News
Evolutionary Intelligence group news
Evolutionary Algorithms for high-quality solutions
It is not uncommon that the solution obtained by an algorithm is not as desired. To overcome this, Stef Maree's PhD research focuses on optimization algorithms for finding not just one solution, …
AI Calculates Best Treatment Plan
A computer that calculates an entire series of optimized treatment plans for prostate cancer in 30 seconds – that took some getting used to for medical specialists. Using artificial intelligence, the computer …
Marie Curie ITN grant awarded to ALPACA network
Recently, CWI and others were awarded an EU Marie Skłodowska-Curie Innovative Training Networks (ITN) consortium grant for ALPACA –'Algorithms for PAngenome Computational Analysis'. The research project involves a total funding of 3.67 …
CWI designs algorithms for the improvement of Genetic Programming
Marco Virgolin of CWI’s Life Sciences & Health group has researched ways to improve the efficiency and effectiveness of Genetic Programming (GP). He defends his thesis ‘Design and Application of Gene-Pool Optimal …
Peter Bosman awarded grant of 1M euros from NWO’s Open Technology Programme
Peter Bosman’s project proposal DAEDALUS (Distributed and Automated Evolutionary Deep Architecture Learning with Unprecedented Scalability) has been granted by NWO TTW in its Open Technology Programme.
€1.5 million European grant for mathematics consortium NETWORKS
The NETWORKS consortium can now continue growing thanks to a €1.5 million grant from the European Union’s Horizon2020 programme.
Artificial Intelligence proposes the best radiation treatment plans in clinical practice for the first time
CWI and Amsterdam UMC have developed software that helps radiation oncologists to make internal radiation treatment plans for prostate cancer. Today, the first patient was treated with a plan made with the …
CWI researchers involved in two NWO-Groot grants
In the NWO Open Competition ENW-GROOT programme, four CWI researchers received in total two grants to study machine learning and neural networks: Nikhil Bansal, Monique Laurent, Benjamin Sanderse and Leen Stougie.
