Ryan LaRose

Ryan LaRose is an Assistant Professor at Michigan State University (MSU) with appointments in the Department of Computational Mathematics, Science and Engineering and the Department of Physics & Astronomy within the College of Natural Science. He also holds affiliations with the Department of Electrical and Computer Engineering and MSU's quantum initiative (MSU-Q), focusing on quantum computing research and development.

His educational background includes a PhD in Computational Mathematics, Science and Engineering from Michigan State University (2022) and a BS with Distinction in Mathematics and Physics from the University of Michigan, Ann Arbor (2017).

LaRose's research bridges computational physics and quantum information science through two interconnected themes: (1) the physics of computation, examining how quantum principles inform information theory and computer science, and (2) the computation of physics, leveraging quantum computers to solve complex problems in physical sciences. His work emphasizes practical quantum algorithm development, error mitigation techniques for noisy hardware, and open-source software tools for quantum computing.

Analysis of his recent publications (2022-2024) reveals strong emphasis on quantum error mitigation strategies—particularly zero-noise extrapolation—and variational quantum algorithms for optimization and linear algebra problems. His contributions span hardware solutions, software frameworks like Mitiq and BGLS, and theoretical advances in quantum volume measurement.

His notable scientific awards include:

• Engineering Distinguished Fellowship
• Fitch H. Beach Award for Outstanding Graduate Research
• NASA Space Technology Graduate Research Fellowship

As an active contributor to the quantum community, LaRose co-organizes the QuIC Seminar series at MSU and develops open-source quantum software. He leads research efforts within MSU-Q, collaborating on quantum algorithm implementation and error mitigation techniques for near-term quantum devices.