Peter Rosso BEng
Peter is a postgraduate researcher in his last year of a PhD.
Graduating from the University of Bristol with a bachelors’ in Mechanical Engineering, he then went on to work on a feasibility study sponsored by Airbus focused on the analysis of engineering drawings. He started his PhD in 2017 within the Design and Manufacturing Futures Lab, working on refactoring of CAD models.
Outside of engineering, he is a keen climber and mountaineer. Mountain Leader trained, and he is currently on his Rock Climbing Instructor qualification. Peter’s love for climbing is fuelled from going climbing in the local Avon Gorge, and mountaineering in the Alps where he grew up.
- Data Analysis
- CAD Modelling
Editability of CAD models – reDesign with Refactoring – The main area of research and topic of Peter’s Thesis
- Investigating and Characterising Variability in CAD Modelling and its Potential Impact on Editability: An Exploratory Study
- Towards integrated version control of virtual and physical artefacts in new product development: inspirations from software engineering and the digital twin paradigm
- Investigating and characterising variability in CAD modelling: An overview
- From orthographic drawings to editable models of simple solid using “Reconstruction-Recomposition” coupled with feature recognition
- Orthographic drawings minting: testing for indeterminate solid models caused by underrepresentation
- CAD Variability: an overview. - I have been working on justifying the need for refactoring in CAD models. The results of this analysis will be presented at the CAD'20 conference which will be held on ZOOM this coming July due to COVID outbreak. Variability in CAD modelling invoked commands in building the same CAD models.… Read More
- New Conference Papers – International Conference on Geometry and Graphics - In August I will be presenting at the 18th International Conference on Geometry and Graphics (ICGG), held in Milan, Italy. The peer-reviewed papers which have been accepted are: From Orthographic Drawings to Editable Models of Simple Solids using "Reconstruction-Recomposition" coupled with Feature Recognition: explores reconstruction of parametric models using Fusion… Read More