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(Required Skills)
(Available projects)
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== '''Available projects''' ==
 
== '''Available projects''' ==
* [[Implementation of the RISC-V Bit Manipulation (RVB) extensions for our RISC-V core]] (semester/master thesis)
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* [[Heroino: Design of the next CORE-V Microcontroller]] (semester/master thesis)
* [[Arnold: Developing efficient IoT data processing applications for a versatile PULPissimo-based SoC in 22nm FDSOI]] (semester/master thesis)
 
* [[Cerebellum: Design of a Programmable Smart-Peripheral for the Ariane Core]] (semester/master thesis)
 
 
* [[Design of Scalable Event-driven Neural-Recording Digital Interface]] (semester/master thesis)
 
* [[Design of Scalable Event-driven Neural-Recording Digital Interface]] (semester/master thesis)
* [[Hardware Accelerators for Lossless Quantized Deep Neural Networks]] (semester/master thesis)
 
 
* If you have your personal idea, you can also contact me for projects!
 
* If you have your personal idea, you can also contact me for projects!
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== '''Completed projects''' ==
 
== '''Completed projects''' ==
 
* [[Deep Learning for Brain-Computer Interface]] (semester thesis)
 
* [[Deep Learning for Brain-Computer Interface]] (semester thesis)

Revision as of 13:55, 6 February 2021

Pasquale Davide Schiavone

Pasquale Davide Schiavone is a PhD student at the Integrated Systems Laboratory of ETH Zurich in the Digital Systems group led by Prof. Luca Benini. He obtained a BSc. and a MSc. from "Politecnico di Torino" in computer engineering in 2013 and 2016 respectively. His main research focus is on low-power energy-efficient computer architectures for Internet-Of-Things systems and brain-machine interfaces through EEG and neural action potential signals.

From January to June 2018 I visited the Centre of Bio-Inspired Technology at Imperial College London in the Next Generation Neural Interfaces group.

Interests

  • Computer and System Architecture
  • Digital ASIC Design
  • Embedded systems
  • Heterogeneous multicore architectures for energy-efficient and low-power embedded systems
  • Brain-Machine interface


Available projects

Completed projects

Contact Information