About Me
Short Bio
I am a modern Data Engineer with extensive experience as a Machine Learning Developer, specializing in Natural Language Processing. My work goes beyond just managing terabytes of data in modern databases; I am deeply involved in the entire machine learning deployment process as well. This focus wasn’t by accident: I believe that a great ML model starts with great data. Over time, I have leaned into Data Engineering, driven by a desire to be the kind of Data Engineer I would have loved to have had as a Junior Scientist.
Some Facts
I hold a PhD in Statistics from Bocconi University, with a strong foundation in Probability and Statistical Modeling. During my PhD (2014-2017), I specialized in Multivariate Survival Models. Below is a selection of my published works:
- Giussani, A. (2021). Applied Machine Learning with Python, Bocconi University Press.
- Giussani, A. & Bonetti, M. (2019). A Note on the Length-Biased Weibull-Gamma Frailty Survival Model. Computational Statistics & Data Analysis, Volume 153, Pages 32-36.
- Giussani, A. & Bonetti, M. (2019). Marshall–Olkin Frailty Survival Models for Bivariate Right-Censored Failure Time Data. Statistics in Medicine, Volume 46, Pages 2945-2961.
- Maconi, G., Bolzoni, E., Giussani, A., Friedman, A.B. & Duca, P. (2014). Accuracy and Cost of Diagnostic Strategies for Patients with Suspected Crohn’s Disease. BMC Medical Informatics and Decision Making, Volume 12, Pages 1684-1692.
- Benedetto, L., Cremonesi, P., Cappelli, A., Giussani, A., & Turrin, R. (2022). Survey on Recent Approaches to Question Difficulty Estimation from Text. ACM Computing Surveys.
- Benedetto, L., Aradelli, G., Cremonesi, P., Cappelli, A., Giussani, A., & Turrin, R. (2021). The Application of Transformers for Estimating the Difficulty of Multiple-Choice from Text. Proceedings of the 16th Workshop on Innovative Use of NLP in Education.
I continue my collaboration with Bocconi University as an Academic Fellow in Computer Science. Currently, I teach Applied Machine Learning with Python, offering students the tools and knowledge to apply machine learning techniques using Python.
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