Description of the legal entity :

Universidad Politécnica de Madrid (UPM, www.lia.upm.es) is the Technical University of Madrid and is the largest Spanish technological university. More than 2,400 researchers carry out their activity at the UPM, grouped in 204 Research Groups, 19 Research Centers or Institutes and 55 Laboratories.

UPM headed the Spanish University participation in the 7th European Framework Program with 286 projects and 83M€ funding. In H2020 UPM keeps on its active participation thank to its highly innovation driven profile. Furthermore, the UPM European Project Office consisting of 11 highly qualified professionals supports researchers when managing the European projects of the University.

Alfonso Rodríguez Patón (M) (ORCID: 0000-0001-7289-2114)). He is PI of the Artificial Intelligence Lab in UPM. Full professor of Artificial Intelligence since 2019 in UPM. He is an electronic physicist by training and was awarded his Ph.D. in DNA Computing in 1999 (third thesis in the world in this field). Dr. Rodríguez-Patón is first-time participant in a granted FET-H2020 project.

Role in the project :

UPM will participate in WP3 using AI tools for SERS active molecules prediction.

UPM will participate in WP4 in the development of AI algorithms for multiplex detection Raman reporters

UPM will participate in WP5 in the simulation of continuous flow and droplet microfluidic systems).

Infrastructure and facilities :

Artificial Intelligence Lab has 12 PCs and has access to the supercomputer installed in the UPM and called Magerit (CESVIMA). This High-Performance Computing facility consists of 3920 Power7 cores (103,50 TFLOPS Rpeak) and 656 Intel cores (13,64 TFLOPS Rpeak) that we could use to run simulations.

Related projects and publications :

PI and coordinator of FET-Proactive FP7 PLASWIRES (www.plaswires.eu) Project ID: 612146. PI and partner of a FET-Proactive FP7 EVOPROG (www.evoprog.eu) Project ID: 610730.  PI and partner of a FET-Proactive FP7 BACTOCOM (Bacterial Computing with Engineered Populations).


  • López-Igual R, Bernal-Bayard J, Rodríguez-Patón A, Ghigo JM, Mazel D. Engineered toxin-intein antimicrobials can selectively target and kill antibiotic-resistant bacteria in mixed populations. Nature Biotechnology 2019 Jul;37(7):755-760.
  • Gutiérrez, M. et al. A New Improved and Extended Version of the Multicell Bacterial Simulator gro. ACS Synth. Biol. (2017).
  • Gupta, V., Irimia, J., Pau, I. & Rodríguez-Patón, A. BioBlocks: Programming Protocols in Biology Made Easier. ACS Synth. Biol. 6, 1230–1232 (2017).
  • Beneš, D., Rodríguez-Patón, A. & Sosík, P. Directed evolution of biocircuits using conjugative plasmids and CRISPR-Cas9: design and in silico experiments. Nat. Comput. 16, 497–505 (2017).
  • Amos, M. et al. Bacterial computing with engineered populations. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 373, 20140218 (2015).
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