Department of
Mechanical, Materials and Manufacturing Engineering
 

Image of Ian Maskery

Ian Maskery

Associate Professor, Faculty of Engineering

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Biography

Studied Physics between 2005 and 2009 at the University of York, obtaining an M.Phys. degree with first class honours.

Joined the Magnetic X-ray Scattering Group of the Department of Physics at the University of Warwick in 2009. Worked on a project to investigate the spin momentum densities of several novel magnetic materials using the experimental technique of magnetic Compton scattering. Thesis title: Spin densities in 4f and 3d magnetic systems. Ph.D. supervisors: Jon Duffy and Gavin Bell.

Joined the Additive Manufacturing Research Group at the University of Nottingham in 2013. I worked as a post-doctoral research fellow on projects to develop strong, lightweight aluminium components with internal lattice structures by selective laser melting (SLM). In the last few years I have focussed on design-for-AM methods, including cellular structure, or 'lattice', generation. In October 2021 I became Assistant Professor in the Department on Mechanical, Materials and Manufacturing Engineering.

Teaching Summary

Teaching at Nottingham

  • Advanced Topics in Additive Manufacturing - module convener.
  • Advanced Characterisation and Metrology - module convener.
  • Fundamentals of Additive Manufacturing - contributor.
  • Programming, Professional & Laboratory Skills - Matlab teacher.
  • Engineering Design and Design Project - design tutor.
  • Additive Manufacturing & 3D-Printing - contributor.

In addition to the above, I am also Year 2 Lead for Mechanical and Manufacturing Engineering courses.

Research Summary

Currently working on the EPSRC-funded ASSAM project (AI Synthesis of Structures via Additive Manufacturing) - EP/X016854/1. The project will examine the training of neural networks with hierarchical… read more

Selected Publications

Current Research

Currently working on the EPSRC-funded ASSAM project (AI Synthesis of Structures via Additive Manufacturing) - EP/X016854/1. The project will examine the training of neural networks with hierarchical natural materials (cellular bone, for example) to develop new solutions for structural engineering problems.

Department of Mechanical, Manufacturing and Materials Engineering

The University of Nottingham
University Park
Nottingham, NG7 2RD


telephone: +44 (0) 115 95 14081