Alexandre Carlhammar

Co-Founder. Assemble the World.

Problem: Every production line is a semi-custom integration project. Low-volume, high-mix production can't amortize it.

Led research on manufacturing cells that reconfigure in hours. Learned manipulation (RL, VLA models, diffusion policies) on real robots, for electromechanical component production. Thesis: The Trunk, Not The Leaf.

Founding engineer. End-to-end: concept through flight test. Ballistic launch, 300+ km/h sustained flight.

Built: Full-stack GNC for GNSS-denied autonomous flight and precision engagement. Multi-sensor fusion (IMU, baro, RGB/IR cameras). RL-based control modules. Airframe, wing structures, propulsion validation via CFD and bench testing.

Closed weekly build-test-fly loops in Mojave. Co-built the founding team. Co-led early fundraising.

Entered with zero defense background. Conducted 120+ interviews across government, industry, and research to isolate actual technical constraints. Iterated via prototypes as probes, presenting rough systems to experts to find what was wrong, missing, or unrealistic.

Awarded $80K by the Defense Innovation Unit to build and deploy a prototype.

AI models that learn orbital physics and multi-satellite coordination for autonomous operations. High-fidelity simulation on open-source propagators, VAEs for physically consistent scenario generation.

Path planning for Blue Origin's 2026 rover mission at the lunar south pole. SLAM-coupled planner producing sun-synchronous traverses between key sites. 3D terrain models (NeRF, Gaussian Splats) trained on lunar DEMs and orbital imagery. Real-time planning validated hardware-in-the-loop.

Won NASA's Lunar Autonomy Challenge. [Stanford announcement]

Multi-agent LLM systems for IBM's enterprise clients. RAG with semantic chunking and query rewriting, orchestrated on AutoGen.

Led 10 engineers across Europe through the final deployment push. Clinical-report system shipped into Pfizer's production environment.

Problem: Deploying software to satellites required custom integration per mission. No standard runtime, no shared storage, no portability.

Built: OS-level abstraction for satellites—containerized app deployment across constellations, S3-compatible distributed storage, data relay through intermediary satellites, sensor virtualization.

Deployed on ISS (Nov 2024). Upcoming NASA mission (Oct 2025). Grants from Swedish Space Agency and NASA.

Problem: Multi-satellite mission scheduling is NP-hard. Traditional solvers take weeks per iteration.

Self-taught deep RL over winter break. Convinced Airbus to share their high-fidelity orbital simulator.

Built: RL policies that replace combinatorial search with learned inference. Feasible plans in seconds.

Cut planning time from weeks to hours. Led first undergraduate workshop at AMLD 2024 (50+ attendees). [recap]