Low-Power Integrated Circuits and Embedded Systems Laboratory (LPiNS-Lab)
We model and develop energy-efficient algorithms and design complementary low-power processors at both the IC and RTL levels for emerging computer architectures that target large-scale parallel computations and AI workloads. Foundational and applied research work extends across diverse audiences and applications, from biomedical device innovation to re-designing in-memory device architecture. In short, in our laboratory, we are:
- Designing power-efficient processor chips and RTL-level domain-specific computer architectures (DSAs) to execute high computational workloads and massively parallel computing.
- Modeling energy-efficient deep learning algorithms to tackle the current AI training and testing bottleneck.
- Developing low-power integrated circuits and systems for next-generation biomedical instrumentations such as inkjet-printed AI-core-based respiratory bracelets and efficient computer vision models on the “edge”.
We are a group of intrigued individuals and low-key coffee connoisseurs who love to get their hands dirty!
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Research Topics
LPiNS-Lab focuses on solving the power-consumption problem on both the software and hardware side. We develop methodologies for low-power integrated circuits (IC) and hardware modeling for computer processors. With a background in computing, integrated circuits, and embedded systems, we work on designing energy-efficient artificial intelligence (AI) accelerators and systems leveraging both the analog and digital domains. Our laboratory thrives on innovation and envisions a future where technology is a force for good. We are driven by the dual pursuit of societal advancement and sustainability, ensuring that our research has a lasting impact on our communities and planet. Visit our research topics to contribute to our mission and vision.