Ilya Kurinov

• ● Developed 2 AI-driven autonomous control systems in Python using reinforcement

learning for heavy machinery automation, enabling an excavator to autonomously unload soil and a forestry forwarder to pick and place logs from variable positions

• ● Designed and implemented custom Python APIs and simulation interfaces between Mevea physics engine and RL training frameworks, enabling real-time state, action, and reward exchange for closed-loop training and validation workflows

• ● Built Unity-based simulation modules in C# to model worker movement, operational workflows, and production scenarios for DaimlerChrysler industrial projects, supporting digital twin validation and process optimization

• ● Delivered working Python RL prototypes for autonomous heavy machinery control, later used in research demonstrations and successful funding applications for LUT robotics projects. Source code available on Github.

• ● Independently taught Python and C++ courses to 20 bachelor students per semester

• ● Created full course materials, video lectures, assignments, and assessments

• ● Delivered online teaching during COVID-19, maintaining high engagement

• ● Built a real-time co-simulation framework in C++ and Python linking Mevea physics simulation with Unreal Engine 4 through UDP networking, enabling synchronized physics and visualization of heavy machinery in VR

• ● Implemented Leap Motion hand gesture controls in Unreal Engine 4 using C++ and

Blueprint scripting, creating an interactive VR menu for gesture-based simulation control and operator testing

• ● Developed synchronization logic for position, rotation, and interaction state transfer between Mevea and UE4 to support immersive digital twin testing