Vision-Language-Action Models
Grounding perception, language and robot actions for embodied task execution.
View project ↗SOFTWARE ENGINEERING × MECHATRONICS SYSTEMS ENGINEERING × MACHINE LEARNING × PHYSICAL AI
Physical AI: Engineering the Future of Next-Generation Robotics.
codeEngineering is an engineering and research platform focused on software systems, machine learning and intelligent robotic technologies.
It explores how computational models can perceive, learn, make decisions and interact with the physical environment.
GitHub ↗P.00 / Selected projects
Explore initial project directions.
Large Behavior Models
Exploring structured behaviour generation and adaptation for intelligent robotic systems.
View project ↗Physical-AI Manipulators
Learning-enabled manipulation under kinematic and physical constraints.
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R.01 / Research focus
Physical AI and intelligent robotic systems.
My interests bring together machine learning, robotics and the mathematical description of physical systems. The following topics describe current research focus and active exploration, not completed claims.
Physical AI & Embodied Intelligence
Intelligent systems that learn and act in connection with the physical world.
Vision-Language-Action Models
Learning-based models that connect visual, linguistic and action-oriented representations.
Large Behavioral Models
Models for representing and generating complex robotic behaviour.
Robot Learning
Reinforcement learning and imitation learning for robotic systems.
Robotic Manipulation
Manipulator behaviour, kinematics, inverse kinematics and system dynamics.
Generative Robot Behaviour
Generative and diffusion-based approaches for robotic interaction and control.
Physical Constraints
Holonomic and nonholonomic constraints in the mathematical description of robotic systems.
Efficient AI
Computational and energy optimisation of AI models for practical intelligent systems.
Research Environments
Exploring Hugging Face LeRobot, ROS, Gazebo and robotic simulation environments.
PUB.01 / Publications
Research outputs.
Peer-reviewed publications and academic research outputs.
View publications ↗T.01 / Teaching
Practical learning with clear reasoning.
As a doctoral researcher, I conduct laboratory classes and prepare educational materials for students. I value practical learning, clear explanations and good programming practices.
My goal is to help students understand how software works and develop independent problem-solving skills rather than simply provide finished solutions.
S.01 / Technologies & tools
Established experience and active exploration.
Technologies are grouped by their current role; the labels distinguish established professional focus from research exploration.
Software & Mechatronics Systems Engineering
C++/Python development and workflows for software and mechatronics systems engineering.
Established focusAI & ML
Machine learning for robotics and generative approaches.
Research focusRobotics
C++, manipulation, ROS, Gazebo and simulation.
Active explorationResearch Tools
LaTeX, modelling, experiments and analysis.
Academic workflowDevelopment Tools
GitHub, version control and CI/CD automation.
Development workflowC.01 / Contact
Discuss software, research or teaching.
For professional and academic enquiries, use the confirmed contact details.