Difference between revisions of "User:Fconti"
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* [[Design and Implementation of Digital Spiking Neurons for Ultra-Low-Power In-Cluster Coprocessors]] (master thesis) | * [[Design and Implementation of Digital Spiking Neurons for Ultra-Low-Power In-Cluster Coprocessors]] (master thesis) | ||
* [[Interfacing PULP with a Brain-Inspired Ultra-Low Power Spiking Cochlea]] (master thesis) | * [[Interfacing PULP with a Brain-Inspired Ultra-Low Power Spiking Cochlea]] (master thesis) | ||
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* [[Ultra-Efficient Visual Classification on Movidius Myriad2]] (semester thesis) | * [[Ultra-Efficient Visual Classification on Movidius Myriad2]] (semester thesis) | ||
Revision as of 14:29, 10 May 2017
Contents
Francesco Conti
I am a postdoctoral researcher here at IIS since July 2016, and I also hold a position as a research assistant at the University of Bologna, Italy. My interests focus on energy-efficient multicore architectures, with particular emphasis on heterogeneous multicores and cognitive computing architectures. I am interested in the entire technological stack "from Python to Silicon".
Interests
- heterogeneous multicore architectures for energy-efficient and low-power embedded systems
- applications of deep learning and brain-inspired computational models and architectures to low-power digital systems
Available projects
- Towards Online Training of CNNs: Hebbian-Based Deep Learning (semester thesis)
- Deep-Learning Based Phoneme Recognition from a Ultra-Low Power Spiking Cochlea (semester thesis)
- Tiny CNNs for Ultra-Efficient Object Detection on PULP (semester thesis)
- Single-Bit-Synapse Spiking Neural System-on-Chip (master thesis)
- You can also always contact me for projects that have not yet been formalized (semester/master), or with your own project idea!
Running projects
- A Low-Power FPGA-Based Camera Sensor Interface for PULP Devices (semester thesis)
Completed projects : 2017
- A Recurrent Neural Network Speech Recognition Chip (semester thesis)
Completed projects : 2016
- Design and Implementation of Digital Spiking Neurons for Ultra-Low-Power In-Cluster Coprocessors (master thesis)
- Interfacing PULP with a Brain-Inspired Ultra-Low Power Spiking Cochlea (master thesis)
- Ultra-Efficient Visual Classification on Movidius Myriad2 (semester thesis)
Contact Information
- Office: ETZ J78
- telephone: +41 44 63 37151
- e-mail: fconti@iis.ee.ethz.ch
- www: Francesco Conti homepage @University of Bologna