
Worked on the lbalmelli/keio repository to deliver foundational features for an Automated Parking System, focusing on a proof of concept for an ADAS Urban Parallel Parking System. Developed a SysML model and a digital twin dashboard with a parking-status state machine and GUI, enabling rapid evaluation and future validation. Refactored and cleaned up SysML models by removing outdated artifacts and improving naming conventions, which enhanced maintainability and repository hygiene. Leveraged Python programming, SysML, and model-based systems engineering to map driver, environment, and system interactions, supporting safer operation and clearer requirements traceability for automated driving system development.
November 2025 monthly summary for lbalmelli/keio: Delivered foundational ADAS/Automated Parking System work and modeling assets to enable rapid evaluation and future validation. Key features delivered include a PoC for the ADAS Urban Parallel Parking System (SysML model, documentation, and a digital twin dashboard with a parking-status state machine and GUI). SysML model cleanup/refactor reduced technical debt by removing outdated artifacts and renaming files to reflect current focus. A comprehensive Automated Parking System model was introduced to map driver, environment, and system component interactions for safer operation and clearer requirements traceability. Major bugs fixed: none reported this month; ongoing cleanup addressed potential issues and improved maintainability. Technologies/skills demonstrated include SysML modeling, system architecture and modeling governance, dashboard/digital twin development, documentation discipline, and repository hygiene. Business value: accelerated PoC evaluation, improved safety assurance through explicit state machines and requirements traceability, and clearer ownership of modeling artifacts; overall impact is higher quality, maintainable assets and faster decision cycles.
November 2025 monthly summary for lbalmelli/keio: Delivered foundational ADAS/Automated Parking System work and modeling assets to enable rapid evaluation and future validation. Key features delivered include a PoC for the ADAS Urban Parallel Parking System (SysML model, documentation, and a digital twin dashboard with a parking-status state machine and GUI). SysML model cleanup/refactor reduced technical debt by removing outdated artifacts and renaming files to reflect current focus. A comprehensive Automated Parking System model was introduced to map driver, environment, and system component interactions for safer operation and clearer requirements traceability. Major bugs fixed: none reported this month; ongoing cleanup addressed potential issues and improved maintainability. Technologies/skills demonstrated include SysML modeling, system architecture and modeling governance, dashboard/digital twin development, documentation discipline, and repository hygiene. Business value: accelerated PoC evaluation, improved safety assurance through explicit state machines and requirements traceability, and clearer ownership of modeling artifacts; overall impact is higher quality, maintainable assets and faster decision cycles.

Overview of all repositories you've contributed to across your timeline