Dr Raul Ochoa Cabrero

My profile

Biography

I am a mathematician by training having received my BSc in Applied Mathematics (2009-2014) with honours from the Autonomous University of San Luis Potosi, in Mexico. I completed an MPhil in Materials Science at the University of Manchester (2018) before receiving my doctorate in Biomedical Materials from the same institution (2022).

I have worked as a lecturer at the UASLP in Mexico and now as a tutor at the Department of Engineering at Manchester Met where I received a distinction in my PGCert in Learning, Teaching and Assessment in HE (including fellowship of advanceHE). I am passionate for teaching and developing active, student-centred environments for learning with special interest in situated learning approaches and digitally enhanced education.

I am Departmental lead integrating AI in STEM education and have ambitious plans incorporating AI tools in our future-focused curriculum, particularly generative AI tools for engineering design or machine learning approaches in engineering applications.

Interests and expertise

My research is centred around the development of novel mathematical approaches to scaling, focusing on the modelling of scale or size effects in physical and non-physical systems, predominantly in the field of biomaterials. My expertise lies in modelling and designing experiments across multiple scales using additive manufacturing methods and computer-assisted design tools, including Solidworks, Fusion 360, Cura for slicing, generative design with diffusion models (Stable Diffusion, Firefly, Photoshop) and programming novel algorithms for scaling using Python. I have extensive experience with mathematical modelling and statistics, particularly AI and machine learning, computational simulations (stochastic and FEA), biomechanics, and rigorous mechanical experimentation and material characterisation of advanced manufactured materials.

My research interests are currently focused on investigating uncertainty quantification at multiple scales, size effects in advanced materials, the scaling of empirical laws in biological systems, and machine learning applications in smart systems. Collaborations include researchers in the Department of Engineering, the Institute of Sport, the Department of Life Sciences, and external collaborators at the University of Manchester, Queen’s Mary University and UASLP in Mexico where I have been an invited speaker at various seminars.

Teaching

I recognise that teaching is an interrelational process and recognise the value each one of us bring to the subject discipline. I am passionate about situated learning, learning by doing in a community of practice through legitimate participation. Therefore, I consider my role as facilitator and aim to foster active, democratic and learner-centred environments. I recognise the importance of digitally enhanced education, innovating our teaching delivery with flexible and blended approaches to learning.

I am enthusiastic about the future of engineering education and practice in the context of new technologies, particularly artificial intelligence (generative AI) and virtual reality, which are becoming essential drivers of productivity and creative outputs. I am currently leading the strategic implementation of these technologies in our future-focused curriculum and innovating with sector-leading practices.

Research outputs

Journal Articles

  • Davey, K. and Ochoa-Cabrero, R., (2023). “Extended finite similitude and dimensional analysis for scaling”. Journal of Engineering Mathematics, https://doi.org/10.1007/s10665-023-10296-1.
  • Ochoa-Cabrero, R., Alonso-Rasgado, T., and Davey, K., (2022).  “A two-experiment approach to scaling in biomechanics”. ASME J. Biomech. Eng., 144 (8), https://doi.org/10.1115/1.4053627.
  • Ochoa-Cabrero, R., Alonso-Rasgado, T., and Davey, K., (2020). “Zeroth-order finite similitude and scaling of complex geometries in biomechanical experimentation”. Journal of the Royal Society Interface, 17(167), June. https://doi.org/10.1098/rsif.2019.0806.
  • Ochoa-Cabrero, R., Alonso-Rasgado, T., and Davey, K., (2018). “Scaling in biomechanical experimentation: a finite similitude approach”. Journal of the Royal Society Interface, 15(143), June, https://doi.org/10.1098/rsif.2018.0254.

Conference Papers

  • Danowski, P., Ekpo, S., Ijaz, M., Raza, U., Ochoa-Cabrero, R. (2024) “Deep Learning-enabled Smart Wearables to Assist People with Autism Spectrum Disorder in Dynamic Environments.” Adaptive and Sustainable Science, Engineering and Technology (ASSET) Conference [Published by Springer Nature].

In Preparation/Submitted

  • Davey, K., Ochoa-Cabrero, R., Ali, Z. and Xu, J. “The scaling of stochastic physical systems with applications in electrodynamics”.
  • Ochoa-Cabrero, R., Duncan, O. and Davey, K., “Finite similitude of the micro-continua”.
  • Ochoa-Cabrero, R. and Davey, K.,.  “Extended finite similitude solves the scaling of empirical laws: metabolism and growth”.