Giovanni Trappolini
REsearch Fellow@Sapienza University
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WHO AM I?
Hi everyone!
My name is Giovanni Trappolini.
I obtained an MSc in Data Science, graduating as one of Sapienza University's top students with a thesis on multi-resolution topological data analysis.
I went on to obtain a Ph.D. in Machine Learning under the supervision of Emanuele Rodolà and the exciting environment of the GLADIA Lab.
At present, I am a Research Fellow at Sapienza University, working with Prof. Fabrizio Silvestri in the RSTLess Lab.
My research interests are machine and deep learning, with a keen enthusiasm for applying these methodologies to technical and scientific problems.
PUBLICATIONS
Sparse Vicious Attacks on Graph Neural Networks; IEEE Transactions on Artificial Intelligence; 2023
Multimodal Neural Databases; SIGIR2023
Renormalized Graph Neural Networks; Arxiv; 2023
RRAML: Reinforced Retrieval Augmented Machine Learning; AIxIA; 2023
FLIRT: Federated Learning for Information Retrieval; Workshop@SIGIR2023
Fauno: The Italian Large Language Model that will leave you senza parole!; IIR2023
CycleDRUMS: automatic drum arrangement for bass lines using CycleGAN; Discover Artificial Intelligence, 2022
Toward Precise Shape Completion; ECCV 2020
Shape Registration in the Time of Transformers; NeurIPS 2021
Multi-resolution topological data analysis for robust activity tracking; SIS 2019
SHORT RESUME
[July 2022 - present] Post-Doc @ RSTLess Lab, Sapienza University
[November 2018 - June 2022] Ph.D student in Machine Learning at the Department of Computer, Control, and Management Engineering of Sapienza University of Rome.
[June 2018 - October 2018] Data Scientist at TIM.
[January 2018 - May 2018] Student Honor programme.
[October 2016 - October 2018] MSc in Data Science, graduated cum laude and awarded the title of "Sapienza honor graduate".
[September 2013 - July 2016] BSc awarded from Luiss Guido Carli.
[June 2012] Diploma from Kamiak High School, Seattle (WA).
Languages: Italian mother tongue; proficient in English; Basic Spanish.
Programming Languages: Python, R, Java, Spark, Matlab. Proficiency with standard deep learning libraries.
Preferred Toolkit: Python-Lighting + Wandb
Certificates: IELTS 8.0
teaching
[2023] Advanced Data Mining and Language Technologies, at Sapienza
[2022] The Python Programming Language for Data Science, at Sapienza
[2021] The Python Programming Language for Data Science, at Sapienza
[2020] The Python Programming Language for Data Science, at Sapienza
[2019-2020] Introduction to Statistics, at Luiss Guido Carli
[2019-2020] Introduction to Statistical Learning, at Luiss Guido Carli
[2019] The Python Programming Language for Data Science, at Sapienza
[2018-2019] Introduction to Statistics, at Luiss Guido Carli