2021: IEEE MeMeA (General Chair)
2019: PRIME (Co-General Chair)
2018: IEEE MeMeA (Co-General Chair)
2017: IEEE BioCAS (TPC Chair)
2016: IEEE ICECS (TPC Chair) - IEEE ISCAS (Special Session Chair)
2015: IEEE BioCAS (TPC Chair) - IEEE Sensors Conference (Demos Chair)
2014: IEEE BioCAS(General Chair)
2013: IEEE IWASI (Sterring Committee)
2012: IEEE BioCAS (Session Chair)
2011: IEEE ISMICT (TPC Chair) / IEEE BioCAS / IEEE IWASI
2010: IEEE BioCAS (Session Chair)
2009: Nano-Net (Session Chair)

Journal BioNanoScience par Springer

Journal IEEE Sensors

Journal IEEE T. on Biomedical Circuits and Systems

EPFL/UM6P Program «Excellence in Africa«
Final objective of the program is to create the proper conditions for them to produce outstanding PhD research. More generally, the program will contribute to the emergence of a new generation of talented young researchers in Africa and to nurture excellence in the academic sector throughout the continent. In particular, we will use Additive manufacturing by bioplastic from agricultural wastes and recycled plastics, and then optimize the 3D printing process parameters for development of biomedical devices, including biosensors. We will also develop Iron oxide nanocomposites for development of innovative devices for detection and removal of pollutant from clear water.

In-Memory Sensing
Von Neumann computation provided to humanity an enormous advantage allowing the spreading of computational power all around the world, nowadays largely embedded in personal electronics too (e.g., personal computers, tablets, smartphones, smartwatches, etc.). Von Neumann machines are based on an architectural concept that is based on storing data as physically separated by the core of computation. Typical examples are modern personal computers where computation is done in the CPU (Central Processing Unit) while data are stored in memories (e.g., Random-access memories, cash memories, non-volatile storage device, etc.). However, moving data from memory to processing units is «time consuming», and represents a bottleneck in computation, while Deep Learning machines exploit a kind of computation based on neural networks. Memristors seem «naturally close» to biological neurons in term of functionality, since they fuse the concept of storing and computing in a single device. Therefore, the aim of this Swiss NSF funded project is to design, realize, and demonstrate the very-first ever-proposed architecture for a new computation machine enabling the concept of «in-memory sensing»: it will automatically provide more than the present edge- computing since, since the computation will be done in the sensors, not close to the sensor.

Eurostar Project NUTRISENS
Development and characterization of the individual ion selective ISFET sensors and their integration into a multi-ISFET sensor head. New membranes for selected ions (e.g., K , NO3&, NH4 , and H2PO4&) are realized based on the recipes used for already established ion-selective membranes. Adapting ionophore-bearing, selective membranes to MICROSENS' ISFET devices with dedicated selective membrane synthesis, deposition, and testing with respect the specifications required by the application of water-plants monitoring. The packaging of multi-ISFET probes, holding individual sensors, will be designed and realized as will its housing. The design of the latter is dedicated by the constraints given by the micro FLOAT. The multi-sensor module together with an integrated miniature reference electrode will then be evaluated with respect to the basic NUTRISENS specifications

Radiation-Tolerance Humidity-Sensor for High-Energy Physics
The «next» generation (after 2025) of high-energy Physics detectors are going to be even more silicon-based. The number of channels is surpassing the billion (for a volume of ~20 m3) with very high current densities
and power consumption close to 250 kW. Cooling is then indispensable both for removal of the produced heat and for avoiding thermal runaway due to the temperature increase induced by the sensor leakage current. The cooling temperatures will range between -35 and -25 degrees Celsius. At those temperatures, vapour condensation may result in dramatic detector's damages. In order to prevent damages by vapour condensation, relative humidity needs reliable and detailed monitoring. To be accurate the dew point temperature has to be monitored but the detectors are equipped with millions of radiation hard temperature sensors that can be combined with a relative humidity measurement in order to give the dew point value. However, the performance of any relative humidity sensor operating in high-energy detectors is highly degraded. Therefore, the main goal of this research is to develop the humidity sensor that will survive in such an environment.
SWEASE (Smart WEArable Sensors for E-Health applications)
The SWEASE project is a networking project born and funded by the Department of Information Engineering of the University of Padova. The project exploits the combination of emerging printed electronics techniques (e.g. Aerosol Jet Printing), nanotechnologies, advanced front-end designs, processing techniques and on-field validation strategies to make a step ahead in the robust continuous monitoring of muscular activity and fatigue during rehabilitation exercises. The activities focus on design and fabrication of customized printed flexible and stretchable wearable sensors able to non-invasively and simultaneously measure electromyographic signals (EMG) and lactate concentration in sweat during muscular activity. Taking advantage of a portable wireless front-end, the combined information driven from the sensors during specific muscular exercises will be then processed to provide a useful feedback in rehabilitative sessions, to prevent fatigue and improve exercises personalization and effectiveness.
Smart Neural Dust to Revert Blindness
(Body Dust for Brain stimulation)Visual prostheses are used to revert blindness: a medical condition affecting more than 39 million people worldwide (WHO). So far retinal prostheses showed the best performances in clinical trial on patients. However, one of the main limitations is the low resolution as due to the limited number of electrodes that can be addressed with wires. Therefore, we propose an innovative neurostimulation by wireless device is an array of thousands freestanding, ultra-small, and individually addressable CMOS-pixels (200 x 200 x 30 μm3), as a kind of Body-Dust embedded into a conformable mesh for easy surgical placement in human visual cortex.

