|Full Name||Riccardo Cadei|
|Date of Birth||16th November 1998|
|Languages||Italian (native), English (fluent), and French (beginner)|
- Causal Machine Learning for Public Health.
Harvard University – Visiting Graduate Student
- Affiliation: Department of Biostatistics at Harvard T.H. Chan School of Public Health and Harvard Data Science Initiative.
- Project: Causal Inference for Machine Learning.
- @NSAPH: Interpretable Inference of Heterogeneous Treatment Effects. Working on 1 methodological paper, 3 applied papers, 1 software paper (P.I.: Francesca Dominici).
EPFL – M.Sc. in Data Science
- Conferences: CISBAT 2021 (Lausanne), NeurIPS 2021 (remote), CVPR 2022 (New Orleans) and NeurIPS (New Orleans).
- Summer Schools: Mediterrean Machine Learning Summer School 2020 (remote), Neurosymbolic Programming Summer School (Los Angeles) and Mediterrean Machine Learning Summer School 2022 (remote).
- @VITA: Introducing the Causal (Representation) formalism and a Robust and Adaptive modular architecture for Motion Forecasting [NIPS21],[CVPR22] (P.I.: Alexandre Alahi).
- @LESO-PB: Introducing a U‐Net (FCNN) based model for detection of available rooftop area to install photovoltaic panels from satellite images [JOP21] (P.I.: Roberto Castello).
Politecnico di Milano – B.Sc. in Mathematical Engineering
- Grade: 110 (110 scale).
- Associations: PoliMI Data Scientists, Associazione Ingegneri Matematici.
- Thesis: Mathematical Programming for activity planning in an Oncology Day-Hospital (P.I.: Giuliana Carello).
Research Assistant at @NSAPH at Harvard
- Working on development and release of Bayesian Causal Forest with Instrumental Variable algorithm package and its software paper (P.I.: Francesca Dominici).
Machine Learning Researcher at Schlumberger-Doll Research in Cambridge (MA) (6-months Internship)
- Deep Learning for Causal Modeling and interpretation of acoustic (sonic and ultrasonic) subsurface data for anomaly detection and hazard prevention.
Research Assistant at @Intelligent Global Health at EPFL (Summer Internship)
- Developing a mobile app for (non-invasive) upper body posture detection using Deep Learning (P.I.: Martin Jaggi).
Machine Learning Engineer at L.O.L. Consulting Group (Freelance)
- Detecting available rooftop area to install photovoltaic panels from high quality satellite images using Deep Learning.
Student Assistant at Politecnico di Milano.
- Task: Teacher (merit based selection) for individual students and small groups.
- Courses: Calculus 1 and Linear Algebra.
Olympic Math Teacher at BrixiAmaTe.
- Task: Teacher in a Math Summer School explaining mathematical concepts, methods and techniques for Mathematical Olympiad.
- Courses: Combinatorics and Probability.
Honors and Awards
- Generali S.p.a. - Data Challenge 2020: (individual) 1st place out of 280+ participants for best model report on a Churn Classification Task and 2° (7°) best performance on public (private) test set.
- EPFL - Higgs Boson Challenge 2020: (in a team of 3) 2nd place* out of 290+ teams in the AICrowd final challenge of Machine Learning course at EPFL about Higgs Boson collisions prediction.
- Politecnico di Milano - Machine Learning for Networking Contest 2019: (individual) 1st place in the Kaggle final challenge of Machine Learning for Networking course at Politecnico di Milano about churn classification.
- Oracle Labs and Politecnico di Milano - Graph Machine Learning Contest 2019: (in a team of 2) 1st place in the Kaggle final challenge of High Performance and Graph Analytics course at Politecnico di Milano in partnership with Oracle Labs.
- International competition for mathematical and logical games: 5th national place (ITA), class L2 (Under21).
- Grand Prix of Applied Mathematics: 5th national place (ITA) out of 7500+ students.
- Grand Prix of Applied Mathematics: 6th national place (ITA) out of 7500+ students.
Software Development Skills
- Collaborative Programming: Git Hub.
- Machine Learning: Python (Numpy, Pandas, Scikit-Learn, ...), R, Julia.
- Deep Learning: Pytorch, TensorFlow.
- Numerical Mathematics: MATLAB.
- Statistics: R, Python (Statsmodels, Scipy, ...).
- Optimization: AMPL, CPLEX, Python (Numpy, Scipy, ...).
- Big Data: Apache Spark, Scala, HDFS, Hadoop, AWS.
- App and Web development: HTML, CSS, Android Studio.
- Robotics: RobotC.
- Text Editor: LaTeX.
- Marathon Runner for Atletica Paratico (Marathon regional champion U23 in 2018).
- Trainer at Politecnico di Milano's athletic team (50+ athletes) in 2018-20.
- Long distance hiker and cycle tourist.
- Other sports: Ski, Skateboard, Wind Surf, ...
- NeurIPS, BrixiAmaTe, AVIS and CARITAS.