by U-M MICDE | Oct 10, 2024
Quantum many-body theory and algorithms for strongly correlated systems.
by U-M MICDE | Oct 10, 2024
I’m working on stochastic optimization, nonlinear optimization, derivative-free optimization, constrained optimization, and machine learning.
by U-M MICDE | Oct 8, 2024
My research focus is Quantum Computing and High-Performance Computing, and I seek to advance practical quantum advantage through integrating these technologies. I’m interested in developing efficient algorithms and architectures that leverage classical HPC...
by U-M MICDE | Dec 12, 2023
Reetu Das is an Associate Professor at the University of Michigan. Prior to this, she was a research scientist at Intel Labs, and the researcher-in-residence for the Center for Future Architectures Research. She also served as the co-founder of a precision medicine...
by U-M MICDE | Dec 12, 2023
Mahlke’s research focuses on novel methods for designing energy-efficient high performance computer systems. Hardware-software codesign is used to create specialized computer systems that are customized to application domains or even individual applications....
by U-M MICDE | Oct 3, 2023
I work on planet formation theory, with a current focus on giant planet formation in a core accretion paradigm. My current work looks at distinctions in the formation of gas giant planets as a result of conditions in their local environment, and how these differences...
by U-M MICDE | Oct 3, 2023
Joshua Pickard’s research is centered on higher-order network-based dynamical systems, the application of control theory to biological systems, and the development of mathematical models for chromatin architecture and gene regulation. Joshua’s present work...
by U-M MICDE | Sep 30, 2023
Quantum many-body theory and algorithms for strongly correlated systems.
by U-M MICDE | Sep 28, 2023
Computational and mathematical optimization to solve large-scale experimental design problems.
by U-M MICDE | Sep 26, 2023
Developing probabilistic frameworks for efficient uncertainty quantification and reliability assessment of high-rise systems against natural hazards leveraging data-driven and artificial intelligent techniques
