Andrea Cossettini is a PostDoc at the Integrated Systems Laboratory of ETH Zurich, in the Digital Systems group led by Prof. Luca Benini.
He received the PhD, M.Sc., and B.Sc. degrees in Electronic Engineering from the University of Udine (Italy), in 2019, 2015, and 2012, respectively. In 2014, he was at Acreo Swedish ICT AB (Kista, Sweden), doing THz electromagnetic design for waveguide-to-chip transitions. In 2014-2015, he was at Infineon Technologies (Villach, Austria), working as signal integrity engineer for high-speed serial interfaces for automotive microcontroller applications. During the PhD (2015-2019) he worked on nanoelectrode array biosensors for high-frequency impedance spectroscopy and imaging of nano- and micro-particles in electrolyte.
He joined ETH Zurich in 2019. His research focus is on circuits and systems design for biomedical applications, with a special emphasis on ultrasound and EEG.
- Analog/mixed-signal biomedical circuits and systems design
- Medical Ultrasound Imaging
- EEG/EMG wearable systems
- High-speed PCB design and electromagnetic/signal-integrity simulations
- Nanoelectronic biosensors
Most of the projects evolve very fast. If you are interested in the research areas mentioned above, send me a message to discuss up-to-date project opportunities. Showing up with your own project ideas is also very appreciated.
- EEG artifact detection with machine learning
- EEG artifact detection for epilepsy monitoring
- Automatic unplugging detection for Ultrasound probes
- Machine Learning on Ultrasound Images
- Nanoelectrode array biosensors - programmable non-overlapping clocks generator project
- Visualizing Functional Microbubbles using Ultrasound Imaging
Projects in progress
- Ultra low power wearable ultrasound probe
- Machine Learning for extracting Muscle features using Ultrasound 2
- Ultrasound Low power WiFi with IMX7
- Ultrasound signal processing acceleration with CUDA
- Minimum Variance Beamforming for Wearable Ultrasound Probes
- Machine Learning for extracting Muscle features using Ultrasound
- Compression of Ultrasound data on FPGA
- LightProbe - 200G Remote DMA for GPU FPGA Data Transfers
- Time Gain Compensation for Ultrasound Imaging