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1 | 1 | --- |
2 | 2 | name: Simon Roy |
3 | | -role: msc |
4 | | -title: Master's Student |
| 3 | +role: phd |
| 4 | +title: PhD Student |
5 | 5 | photo: simon-roy.jpg |
6 | | -short_bio: Ad astra per scientiam — working on LLM-driven mission planning and vision-based precision landing for autonomous robots. |
| 6 | +short_bio: Ad astra per scientiam — working on world models, action compression for world models, and humanoid and space robotics. |
7 | 7 | supervisor: Giovanni Beltrame |
8 | | -tags: [Mission Planning, LLMs, Aerial Robotics] |
| 8 | +tags: [World Models, Action Compression, Humanoid Robotics, Space Robotics] |
9 | 9 | email: simon-7.roy@polymtl.ca |
10 | 10 | github: "" |
11 | 11 | linkedin: https://www.linkedin.com/ |
12 | 12 | order: 1 |
13 | 13 | --- |
14 | 14 |
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15 | | -Simon Roy is a Master's student in computer engineering at Polytechnique |
| 15 | +Simon Roy is a PhD student in computer engineering at Polytechnique |
16 | 16 | Montréal and Mila, supervised by Professor Giovanni Beltrame. He received his |
17 | 17 | Bachelor's degree with honors in Software Engineering from the École de |
18 | 18 | technologie supérieure (ÉTS) in December 2024. He is interested in autonomous |
19 | 19 | robotics and space exploration. |
20 | 20 |
|
21 | 21 | ## Current Work |
22 | 22 |
|
23 | | -- **LLM-driven mission planning** — using large language models to translate |
24 | | - high-level objectives into structured, adaptive task sequences for autonomous |
25 | | - robots under real-world constraints. |
26 | | -- **Precision landing for aerial robotics** — vision-based, markerless |
27 | | - algorithms that let drones identify, track, and land on arbitrary targets with |
28 | | - sub-meter accuracy. |
29 | | -- **Latent-space world modeling** — compact learned representations of |
30 | | - environmental dynamics for real-time planning and decision-making. |
| 23 | +- **World models** — learned representations of environmental dynamics for |
| 24 | + planning and decision-making in autonomous systems. |
| 25 | +- **Action compression for world models** — compact encodings of action spaces |
| 26 | + that make world-model-based planning tractable in real time. |
| 27 | +- **Humanoid robotics** — applying world models and compressed action spaces to |
| 28 | + planning and control for humanoid robots. |
31 | 29 |
|
32 | 30 | ## Contact |
33 | 31 |
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