I work at the intersection of physical AI, manufacturing, and quality engineering—where software meets hardware, and where systems either scale reliably or fail quietly.
My focus is on understanding failure modes in complex products and production systems, and on how modern analytics—machine learning, time-series analysis, and AI-enabled inspection—change how quality, reliability, and execution risk are managed at scale.
Focus Areas
Quality, Failure Analysis & Corrective Action
Failure analysis, root cause analysis, and corrective and preventive action (CAPA) across products, processes, and manufacturing systems.
AI-Enabled Inspection & Monitoring
Quality control using automatic optical inspection (AOI), AI-driven visual inspection robots, sensor-based monitoring, and vibration analysis.
Physical AI & Manufacturing
AI systems embedded in physical processes, including robotics, automation, and production equipment operating under real-world constraints.
Predictive Analytics & Systems Behavior
Time-series analysis, predictive maintenance, anomaly detection, and deep learning approaches for anticipating failures before they surface operationally.
I engage with these topics at inflection points—where system behavior, data, and decisions materially affect long-term outcomes.
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