Digipredict detects the first signs of a ‘cytokine storm’ in high-risk COVID-19 patients, thus allowing doctors to act before it causes serious damage to the cardiovascular systems. Cytokines are proteins that play an important role in normal immune responses, but having a large amount of them released in the body all at once can be harmful.
The Board of the Swiss Federal Institutes of Technology has announced the appointment of Pascal Frossard as Full Professor of Electrical Engineering and Electronics in the School of Engineering (STI). Currently Associate Professor at EPFL, he joined the EcoCloud faculty in 2018 to help the research centre drives its cloud computing programs.
About a year ago, when the novel coronavirus broke out, medical science not only failed to arrest its spread but also to properly identify the developmental stages of the disease. Many casualties resulted because the progression of the disease was an enigma. In the later part of the year, there were nascent attempts to harness AI for COVID-19 diagnosis, treatment, and monitoring. A giant step in that direction has been taken recently by researchers at EPFL; they have developed algorithms that can practically see and hear COVID in a patient’s lungs.
At least three EPFL laboratories are working in tandem on the project: Computer Vision Laboratory led by Professor Pascal Fua, Realistic Graphics Lab led by Assistant Professor Wenzel Jakob, and Embedded Systems Lab spearheaded by Professor David Atienza (also a faculty member at EcoCloud).
We are investigating new stochastic theories and analytics including statistical learning techniques, machine training and inference systems and their applications to IoT, social media and big data platforms.
We are investigating technologies to maximize efficiency with in-memory data services, in-situ query processing on streamed data, and on-demand query engine customization using multi-objective compiler optimization.
We are investigating a three-pronged approach to holistic data platforms and datacenter efficiency: vertical integration to minimize data-movement; specialization to optimize work per service; and approximation to tailor work for output quality.
We are investigating technologies spanning from decentralized trust and cryptography to robustness and resiliency of natural processes to strengthen security, privacy and trust in data platforms and systems.