Alasdair Gray is a research fellow and computational design specialist with nine years' experience applying simulation and optimization to aerospace and automotive problems, currently based at the University of Michigan MDO Lab. He completed a PhD focused on multidisciplinary design optimization after an MSc at Delft, and has practical hands-on experience from Formula Student teams and industry roles including propulsion engineering at Lilium. Skilled in FEM, CFD, topology optimization and automation, he blends rigorous academic research with prototyping—designing, manufacturing and testing components from carbon monocoques to 3D‑printed parts. Notably, he has taught graduate CFD, built live Jupyter-based course materials that won a College of Engineering teaching prize, and maintains a persistent focus on making optimization tools transferable to real-world design cycles.
9 years of coding experience
5 years of employment as a software developer
Portobello High School
MSc, Aerospace Engineering, Grade Average: 8.93/10, MSc, Aerospace Engineering, Grade Average: 8.93/10 at Delft University of Technology
Master of Engineering (MEng), Mechanical Engineering, 1st Class Honours, Grade Average 77%, equivalent 3.93 GPA, Master of Engineering (MEng), Mechanical Engineering, 1st Class Honours, Grade Average 77%, equivalent 3.93 GPA at The University of Edinburgh
Doctor of Philosophy - PhD, Aerospace Engineering, Doctor of Philosophy - PhD, Aerospace Engineering at University of Michigan
Education Abroad Program, Mechanical Engineering, 3.80 GPA, Education Abroad Program, Mechanical Engineering, 3.80 GPA at UC Berkeley College of Engineering
This repository is for an educational exercise that is a part of NERS570 course of the Fall 2022 semester at the University of Michigan
Contributions:37 reviews, 59 commits, 8 PRs in 24 days
pythonfalljavascriptmichigansemester
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Alasdair Gray - Research Fellow at University of Michigan MDO Lab