Dr Jaime Zabalza

Strathclyde Chancellor's Fellow

Electronic and Electrical Engineering

Personal statement

Jaime is a Strathclyde Chancellor's Fellow working closely with the Advanced Nuclear Research Centre (ANRC) since September 2022.

He is interested in the creation of new artificial intelligence tools to solve real-world industrial challenges. 

Jaime has been within the Centre for Signal and Image Processing (CeSIP) since 2011 in different positions including: MSc and PhD student, Research Assistant, Associate, and Fellow. Previously, he took a number of research positions at the Universitat Jaume I, Universitat Politecnica de Valencia and the Energy Technological Institute in Spain.

Expertise

Has expertise in:

    Artificial Intelligence

    Machine Learning

    Digital Signal Processing

    Hyperspectral Imaging

    Software Engineering and Robotics

    MATLAB, C/C#/C++

Prizes and awards

IEEE Brain Data Bank Challenges and Competitions
Recipient
8/7/2018
IEEE Brain Data Bank Challenges and Competitions
Recipient
31/10/2017
IET V&I Best PhD Thesis Award (only one in UK per year)
Recipient
12/2016

More prizes and awards

Qualifications

PhD in Electronic and Electrical Engineering (2012-2015)

MSc in Electronic and Electrical Engineering (2011-2012)

MAS in Electrical Technology (2008-2010)

MEng in Industrial Engineering (2000-2005)

PGCert in Researcher Professional Development (2015)

Spanish Chartered Industrial Engineer (COIICV - 5288)

Publications

Intelligent characterisation of space objects with hyperspectral imaging
Vasile Massimiliano, Walker Lewis, Dunphy R David, Zabalza Jaime, Murray Paul, Marshall Stephen, Savitski Vasili
Acta Astronautica (2022)
https://doi.org/10.1016/j.actaastro.2022.11.039
X-ray classification of Special Nuclear Materials using image segmentation and feature descriptors
Campbell Andrew, Zabalza Jaime, Murray Paul, Marshall Stephen, Myres Gareth, Bernard Robert, Cockbain Neil, Offin Douglas
Canadian Nuclear Society - Disruptive Innovative Emerging Technologies 2022 (2022)
A comparative study of loss functions for hyperspectral SISR
Aburaed Nour, Alkhatib Mohammed Q, Marshall Stephen, Zabalza Jaime, Al Ahmad Hussain
30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings 30th European Signal Processing Conference, EUSIPCO 2022 European Signal Processing Conference Vol 2022-August, pp. 484-487 (2022)
SISR of hyperspectral remote sensing imagery using 3D encoder-decoder RUNet architecture
Aburaed Nour, Alkhatib Mohammed Q, Marshall Stephen, Zabalza Jaime, Ahmad Hussain Al
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium 2022 IEEE International Geoscience and Remote Sensing Symposium International Geoscience and Remote Sensing Symposium (IGARSS) Vol 2022-July, pp. 1516-1519 (2022)
https://doi.org/10.1109/igarss46834.2022.9883578
3D expansion of SRCNN for spatial enhancement of hyperspectral remote sensing images
Aburaed Nour, Alkhatib Mohammed Q, Marshall Stephen, Zabalza Jaime, Al Ahmad Hussain
2021 4th International Conference on Signal Processing and Information Security, ICSPIS 2021 4th International Conference on Signal Processing and Information Security, ICSPIS 2021 2021 4th International Conference on Signal Processing and Information Security, ICSPIS 2021, pp. 9-12 (2021)
https://doi.org/10.1109/ICSPIS53734.2021.9652420
Folded LDA : extending the linear discriminant analysis algorithm for feature extraction and data reduction in hyperspectral remote sensing
Fabiyi Samson Damilola, Murray Paul, Zabalza Jaime, Ren Jinchang
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol 14, pp. 12312-12331 (2021)
https://doi.org/10.1109/JSTARS.2021.3129818

More publications

Teaching

Jaime is a lecturer in the EE270/EM270 class (Semester 1) since 2022-23, as well as a tutor in the Small Group Seminars since 2018-19. He is also part of Strathclyde's Chinese Teaching Agreement, where he delivers lectures in the class "Signals and Systems".

Research interests

Signal and image processing, hyperspectral imaging and machine learning for artificial intelligence in a wide range of applications, focusing on the Nuclear Sector.

Professional activities

MPhil Convener
Examiner
1/2020
Remote Sensing (Journal)
Peer reviewer
2020
Remote Sensing (Journal)
Guest editor
2020
Beijing University of Technology
Visiting researcher
11/4/2019
Northeast Electric Power University
Visiting researcher
1/4/2019
Demos on robotically enabled sensing and novel robot control for dynamic environments
Consultant
12/3/2019

More professional activities

Projects

NNL Gamechangers GC_142 Phase 5 (Linked to 191761) Image Processing for Enhanced Visualisation
Murray, Paul (Principal Investigator) Marshall, Stephen (Co-investigator) West, Graeme (Co-investigator) Zabalza, Jaime (Co-investigator)
18-Jan-2021 - 31-Jan-2022
Image Processing for Enhanced Visual Inspection of Nuclear Waste Packages GC142 Phase 2
Murray, Paul (Principal Investigator) Marshall, Stephen (Co-investigator) Ren, Jinchang (Co-investigator) West, Graeme (Co-investigator) Zabalza, Jaime (Research Co-investigator)
01-Jan-2020 - 30-Jan-2021
Remote Inspection of SNM cans GC_253
Murray, Paul (Principal Investigator) MacLeod, Charles Norman (Co-investigator) Marshall, Stephen (Co-investigator) Ren, Jinchang (Co-investigator) Zabalza, Jaime (Co-investigator)
01-Jan-2020 - 31-Jan-2020
Oilfield data processing
Murray, Paul (Principal Investigator) Campbell, Andrew John (Co-investigator) Marshall, Stephen (Co-investigator) Ren, Jinchang (Co-investigator) Zabalza, Jaime (Co-investigator)
22-Jan-2019 - 31-Jan-2019
Flexible and Intelligent Path Planning and Control of Industrial Robots towards Autonomous Hot Forging in the Digital Manufacturing Age
Yan, Yijun (Researcher) Mineo, Carmelo (Co-investigator) Yang, Erfu (Principal Investigator) Mehnen, Jorn (Co-investigator) Zabalza, Jaime (Researcher) Fei, Zixiang (Researcher) Wong, Cuebong (Researcher)
The proposed project aims to enhance the autonomous manufacturing capability of UK industry in metal forming and forging. The project brings together two departments of the University of Strathclyde, namely DMEM and EEE. It augments this knowledge with the experts of Strathclyde’s global strategic partner Nanyang Technology University (NTU, Singapore). With Industry 4.0 being currently widely acknowledged as a key driver of industrial advancement, a strong technologic shift has become apparent within industry to move towards both, more intelligence and more autonomy. Currently, hot forging and forming has benefitted only little from this shift beyond traditional automation. There is a vast opportunity to systematically transform the inherently challenging technologies, namely forming and forging into truly smart and flexible manufacturing systems.
The AFRC offers an outstanding practical background for the applied transformation of Industry 4.0 theories. This project aims at delivering practical demonstrators at TRL 6 through implementing advanced knowledge into intelligent robot behaviour and simulation environments for robotic manipulation and flexible automation into the hot forging area considering the “living” and “dirty” environment of such industries, which requires the consideration of humans, hazardous, dynamic, hot and noisy conditions which did not experience much smart automation yet.
01-Jan-2017 - 31-Jan-2018

More projects

Address

Electronic and Electrical Engineering
Royal College Building

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