Azime Can

Azime Can is an Assistant Professor at the Swanson School of Engineering, University of Pittsburgh. Their research focuses on signal processing with applications in biomedical engineering, nonstationary signal analysis, compressive sampling, and control systems. Key areas include asynchronous signal processing techniques, sparse signal reconstruction, and event-based control systems.

Research interests emphasize interdisciplinary challenges in biomedical signal analysis (e.g., swallowing accelerometry, heart sounds) and industrial fault diagnosis. Publications span theoretical advancements in time-frequency analysis and practical implementations in embedded systems.

Recent work highlights contributions to compressive sensing, event-triggered control, and adaptive signal processing algorithms. No scientific awards are listed, but active research in high-impact areas suggests potential for future recognition. Advising and grant details are not provided in available data.