GlucoRaman
(Compact Glucose Sensing Using Vibrational Imaging)
With diabetes as a major disease issue for many people all around the world, the regular monitoring of the blood glucose level remains the only way to avoid severe secondary health complication through controlled insulin administration. However, present way to measure glucose level in diabetic patients is quite invasive techniques like the fingerstick testing. Therefore, we plan here the development of new and fully non-invasive blood glucose monitoring techniques that would improve significantly the life quality of diabetic subjects and help early detection and prevention of diabetes for the healthy ones.

https://www.epfl.ch/labs/iclab/index-html/bci-group/research/

En cours
Diego Ghezzi (EPFL)
Andromachi Tsirou (CERN)
Takashi Hayashita (Sophia University, Tokyo)
Christophe de la Taille (école Polytechnique de Paris)
Timothy Constandinou (Imperial Collage, London)
Jun Ohta (Nara Institue of Science and Technology)
Pantelis Georgiou (Imperial Collage, London)
Danilo Demarchi (Politecnico di Torino)
Thierry Buclin (CHUV, University of Lausanne)
Catherine Dehollain (EPFL, Lausanne)

Anciennes
Ali Khademhosseini (Harvard, Boston)
Ralph Etienne-Cummings (Johns Hopkins University, Baltimore)
Anthony Guiseppi-Elie (Clemson University/South Carolina)
Massimigliano Di Ventra (University of Califormia, San Diego)
Marie-Agnès Doucey (Ludwig Institute for Cancer Research)
Christine Nardini (Karolinska Institute, Sweden)
Giacomo Indiveri (University of Zurich, ETHZ)
Philippe Renaud (EPFL, Lausanne)
Mohamad Sawan (école Polytechnique de Montréal, Canada)
Elisabetta Chicca (Universty of Bielefeld/DE)
Ursula von Mandach (Zurich University)
Linda Thöny-Mayer (EMPA/San Gallen)
Pedro Estrela (University of Bath/UK)
Qiuting Huang (ETHZ, Zurich)
Fabio Grassi (IRB/Bellinzona)
Paolo Silacci (ALP/Posieux)
Guy Vergères (ALP/Bern)
Pascal Colpo (EU JRC/Ispra)
Yusuf Leblebici (EPFL, Lausanne)
Martin Gijs (EPFL, Lausanne)

1. Sandro Carrara, Krzysztof Iniewski, (Eds), Handbook of Bioelectronics, Cambridge University Press, Cambridge, 2015 // 2. Sandro Carrara (Aut),
Bio/CMOS Interfaces and Co-Design, Springer, New York, 2013 // 3. W.Burleson & S.Carrara (Eds),
Security and Privacy for Implantable Medical Devices, Springer, NY, 2014 // 4. Sandro Carrara (Ed),
Nano-Bio-Sensing, Springer, New York, 2011 // 5. Sandro Carrara (Aut),
Che cosa è il tempo? (italian), Simonelli, Milan, 2011 // 6. Alexander Schmid, al. et S.Carrara (Eds), Nano-Net, Springer, Berlin, 2009 // 7. C.A. Nicolini, S. Carrara, et al. (Auts), Molecular Bioelectronics, World Scientific, Singapore, 1996

S. Carrara, F. Stradolini, T. Kilic (2017), Fouling-resistant Pencil Graphite electrode, international Patent Application n° PCT/IB2017/053175 G. Köklü, S. Carrara, G. De Micheli (2013), A novel CMOS Image Sensor with Event/Change Detection and Reduced Data Redundancy. Provisional U.S. Patent Application No. 61/816,197 I. Taurino, M. Arnaud, F. Laszlo, G. De Micheli, S. Carrara, (2013) Close and Selective Integration of Carbon Nanomaterials by CVD onto working microelectrodes of multi sensing electrochemical biosensors, filed on September 13th 2013, European Patent Registration # EP 13184291.6

PhD Students in remote / Guest PhD Students
Maurine Andanje (2022-2026), Joseph Jjagwe (2022-2026), Mallikarjun Madagalam (2021-2024), Yihe Zhao (2021-2022), Maria Antonietta Casulli (2019-2022), Marco Scarpetta (2022), Mattia Alessandro Ragolia (2022), Simone Aiassa (2017-2021), Nattakarn Wuthibenjaphonchai (2018-2020), Mahshid Alsadat Padash (2019), Abuduwaili Tuoheti (2018), Sattar Akbari Nakhjavani (2018), Ana De Sousa Valinhas (2017), Sarah Tonello (2017), Xiaoling Lu (2016), Marius Schirmer (2016), Jacopo Secco (2015), Gabriella Sanzò (2014), Narayanan Srinivasan (2014), Ali Zaher (2014), Ismael Rattalino (2013), Evripides Kyriakides (2012), Alice Dimonte (2011), Giovanna De Vecchio (2010)