Profile
I am a PhD candidate in Aerospace Engineering at Queen Mary University of London, where I study damage-tolerant ultralightweight mechanical metamaterials for future air transportation. My current work focuses on quasi-distorted lattice architectures, adaptive finite-element workflows, and machine-learning-guided structural optimization.
Before starting the doctorate, I completed a First Class BEng in Mechanical Engineering at Queen Mary. My undergraduate dissertation explored the prediction of aerofoil aerodynamic coefficients using machine learning, and that same interest in computation still shapes the way I approach mechanics, simulation, and design.
Having grown up across Washington, Jerusalem, Rome, Brussels, and London, I tend to bring an international and interdisciplinary outlook to research. Alongside my PhD work, I teach engineering modules, work with data and software, and keep a close interest in how technical ideas can be explained clearly and built carefully.
Publications
Paper on quasi-disordered lattice metamaterials and failure response
Niccolò Forte
Current publication track stemming from doctoral work on lightweight mechanical metamaterials, quasi-disordered architectures, and damage-tolerant structural behavior.
Russell Binion Research Symposium presentation
Research symposium contribution - 21 April 2026
Presented ongoing doctoral research on lattice metamaterials, simulation workflows, and data-driven optimization methods.
ICEFA-X conference presentation
Tenth International Conference on Engineering Failure Analysis
Shared early doctoral work on engineering failure analysis and quasi-distorted lattice systems at ICEFA-X, held 7-10 July 2024.
Research and Technical Experience
Damage-tolerant ultralightweight mechanical metamaterials
Queen Mary University of London - PhD research
Developing design pathways for the manufacture of quasi-distorted lattice metamaterials, with emphasis on topology, shape, and size optimization through physics-informed machine learning and structural mechanics.
Teaching assistant across engineering modules
Queen Mary University of London
Supporting teaching in fluid mechanics, CFD, solid mechanics, FEA, thermodynamics, computational modelling, and simulation-focused engineering coursework.
Data Science Intern
Red Bull
Worked on market estimation, e-commerce evaluation, and commercial analytics, strengthening the data and modelling side of my technical background.
Machine learning for aerofoil coefficient prediction
Queen Mary University of London - BEng dissertation
Built predictive models for experimental aerodynamic coefficients, combining numerical thinking, engineering judgement, and applied machine-learning methods.
Software and Digital Work
niccoloforte.com
Personal website repository
Building and maintaining my personal website as a minimal research-facing home for publications, technical writing, and public-facing academic information.
IT and Web Developer
Dante Alighieri Project Foundation
Worked on website development, SEO, and digital communication for a non-profit foundation, combining technical implementation with user-facing clarity.
Freelance UI and UX Tester
Prototype and product testing
Tested early software and product experiences for companies including Meta, Hyundai, and SumUp, with a focus on usability, product feel, and structured feedback.
Education
PhD Candidate in Aerospace Engineering
Queen Mary University of London
Thesis: Damage Tolerant Ultralightweight Mechanical Metamaterials for Future Air Transportation
2023-present
BEng Mechanical Engineering - First Class Honours
Queen Mary University of London
Dissertation: Predictive modelling of experimental aerofoil aerodynamic coefficients using machine learning
2020-2023
Secondary School Diploma - AP International Diploma
American Overseas School of Rome
Strong academic base in calculus, physics, chemistry, economics, and languages
2015-2020
Writing
Notes in progress on metamaterials, modelling, engineering judgement, and the small decisions that make technical work more reliable.
What changes when lattice disorder becomes a design variable
A short note on distorted lattice architectures, robustness, and what makes disorder useful rather than merely irregular.
Making finite-element workflows easier to trust
Reflections on mesh choices, sampling strategy, and the difference between a model that runs and a model that teaches you something.
Teaching simulation without making it mysterious
Notes on explaining computational tools to students without flattening the real engineering judgement underneath them.
Personal Contact Card
Niccolò Forte
PhD Candidate in Aerospace Engineering
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