Difference between revisions of "Andrea Cossettini"
From iis-projects
(→Interests) |
(→Available Projects) |
||
| Line 16: | Line 16: | ||
==Available Projects== | ==Available Projects== | ||
| + | |||
| + | '''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.''' | ||
| + | |||
<DynamicPageList> | <DynamicPageList> | ||
supresserrors = true | supresserrors = true | ||
Revision as of 14:08, 3 June 2021
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 THz waveguide-to-chip transitions. In 2014-2015, he was at Infineon Technologies (Villach, Austria), working on signal integrity 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.
Interests
- High-speed analog/mixed-signal biomedical systems
- Medical Ultrasound Imaging
- Systems for ExG signal acquisition
- Nanoelectronic biosensors
Available Projects
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.
- 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
