Software for AI-Driven Industrial Applications
Narrow AI systems for robotic perception, task interpretation, and reliable execution. Focus on architectures that are testable, integrable, and suitable for industrial constraints.
Areas of focus
Robotic perception
Practical scene understanding for structured and semi-structured environments, built for robustness rather than demos.
Decision logic & execution
Constrained, task-specific logic that bridges perception outputs to predictable robot actions and recovery behavior.
Simulation-driven development
Validation of task logic and failure modes in simulation to reduce iteration cost and deployment risk.
Integration mindset
Design that respects real interfaces (controllers, PLCs, industrial networks) and keeps AI out of safety-critical loops.
Selected projects
Short, technical summaries with emphasis on system behavior and constraints. Implementation details are intentionally omitted.
AI for Industry Challenge: Vision-Based Robotic Insertion
Competition project for Intrinsic's AI for Industry Challenge, focused on perception-driven cable insertion without ground-truth information.
Language-Guided Robot Task Interpretation
Using language models as an interpretation layer to map intent and scene descriptions into a predefined action vocabulary.
Sim-to-Real Fruit Detection with Synthetic Data
Evaluation of synthetic, real, and hybrid datasets for fruit detection, including deployment on embedded hardware.
