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)
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
Royal College Building
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