Prakash Murali

About

My research interests include quantum architecture, resource estimation and compilation. I was previously a Senior Quantum Systems Architect as part of Microsoft's quantum computing program where I designed the Azure Quantum Resource Estimator to understand the resource needs of practical-scale quantum applications. I graduated with a Computer Science Ph.D. from Princeton University. My PhD research aimed at developing an efficient quantum computing stack to bridge the resources gap between quantum algorithms and hardware that is buildable in the near future. My work has been adopted by several industry compilers, influenced architecture and industry benchmarking practices. My work has been recognized by the ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Award (2022), Communications of

Education

• Ph.D. Computer Science, Princeton University

Selected publications

• Assessing requirements to scale to practical quantum advantage.
• Toward systematic architectural design of near-term trapped ion quantum computers.
• Designing Calibration and Expressivity-Efficient Instruction Sets for Quantum Computing.
• Resource-Efficient Quantum Computing by Breaking Abstractions.
• Architecting Noisy-Intermediate Scale Quantum Computers: A Real-System Study
• Architecting Noisy Intermediate-Scale Trapped Ion Quantum Computers
• Software Mitigation of Crosstalk on Noisy Intermediate-Scale Quantum Computers
• Full-Stack, Real-System Quantum Computer Studies: Architectural Comparisons and Design Insights.
• Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers.