resume
A selection of my experience.
Basics
Name | Daniele Grandi |
grndnl@gmail.com | |
Url | https://www.linkedin.com/in/grndnl/ |
Summary | Machine Learning + Design Research |
Education
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2022.01 - 2023.12 -
2011.08 - 2015.05
Work
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2024.11 - Present San Francisco, CA /
RemotePrincipal Research Scientist
Autodesk
Researching machine learning applications in data-driven design using LLMs, VLMs, and GNNs. Collaborating with MIT, UC Berkeley, and CMU on datasets and benchmarks.
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2019.03 - 2024.11 San Francisco, CA /
RemoteSr. Research Engineer
Autodesk
Focused on combining mechanical engineering with machine learning, leveraging knowledge graphs and semantic technologies to extract best practices from CAD data.
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2015.09 - 2019.03 San Francisco, CA /
London, UKDesign Engineer
Autodesk
Worked on generative design platforms, creating demonstrators and integrating end-user feedback into development.
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2015.05 - 2016.03 San Francisco, CA
Additive Manufacturing Engineer
Project BAM
Streamlined additive manufacturing processes, designed facility layout, and supported customer part redesign for AM.
Skills
Programming | |
Python | |
C++ | |
MATLAB | |
Visual Basic |
Data Science | |
Pytorch | |
Tensorflow | |
Keras | |
Scikit-learn | |
R | |
SQL | |
Neo4j | |
GDL | |
GNN | |
NLP |
CAD | |
Autodesk Expert Elite | |
SolidWorks Certified Professional | |
NX | |
Creo (Pro/E) |
Simulation | |
NASTRAN | |
Siemens Femap | |
Autodesk Simulation Mechanical | |
CFD |
Optimization | |
Generative Design/TopOpt | |
ADSK Within | |
Altair Optistruct | |
Solidthinking Inspire |
Manufacturing | |
Additive Manufacturing | |
Machine Shop Expertise |
Projects
- 2021 - 2023
ARCS | AI-assisted Knowledge Graph Design
- Machine Learning (ML)
- Graph Neural Networks (GNN)
- 2018 - 2020
Autodesk, Project Dreamcatcher | NASA JPL Lander
- Topology Optimization
- Simulation
- Design and Manufacturing
Publications
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2025 Designqa: A multimodal benchmark for evaluating large language models’ understanding of engineering documentation
Journal of Computing and Information Science in Engineering
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2025 Evaluating large language models for material selection
Journal of Computing and Information Science in Engineering
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2024 HG-CAD: hierarchical graph learning for material prediction and recommendation in computer-aided design
Journal of Computing and Information Science in Engineering
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2023 Conceptual design generation using large language models
ASME IDETC/CIE