Ehsan Yousefzadeh-Asl-Miandoab

Ehsan Yousefzadeh-Asl-Miandoab is a Postdoctoral Researcher at the IT University of Copenhagen (ITU), Denmark. His work lies at the intersection of computer systems, architecture, and emerging applications, with a particular focus on optimizing hardware efficiency for deep learning training tasks.

He earned his PhD at ITU, where his research tackled the challenge of GPU underutilization in deep learning training. His doctoral thesis explored both analytical studies and system designs aimed at improving GPU resource usage and training efficiency.

Earlier, during his master’s studies in computer architecture, Ehsan investigated GPU energy efficiency at the microarchitectural level, proposing new designs for on-chip memories to reduce power consumption while maintaining performance.

His broader research interests include GPUs, parallel computing systems, energy-efficient architectures, and the use of machine learning and deep learning techniques to guide efficient system design.