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Sergio Decherchi

Technologist - Facility Coordinator
Data Science & Computation Facility
Research center

Sergio Decherchi obtained the Laurea degree summa cum laude in Electronic Engineering in 2007 from Genoa University, Italy, Europe. In 2011 he obtained a PhD in Electronic Engineering and Computer Science on Machine Learning and Data Mining from the same University while working at the Department of Biophysic and Electronic Engineering (DIBE). From 2011 to 2016 he was Post Doctoral researcher at the Istituto Italiano di Tecnologia (IIT), Genoa, Italy, Europe, Department of Drug Discovery and Development (D3) where he designed, developed and applied computational intelligence/chemistry methods to drug discovery. He is the designer and developer of NanoShaper, a tool for molecular surface computation and pockets detection  . In 2014 Sergio co-founded BiKi Technologies s.r.l. a company dealing with Molecular Dynamics and machine learning methods for drug discovery. From 2017 to 2022 Sergio is technologist in IIT. In 2022 he obtained the national habilitation as Associate Professor in computer science. From 2023 he is the coordinator of the Data Science and Computation IIT facility. He is author of more than 70 papers on peer reviewed Journals and conferences in the fields of computational intelligence and computational chemistry. Sergio has received some awards, EU/national/private grants, delivered several invited talks/lectures and co-organized some workshops (e.g. ECAM/CECAM). He is reviewer for EU and national funding agencies. He serves as Associate Editor for the Springer Journal, Cognitive Computation.

All Publications
Rocutto L., Maronese M., Traversa F.L., Decherchi S., Cavalli A.
Assessing the Effectiveness of Non-Turing Computing paradigms
IEEE Access
Article Journal
Abate C., Decherchi S., Cavalli A.
Graph neural networks for conditional de novo drug design
Wiley Interdisciplinary Reviews: Computational Molecular Science
Article Journal
Di Palma F., Abate C., Decherchi S., Cavalli A.
Ligandability and druggability assessment via machine learning
Wiley Interdisciplinary Reviews: Computational Molecular Science
Review Journal
Majumdar S., Di Palma F., Spyrakis F., Decherchi S., Cavalli A.
Molecular Dynamics and Machine Learning Give Insights on the Flexibility-Activity Relationships in Tyrosine Kinome
Journal of Chemical Information and Modeling
Article Journal
Aguti R., Bernetti M., Bosio S., Decherchi S., Cavalli A.
On the allosteric puzzle and pocket crosstalk through computational means
Journal of Chemical Physics, vol. 158, (no. 16)
Article Journal
Organized Events
Cavalli A., Decherchi S., Ferrarotti M., Rocchia W.
Extended Software Development Workshop: high performance computing for simulation of complex phenomena
Decherchi S., Bonella S., Cavalli A.
Scoping workshop: Building the bridge between theories and software: SME as a boost for technology transfer in industrial simulative pipelines