is researcher at High Performance Computing and Networking Institute of the Italian National Research Council. He received a PhD in Mathematics defending a thesis on projection techniques for parallel sparse linear algebra and an Ms in Applied Mathematics. His postdoctoral training from National Research Council focused on low cost high performance architectures for scientific computing. He has been collaborating with Center for Applied Optimization at University of Florida since 2005. He has taught various undergraduate courses in both computer science and mathematics.
From January 2012 to December 2015, he has been leading the Laboratory for Genomics, Transcriptomics and Proteomics (Lab-GTP) http://www-labgtp.na.icar.cnr.it/),
a public-private initiative for the molecular diagnosis and gene therapy of rare genetic diseases (theranostics).
At the lab, he led a research group with several graduate fellows and postdocs.
Since January 2016, he is leading the Computational Data Science Laboratory (CDS-Lab), with 7 staff scientists, His group is composed of 4 post-docs (two computer scientists, one biotechnologist, one biologist), 3 Ph.D. students (one bioinformatician,
one computer scientist and a biologist), and several master students.
His objective is to study and develop novel algorithms, methods and software tools based on mathematical programming and statistical learning theory.
He applies his expertise to unveil biological mechanisms, using data produced by high throughput technologies, such as Microarray, SNP-array, miRNA-array, TaqMan-array, Next-Generation Sequencers (NGS), Nuclear Magnetic Resonance (MNR), Raman and mass spectrometers.
His aim is to help life scientists to have a better insight in their problems, without the hassle of integrating and inspecting large quantities of data coming from different sources.