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| − | Andrea Cossettini is a PostDoc at the Integrated Systems Laboratory of ETH Zurich. | + | 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 and M.Sc. degrees in Electronic Engineering from the University of Udine (Italy), in 2019 and 2015, respectively. | He received the PhD and M.Sc. degrees in Electronic Engineering from the University of Udine (Italy), in 2019 and 2015, respectively. | ||
Revision as of 22:25, 25 May 2020
Andrea Cossettini
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 and M.Sc. degrees in Electronic Engineering from the University of Udine (Italy), in 2019 and 2015, respectively. In 2014, he was at Acreo Swedish ICT AB (Kista, Sweden), designing waveguide-to-chip transitions at sub-millimeter waves. In 2014-2015, he was at Infineon Technologies (Villach, Austria), working on signal integrity for high-speed serial interfaces. During the PhD (2015-2019) he worked on nanoelectrode array biosensors for high-frequency impedance spectroscopy. He first joined ETH Zurich in 2019 as Academic Guest for the design of high-speed analog/mixed-signal boards for nanoelectronic biosensors.
His main research focus is on HW system design for biomedical applications.
Interests
- Medical Ultrasound Imaging
- High-speed analog/mixed-signal systems
- Nanoelectronic biosensors
Available Projects
- Exploratory Development of a Unified Foundational Model for Multi Biosignal Analysis
- Deep Learning Based Anomaly Detection in ECG Signals Using Foundation Models
- Pretraining Foundational Models for EEG Signal Analysis Using Open Source Large Scale Datasets
- EEG-based drowsiness detection
- In-ear EEG signal acquisition
- EEG earbud
- Development Of An FPGA-Based Optoacoustic Image Reconstruction Platform for Clinical Applications
- Ultrasound measurement of microbubble stiffness for in situ detection of protease activity in clinical settings
- Advanced EEG glasses
- Predict eye movement through brain activity
- Design of combined Ultrasound and PPG systems
- Improving datarate and efficiency of ultra low power wearable ultrasound
- Battery indifferent wearable Ultrasound
- Wearable Ultrasound for Artery monitoring
- Machine Learning for extracting Muscle features from Ultrasound raw data
- Self Aware Epilepsy Monitoring
- 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
Contact Information
- Office: ETZ J78
- e-mail: cossettini.andrea@iis.ee.ethz.ch
- phone: (+41 44 63) 378 97
- www: IIS Homepage
