
Daniel Liu developed a first-person camera system with mouse-based control for the PurdueSIGGD/SIGGD-GAME-2025 repository, focusing on enhancing player immersion and interaction within the Unity game environment. Using C# scripting, Daniel implemented real-time input handling to ensure smooth and responsive camera movement, laying a robust foundation for future gameplay features. The work emphasized stability and incremental delivery through Git, with attention to preparing the system for quality assurance feedback. Although no major bugs were addressed during this period, Daniel’s contribution provided a core gameplay mechanic that supports further camera refinements and demonstrates proficiency in both Unity and C# development practices.
October 2025: Delivered a first-person camera system with mouse-based control for PurdueSIGGD/SIGGD-GAME-2025, significantly enhancing immersion and player interaction. No major bugs fixed this month; focused on stabilizing the camera feature and preparing for QA feedback. Impact: stronger core gameplay feel and a solid foundation for future camera refinements; demonstrated proficiency in real-time input handling, camera control, and Git-based incremental delivery.
October 2025: Delivered a first-person camera system with mouse-based control for PurdueSIGGD/SIGGD-GAME-2025, significantly enhancing immersion and player interaction. No major bugs fixed this month; focused on stabilizing the camera feature and preparing for QA feedback. Impact: stronger core gameplay feel and a solid foundation for future camera refinements; demonstrated proficiency in real-time input handling, camera control, and Git-based incremental delivery.

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