Biography
Lorenzo Madeddu is a senior data scientist (R&D) in the Knowledge Graph Insights team at AstraZeneca (Sweden). He received his PhD from Sapienza University of Rome. His research interests include machine learning, network theory, and network biology. He develops machine learning algorithms in interdisciplinary projects in the fields of healthcare and graph mining.
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Interests
- Machine Learning
- Bioinformatics
- Network Biology
- Network Pharmacology
- Data Visualization
Education
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PhD in Innovative Biomedical Technologies in Clinical Medicine, 2022
Sapienza University of Rome
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MSc in Computer Science (Grade: 110/110 with honors; GPA 4.00), 2018
Sapienza University of Rome
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BSc in Computer Science (Grade: 108/110; GPA 4.00), 2016
Sapienza University of Rome
Recent Experiences
Senior Data Scientist (R&D)
Developed graph mining frameworks for large biomedical knowledge graphs to investigate novel pharmaceutical insights.
Machine Learning Teacher
Recorded 17 Machine Learning lessons.
Data Science Teacher
Teaching assistant for the Data Visualization course.
Machine Learning Scientist (PhD experience)
Tested 6000+ drugs with network pharmacology and machine learning strategies in order to uncover effective treatments for the COVID-19 infection
Protein-Protein Interaction Prediction Challenge
Worked with an international team of academics from Harvard University and Sapienza University of Rome, to develop a research challenge for predicting new protein-protein interactions. Co-researcher and I developed a protocol for evaluating, analyzing and testing the methods and results submitted by challenge participants. We worked within the organizing team to provide the requirements and datasets to the research teams (Conference Program) (Video)
Machine Learning Scientist in the International AI task-force on COVID-19
- Released a public bioinformatic dataset on Covid-19 for drug repurposing tasks. The dataset includes protein-protein interactions, drug-target interactions, COVID-19 targets, drug structures and protein functions (GitHub) (Video)
- Developed a drug repurposing deep learning model for Covid-19 (submitted paper)
Featured Publications
Recent Publications
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(2021).
Deep Graph Networks for Drug Repurposing with Multi-Protein Targets.
Submitted.
(2021).
Deep Learning Methods in Network Biology.
By World Scientific.
(2021).
Integrating Categorical and Structural Proximity in Disease Ontologies.
In EMBC.
Talks
Books
Attended & Awards
The foundational concepts of neural networks and deep learning
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womENcourage Hackathon 2019 (Winner)
Hackathon event aimed at bringing participants from diverse technical disciplines together to collaborate on developing a novel solution for the challenge of “Enabling Sustainable Cities Through Blockchain”
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womENcourage 2019 (Volunteer)
Event aimed at bringing participants from diverse technical disciplines to discuss pressing issues of women in the computing profession
DeepLearn Summer School 2019
Research training event about the most recent advances in the critical and fast developing area of deep learning