• Specialized in embedded systems, robotics, and distributed systems, with solutions in Python and Rust.
• Background in International Business, which helps translate business needs into real technical systems.
• I focus on designing systems that remain stable under noisy sensing conditions, constrained computation, and asynchronous communication between distributed components.

End-to-end cyber-physical system integrating embedded sensing, probabilistic state estimation, and distributed edge processing.

• Embedded Kalman filtering for noise-aware state estimation
• Finite-state machine for deterministic multi-sensor control
• Distributed architecture (UART → MQTT → edge node)
• Real-time data pipeline with SQLite and REST API
• Live monitoring dashboard via Server-Sent Events

This project demonstrates the integration of probabilistic estimation, deterministic control, and distributed system design under real-world sensing constraints.

These repositories examine fundamental engineering concepts commonly used in robotics and cyber-physical systems.

They focus on the core engineering principles underlying robotics systems, with emphasis on sensing, estimation, control, and distributed coordination in real-world conditions.

Includes implementations of Kalman filtering, Bayesian estimation, and control systems evaluated under realistic sensor noise and system-level constraints.

• Perception and probabilistic sensing
• Bayesian estimation and sensor fusion
• Robot perception and environment representation
• Feedback control and system dynamics
• Embedded state-machine architectures
• Distributed coordination of edge devices

• sensor-uncertainty-lab
  Experiments exploring probabilistic models of noisy sensor measurements.

• bayesian-sensor-fusion
  Implementations of Kalman filters, particle filters, and multi-sensor fusion techniques for state estimation in robotics systems.

• robot-perception-lab
  Probabilistic perception techniques such as occupancy grids and localization.

• control-systems-lab
  Feedback control experiments demonstrating PID controllers and system dynamics.

• embedded-state-machine-systems
  Finite state machine architectures commonly used in embedded robotics systems.

• edge-device-coordination
  Coordination patterns for distributed embedded nodes and edge devices.

• 📧 Email: [email protected]
• 💡 Open to collaboration on embedded systems, industrial automation, and innovative hardware–software integration.
• 🌎 Available for remote consulting and technical advisory roles with international teams.