Alessandro Palmas 🚀
Alessandro Palmas

Senior AI/ML Research Engineer

LawZero - Montreal
Artificial Twin

About Me

I’m an applied AI/ML research engineer with 15+ years of experience building intelligent systems that combine foundation models, reinforcement learning, multimodal AI, and high-fidelity simulation. My work bridges foundational research and production-grade solutions across aerospace, defense, robotics, and gaming.

Currently part of the core research and engineering team at LawZero, a non-profit AI lab in Montreal led by Yoshua Bengio, I focus on advancing foundation models, reasoning architectures, and safe-by-design AI.

I’m passionate about combining foundation model, embodied learning, RL, and multimodal AI to tackle complex real-world challenges, designing systems that understand and reason about the world rather than simply act in it.

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Interests
  • Foundation Models
  • Reinforcement Learning
  • Embodied / Physical AI
Experience
Education

  • MSc by Research (Post Graduate) Space Engineering

    University of Glasgow

  • MSc AeroSpace Engineering

    Turin Polytechnic

  • MSc Space Engineering

    Milan Polytechnic

  • Multidisciplinary International Program

    Alta Scuola Politecnica

  • BSc Aeronautical and Space Engineering

    Turin Polytechnic

Open Source Projects

Building is the fastest way to learn.

✨ Coming Soon: Adversarial RL for LLM, Specultive Decoding, Triton Kernels, and more ...
🔀 Fast Deep RL on GPU: Adding Multi-Discrete Actions to RSL-RL Library
🛡️ Reinforcement Learning for Decision-Level Interception Prioritization in Drone Swarm Defense
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Experience Summary

  1. Senior AI/ML Research Engineer

    LawZero - Montreal • Permanent Full-time
    Core member of the research and engineering team at LawZero, a non-profit AI research lab led by Yoshua Bengio, advancing safe, transparent, and interpretable AI systems that reason about the world.
    Skills: C++ · Python · PyTorch · vLLM · Docker · Foundation Models · Large Language Models (LLM) · Generative Flow Networks

  2. Senior AI/ML Research Engineer

    Ubisoft La Forge - Montreal • Permanent Full-time
    Built and deployed advanced Deep RL systems for AAA games, including scalable multi-agent and curriculum-based algorithms. Led cross-site development of a distributed training pipeline and integrated AI models into proprietary engines for NPCs and simulations.
    Skills: C++ · Python · PyTorch · Deep Reinforcement Learning · Large Language Models (LLM) · Docker · Reinforcement Learning · Machine Learning

  3. AI/ML Consultant

    Artificial Twin • Freelance
    Led end-to-end AI/ML development across RL, LLMs, CV, and MLOps for real and simulated environments. Built and deployed transformer-based models, VLAM prototypes, and industrial CV systems, while maintaining core AI and geometry libraries.
    Skills: C++ · Python · PyTorch · Deep Reinforcement Learning · Large Language Models (LLM) · Computer Vision · Deep Learning · Computational Geometry · Vision Language Models (VLM) · Vision Language Action Models (VLAM) · Reinforcement Learning · Computational Fluid Dynamics

  4. Founder & Principal AI/ML Engineer

    DIAMBRA (Acquired in Dec 2024) • Part-time
    Founded and led DIAMBRA, a global RL competition platform with leaderboards and Twitch integration. Built DIAMBRA Arena with Gym-compatible environments to support advanced RL research and seamless library integration.
    Skills: C++ · Python · PyTorch · Deep Reinforcement Learning · Docker

  5. Principal Research Engineer

    Nurjana Technologies • Permanent Full-time
    Designed and deployed AI for autonomous drones and space systems, including CV-based ISR, GNSS-denied navigation, and embedded deployment. Led development of ML algorithms for satellite tracking and multi-UAV autonomy, integrating sensor fusion and simulation-based training.
    Skills: C++ · Python · PyTorch · Computer Vision · Deep Learning · Deep Reinforcement Learning · OpenCV · Modeling and Simulation · Space Flight Dynamics

  6. AI/ML & Simulation Advisor and Industry Expert

    NATO • Contract Part-time
    Advised NATO on integrating AI/ML into defense systems for autonomous operations, sensor fusion, and decision-making under uncertainty. Contributed to AI-enhanced C4I for air defense and airdrop missions, focusing on real-time capabilities, trustworthiness, and emerging threat response.
    Skills: Artificial Intelligence · Machine Learning · Deep Learning · Computer Vision · Deep Reinforcement Learning · Flight Dynamics · Computational Fluid Dynamics
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Papers
Danilo Zona, Giulio Avanzini, Fabrizio Giulietti, Alessandro Palmas (2025). Application of Singular Perturbation Theory to Space Flight Dynamics Problems. Astrodynamics - Springer and Tsinghua University Press.
PDF Cite DOI
Alessandro Palmas (2025). Reinforcement Learning for Decision-Level Interception Prioritization in Drone Swarm Defense. arXiv preprint (cs.LG).
PDF Cite Code Video DOI Project
Alessandro Urru, Michele Spanu, Enrico Congiu, Alessandro Palmas, Pietro Andronico (2023). Performance Index of a Network of Ground-Based Optical Sensors for Space Objects Observation and Measurements. Advances in Space Research.
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Alessandro Palmas (2022). DIAMBRA Arena: a New Reinforcement Learning Platform for Research and Experimentation. arXiv preprint (cs.LG).
PDF Cite Code Video DOI Project
Giulio Avanzini, Fabrizio Giulietti, Alessandro Palmas, Danilo Zona (2022). Application of Singular Perturbation Theory to Space Flight Dynamics Problems. 73th International Astronautical Congress (IAC).
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