Ilia Azizi is a PhD candidate at HEC Lausanne, interested in applied Machine Learning, interpretability, and modeling multi-modal data (structured and unstructured data). With a multicultural background and highly dynamic education, he aims to break through the world of data analytics and rigorously apply data in answering challenging business questions.
Aside from having a passion for data, he analyzes high-tech firms to foresee those that can make the future happen sooner. His interests outside of work fall on traveling, playing the piano, and hiking through the Swiss mountains.
MSc in Management, Spec. in Business Analytics, 2022
Swiss Mobility (SIM), 2021
University of St. Gallen
BSc in Economics and Management, 2018
University of Rome Tor Vergata
Erasmus Exchange Program, 2018
University of Ghent
FaceRunner is a program written in Python for face detection and mask overlays possible through existing images or streaming live through a webcam.
A project where the the effect of speed limits and the weather conditions on road accidents in New York City was studied extensively.
Determining whether the weather (i.e. rain and snow) influences the length of the taxi trips in the city of Chicago.
Using deep learning, and neural networks, to identify COVID-19 and viral pneumonia from the x-ray scans of patients.
Modelling COVID-19 using a SIR model (Suscepitble, Infectious, Recovered/Removed) commonly implemented for epidemiological studies.
Text mining techniques applied to employer reviews from Glassdoor.com with the aim of predicting the stars given to the employers.