Andrea Mastropietro
About
I'm a Computer Engineer with a Ph.D. in Data Science.
Currenlty, I'm a Short-term Postdoctoral Research Fellow at the Lamarr Institute at the University of Bonn and upcoming Postdoctoral Researcher (Jan 2025).
I was a Postdoctoral Project Researcher at the Department of Computer, Control and Management Engineering (DIAG) of Sapienza University of Rome.
My research interests are in the field of AI for medicine, mainly focusing on deep learning and XAI in bioinformatics and chemoinformatics.
During my Ph.D., my advisor was Aris Anagnostopoulos (Sapienza) and my co-advisor Paolo Tieri (CNR).
I was teaching assistant (TA) for the Data Mining, Social Network and Online Markets and Bioinformatics and Network Medicine courses.
From September 2022 to February 2023, I was a visiting Ph.D. researcher at the Department of Life Science Informatics and Data Science, B-IT, LIMES Institute at The University of Bonn. I worked here under the supervision of Prof. Jürgen Bajorath.
Education
Ph.D. in Data Science, Sapienza University of Rome. Summa cum Laude.
Doctor Europaeus.
Visiting Ph.D. researcher at the University of Bonn (Germany).
MSc in Engineering in Computer Science, Sapienza University of Rome. 110/110 Summa cum Laude.
Excellent Graduate A.Y. 2018/19.
Honours Programme.
Erasmus Programme at Polytechnic University of Catalonia (Barcelona, Spain).
BSc in Computer and System Engineering, Sapienza University of Rome 110/110 Summacum Laude.
Honours Programme.
High School Degree, Liceo Scientifico A. Labriola, 100/100 Summa cum Laude.
Publications
Latest research
Mastropietro, A., & Bajorath, J. (2024). Protocol to explain support vector machine predictions via exact Shapley value computation. STAR protocols, 5(2), 103010. https://doi.org/10.1016/j.xpro.2024.103010.
Mastropietro, A., Pasculli, G. & Bajorath, J. Learning characteristics of graph neural networks predicting protein–ligand affinities. Nature Machine Intelligence (2023). https://doi.org/10.1038/s42256-023-00756-9. Read here: https://rdcu.be/dqZlS.
Mastropietro, A., Feldmann, C. & Bajorath, J. Calculation of exact Shapley values for explaining support vector machine models using the radial basis function kernel. Sci Rep 13, 19561 (2023). https://doi.org/10.1038/s41598-023-46930-2.
Andrea Mastropietro, Gianluca De Carlo, Aris Anagnostopoulos, XGDAG: eXplainable Gene–Disease Associations via Graph Neural Networks, Bioinformatics, Volume 39, Issue 8, August 2023, btad482, https://doi.org/10.1093/bioinformatics/btad482
For a full list of my publications, see here.
Teaching
For courses/labs, click here.
Achievements, Grants & Awards
2024
Recipient of the first Lamarr Stipendium Program Fellowship for postdoctoral researchers.
2023
My joint research with Gianluca De Carlo "Enhancing Drug Repurposing via Explainable Geometric Deep Learning for Knowledge Graphs " won the grant Fondi di Avvio alla Ricerca Tipo 1.
2022
My research "Explaining Graph Neural Networks in Medicinal Chemistry" won the grant Fondi di Avvio alla Ricerca Tipo 2.
2021
My research "Neural Network Interpretability in Bioinformatics" won the grant Fondi di Avvio alla Ricerca Tipo 1.
Best presentation/poster award: "Feature Selection in Neural Networks via Rank Aggregation", 4th Advanced Online & Onsite Course on Data Science & Machine Learning (ACDL 2021).
2020
Copernicus Masters 2020 - ESA DTE Challenge and Copernicus Prize Italy winners: U-GEO, Urban Green from Earth Observation.
Contacts
Email: mastropietro [at] bit.uni-bonn.de