Rodrigo Schmitt
The cratered lunar surface with Earth rising over the horizon

Three pillars: Astrodynamics, Deep Learning & AI, and Design–Build–Test.

Artemis-era mission design, computer-vision navigation, and hands-on hardware.

One small step, many systems

Projects

What, how and why? Space exploration is entering a new operational era: the Artemis program is returning humans to the Moon, and commercial ventures are rewriting the economics of cislunar logistics. My work sits at the intersection of these forces — designing mission architectures through Generative AI and Explainable AI, building computer vision navigation systems for spacecraft rendezvous, and contributing to the hardware systems that make it all real. The following pillars define my technical expertise.

Illustration of the solar system

Astrodynamics

The motion of natural and artificial objects in space — from preliminary orbit determination for Brazilian satellites to Artemis-era mission architectures in the CR3BP.

  • Interplanetary trajectory design
  • Rendezvous & Proximity Operations
  • Computer vision-based navigation
  • Multi-body dynamics & CR3BP
  • In-situ resource utilization
Abstract artificial intelligence visualization

Deep Learning & AI

Generative design of space systems via Reinforcement Learning, Explainable AI for mission architecture trade-offs, and neural networks for spacecraft navigation and transfer optimization.

  • Reinforcement Learning for design
  • Explainable AI (XAI)
  • Generative Design & System-of-Systems
  • Computer Vision & SE(3) Dynamics
  • Deep Learning Mission Design
Multiphysics engineering simulation

Design, Build & Test

Hands-on engineering: carbon-fiber rocket structures with Project Jupiter, LIDAR-drone integration for Mars EDL research at MDRS, and the RocketPy flight simulator.

  • Topological optimization
  • Multi-physics modeling
  • Design space exploration
  • Additive manufacturing
  • Industry 4.0

Vibe Coding Projects

Side projects built end-to-end with an AI pair programmer (Claude Code): I set the problem, the architecture and the quality bar, and the code gets written in conversation. Each one is a working product with its own repository, not a mock-up.

Neuro Compass results: ADHD, autism and OCD scores out of 100 above a trait fingerprint of sub-dimension bars

Neuro Compass

A private, bilingual (EN / PT-BR) self-reflection quiz for ADHD, autistic and OCD traits, with every formula and research source on show. Not a diagnosis.

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Cooking Daddy Cook mode: a step photo of rice and a saucepan beside instructions with ingredients in green and tools in amber, and a timer

Cooking Daddy

AI-generated, meal-kit-style recipe cards rescaled to the portions you actually eat, with nutrition derived from your own body stats.

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Show Me The Money mission briefing dashboard with portfolio metrics and monthly moves

Show Me The Money

A quantitative portfolio cockpit: regime detection, GARCH risk, ML signals, an optimizer and a monthly emailed briefing.

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Ohara feed for a sample researcher: a greeting with the count of new papers and paper cards that each say why they were picked

Ohara

Reads a researcher's CV and profiles, then surfaces state-of-the-art papers and media matched to what they are ready to learn next.

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Resonance Rings playing a demo track: concentric rings on black, one per instrument, with lit note segments

Can I See The Music

Six rings of light, one per instrument: drop a song and watch who is playing what, with notes transcribed from separated stems.

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Plans and pricing for the apps.