Our research focuses on the areas of adaptive systems and architectures, which includes coordinated tasks on all system layers ranging from core-level architecture to runtime systems all the way to the system level. These adaptive systems should monitor themselves, analyze their behavior, learn and adapt to several execution environments while keeping the system’s complexity invisible to the user.Moreover, as the demand for performance confronts permanent and transient faults, device/process variation, thermal issues, and also noisy and incomplete data sets (uncertainty), we are researching a new computing model by combining concepts of neuroscience and machine learning with computer architecture and microelectronics that go beyond the current stored-program computing model. Current research focuses on adaptive neuromorphic systems and processors with higher speeds, lower-overhead and ultra-low power consumption directed at impacting a number of real-world applications, including embedded pattern recognition and neuro-inspired approaches to improving scientific computing and high-performance computing. 


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