I research how humans and AI agents learn to cooperate without being told how — starting in virtual environments during my undergraduate thesis, and now extending that question into the physical world for my Master's in Computer Engineering.
My engineering background is in automation and robotics: embedded control, navigation, embedded devices, and industrial retrofitting. That hands-on foundation is what lets me take collaboration research out of simulation and actually build it into physical, real-time systems — not just model it on paper.
- 🧠 Core research interest: emergent coordination between humans and AI agents
- 🦾 Currently building the physical/embodied extension of this research for my M.Sc.
- ⚙️ Broad automation engineering background — robotics is the common thread across every project I've built
- 🤝 Open to research partnerships, open-source collaboration, and roles in robotics/embedded systems
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Undergraduate Thesis (TCC) · Python / Pygame A cooperative game where some players are humans and others are AI agents, and no one is told the shared objective upfront. The goal exists, but it's never stated: all players must infer it in real time, purely by observing each other's actions, and converge on cooperative behavior without any explicit communication channel. This is, at its core, a study in implicit coordination and mutual intent-reading between a human and an AI partner.
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M.Sc. Research · Computer Engineering Taking the same underlying question — can a human and an AI partner reach a shared goal by reading each other's behavior alone? — and moving it into the physical world. The objective and full design are still being defined by nature of the research (discovering it is the point), but the throughline is the same: coordination through observation, not instruction, now embodied in real hardware.
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Different domains, same common thread: robotics. This is the hands-on foundation that makes the physical side of my research possible.
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Multisensor Navigation for UAVs Navigation system for unmanned aerial vehicles operating in GNSS-degraded environments, developed in partnership with a private aerospace/defense company.
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Surgical Device for Nasal Cartilage Trituration Mechatronic surgical tool for cartilage grinding, validated on ex-vivo models for plastic otolaryngology applications.
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Industrial Automation & Simulation Digital Twin and Industry 5.0 projects for industrial robotic manipulators — integrating part inspection, MQTT-based instrumentation, classical computer vision, and vibration/noise detection into a closed-loop, sensor-driven operation.
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🧠 Human-AI Collaboration & Multi-Agent Systems
🤖 Robotics & Embedded Systems
🧰 Tools & Platforms
I'm actively open to:
- 🧠 Research collaboration in human-AI interaction, multi-agent coordination, and embodied AI
- 🔓 Open-source collaboration in robotics, embedded systems, and computer vision tooling
- 🎓 Academic partnerships — HRI, applied AI, medical devices, autonomous navigation
- 🏭 Opportunities in embedded systems / industrial robotics — R&D or hands-on engineering roles
