof Mark Jones

  Other supervisor: Dr Sarah Roberts

• Introducing Explainability to Image Based Place Recognition for AI Assisted Shoreline Navigation (current)

  PhD

  Other supervisor: Dr Matt Roach

  Other supervisor: Dr Alma Rahat

• Geospatial machine learning in safety critical systems (current)

  PhD

  Other supervisor: Prof Mark Jones

• Irregular Domain Deep Learning (current)

  PhD

  Other supervisor: Dr Gary Tam

  Other supervisor: Prof Xianghua Xie

• CS-150 Concepts of Computer Science

  This module gives an overview of some of the main principles underlying computers and computing from both a theoretical and an applied point of view. Following a brief history of computers and software an introduction to the representation of data and the basic components of a computer will be given. Students will be introduced to the principles of programming at assembly language level. Further topics include simple algorithm analysis, operating systems, file systems, computer networks, and the world wide web. A brief discussion on the limitations of computing is also given. The module is accessible and relevant to students of all disciplines who wish to learn about, or reinforce their understanding of, computers and computer science

• CS-165 Introduction to Data Science

  We live in the age of data: it is ubiquitous in modern life. However, data in itself cannot inform or inspire. We need to ¿do science¿ with the data to extract knowledge and actionable insights. In this module, we will explore scientific methods and processes that make data so valuable to us and society and gain an insight into the world of practical data science and its challenges. We will also cover the ethical issues relating to data.