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Smart and Green AI
Smart and Green AI
Goal: Lay the foundations for a new AI paradigm featuring algorithms based on the free energy principle (FEP) and hardware platforms leveraging the stochasticity of novel nanoscale devices based on 2-dimensional materials, enabling embedded systems with unprecedented efficiency.
Funding:EPSRC
NeuroSoC
NeuroSoC
Goal: Develop a flexible computing system where an analog In-Memory-Computing-based neural processing unit (NPU) is integrated into a multi-processor system-on-chip. The analog NPU will be built using Phase Change Memory technology.
Funding: European Commission
CENTRIC
CENTRIC
Goal: Create and customise innovative hardware computing substrates, tailor-made waveforms, transceivers, signalling, protocols and RRM procedures leveraging AI techniques to support wireless connectivity that puts the users’ communication needs and environmental constraints at the centre of the network stack design.
Funding: European Commission
NeuroComm
NeuroComm
Goal: Lay the foundations of wirelss cognition by addressing the integration of neuromorphic principles within an end-to-end system encompassing sensing, computing, and wireless communications for the development of efficient, integrated wireless connectivity and semantic processing.
Funding: EPSRC & NSF
Bayesian AI hardware
Bayesian AI hardware
Goal: Develop hardware architectures to efficiently implement Bayesian Neuromorphic algorithms leveraging programming and read stochasticity of emerging memory devices.
Funding: King's
Team members
Team members
Abin Varghese,
Post-doc
Robert O'Shea,
Post-doc
Zihang Song,
Post-doc
Chen Li,
Post-doc
Prabodh Katti,
PhD student
Anagha Nimbekar,
Visiting PhD student
Stefan Johannesson,
Undergraduate student
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