A geometric deep learning method for decoding brain dynamics
EPFL scientists have developed a geometric deep learning method that can create a coherent picture of neuronal population activity during cognitive and motor tasks across experimental subjects and conditions.
“Designing Life with AI” is a cross-disciplinary MAKE project in which EPFL students get a chance to explore the research process by designing proteins. A total of eight research labs are involved.
Choosing the best medical treatment with the help of AI
To advance modern medicine, EPFL researchers are developing AI-based diagnostic tools. Their goal is to predict the best treatment a patient should receive.
EPFL researchers have developed a computational method to explicitly consider the impact of water while designing membrane receptors with enhanced stability and signaling, paving the way for novel drug discovery and protein engineering.
New study improves the trustworthiness of wind power forecasts
By applying techniques from explainable artificial intelligence, engineers can improve users’ confidence in forecasts generated by artificial intelligence models. This approach was recently tested on wind power generation by a team that includes experts from EPFL.
A Deep Learning Pipeline for Controlling Protein Interactions
EPFL scientists have used deep learning to design new proteins that bind to complexes involving other small molecules like hormones or drugs, opening up a world of possibilities in the computational design of molecular interactions for biomedicine.
Three SNSF Advanced Grants awarded to EPFL researchers
The Swiss National Science Foundation (SNSF) has awarded three “SNSF Advanced Grants” to EPFL researchers, including Florent Krzakala in the School of Engineering.
