Our applications range from neuro-inspired (brain-like) low-power computing embedded systems to adaptive neural-based control, and brain-machine interfaces
Research at the Adaptive Systems Laboratory focuses on energy-efficient adaptive computing systems based on novel adaptive algorithms and fault-tolerant scalable interconnects to overcome the limitation of traditional stored-program computing style. In particular, we study adaptive computing systems for …
Our research tackles adaptive systems and SoSs targeted for complex real-time machine learning applications such as robotic control, pattern recognition, and brain-machine interfaces…
We are developing low-power chips and SoCs with on-chip learning capabilities to tackle complex real-time machine learning applications such as robotic control, pattern recognition, and brain-machine interfaces…
We investigate innovative computing systems and technologies that deliver high performance, energy efficiency, and adaptivity for various application domains and social needs. In particular, we develop algorithms and techniques for run-time decision-making targeting various optimization goals such as power/energy-efficiency, fault-tolerance/reliability, or compute performance, and targeting different architectural platforms, including high-performance computing nodes, reconfigurable systems, and power-constrained edge computing systems and technologies.
April 1st, 2022. This public site is no longer maintained.
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