27.04.202210:20

Two 2021 ERC Advanced Grants to Politecnico

To Manuela Raimondi, with BEACONSANDEGG, and to Daniele Ielmini, with ANIMATE


 

From studying breast cancer to reducing energy consumption in data processing. The Politecnico di Milano has secured two 2021 ERC Advanced Grants awarded by the European Research Council (ERC) for established researchers in their field to carry out innovative and high-risk projects. The grants have been awarded to Professor Manuela Raimondi, with the BEACONSANDEGG project, and to Professor Daniele Ielmini, with the ANIMATE project.

The University once again proves to be at the forefront, having outperformed its scholarly competitors in a very competitive selection process, with only 14.6% of the 1735 projects submitted receiving funding. With these two projects, the Politecnico di Milano has been awarded a total of 86 European Individual Grants (including ERC and Marie Curie).


Daniele Ielmini, professor at the Department of Electronics, Information and Bioengineering, will conduct ANIMATE (ANalogue In-Memory computing with Advanced device Technology), a project that aims to develop a new computational concept to reduce energy consumption in machine learning.

We generate, process and use a huge amount of data every day. Searching for a keyword on the internet, choosing a film for the weekend or booking our next holiday are just some of the actions that rely on data-intensive algorithms. The energy cost of this type of calculation is extremely high: it has been estimated that training a conventional neural network for artificial intelligence (AI) produces the same amount of carbon dioxide as 5 cars in their life cycle. Data centres, which currently meet most of the world's AI needs, now consume about 1% of global energy demand, with growth expected to reach 7% by 2030. To correct this worrying trend, new energy-efficient hardware solutions are needed. Professor Ielmini's preliminary ANIMATE research has shown that computational energy requirements can be reduced by closed-loop in-memory computing (CL-IMC), which can solve linear algebra problems in a single computational step.

In CL-IMC, the time to solve a given problem does not increase in proportion to the size of the problem, unlike other computing concepts, such as digital and quantum computers. Thanks to the reduction in calculation time, CL-IMC requires 5,000 times less energy than digital computers with the same accuracy in terms of number of bits. Ielmini's project will develop the device and circuit technology, system architectures and set of applications to fully validate the CL-IMC concept. System-level architecture and exploring its applications will further prove the scalability and feasibility of the concept, to prove that CL-IMC is a major contender among energy-efficient computing technologies.


Manuela Raimondi, professor at the Department of Chemistry, Materials and Chemical Engineering "Giulio Natta", will work on BEACONSANDEGG (Mechanobiology of cancer progression), a project that combines mechanobiology with bioengineering, oncology, genetics, microtechnology, biophysics and pharmacology in order to develop an innovative platform capable of recapitulating tumour fibrosis by exploiting the vascularisation of a living organism.

In breast cancer, aggressiveness is related to fibrotic stiffening of the tumour tissue. Fibrosis progressively prevents drugs from reaching the tumour cells, due to the formation of a matrix with mechanical properties that stabilise the tumour's vascular network. However, the hierarchy and stability of the tumour vascular network are not reproducible in vitro. The BEACONSANDEGG research will model microtumours at various levels of fibrosis. Human breast cancer cells adhered to 3D polymeric microplates will be used. The microtumours will be implanted in vivo in the respiratory membrane of embryonated avian eggs in order to elicit a fibrotic foreign body reaction in the microtumours. The geometry of the 3D microsupports will be manipulated to condition the infiltration of the microtumours by the vessels and cells of the embryo. This study model will be validated with anticancer drugs whose clinical outcome is known to depend on the level of tumour fibrosis. This project will also provide a standardised and ethical platform to promote the clinical translation of new therapeutic products in oncology.

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