Ilia Azizi

Ilia Azizi

PhD Candidate

University of Lausanne

About me

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.

Interests

  • Machine Learning
  • Deep Learning
  • Multi-Modality

Education

  • MSc in Management, Spec. in Business Analytics, 2022

    HEC Lausanne

  • 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

Journal Article

Ilia Azizi, Iegor Rudnytskyi (2022). Improving Real Estate Rental Estimations with Visual Data. Big Data and Cognitive Computing.

PDF Dataset DOI

Experience

 
 
 
 
 

PhD Candidate (Business Analytics)

University of Lausanne, HEC

Mar 2022 – Present Lausanne, Switzerland
PhD candidate in Business Analytics, working on topics such as applied Multi-Modal Machine Learning under the supervision of Dr. Marc-Olivier Boldi.
 
 
 
 
 

Teaching Assistant (Machine Learning)

University of Lausanne, HEC

Feb 2022 – Feb 2022 Lausanne, Switzerland
Teaching assistant (40%) in Machine Learning.
 
 
 
 
 

Data Science Intern (Natural Language Processing)

Nestlé Research

Aug 2021 – Jan 2022 Lausanne, Switzerland
Working on Natural Language Processing (NLP) and creating AI-based solutions for food Named-Entity Recognition.
 
 
 
 
 

Teaching Assistant (Deep Learning)

University of Lausanne, HEC

Feb 2021 – Jun 2021 Lausanne, Switzerland
Teaching assistant (20%) of Dr. Iegor Rudnytskyi for a course in Deep Learning and Neural Networks.
 
 
 
 
 

Research Assistant (Data Science)

University of Lausanne, HEC

Oct 2020 – Aug 2021 Lausanne, Switzerland
Research assistant (20-100%) of Prof. Christian Peukert on a research project covering the topics of digital strategy and data analytics.
 
 
 
 
 

Teaching Assistant (Data Science)

University of Lausanne, HEC

Sep 2020 – Dec 2020 Lausanne, Switzerland
Teaching assistant (20%) of Prof. Thibault Vatter, a visiting professor from Columbia University.
 
 
 
 
 

Teaching Assistant (Innovation Strategy Project)

University of Lausanne, HEC

Feb 2020 – Jun 2020 Lausanne, Switzerland
Teaching assistant (15%) of Mrs. Rita Queiros for the company project in Innovation Strategy.
 
 
 
 
 

Part-time Student Collaborator

University of Rome Tor Vergata

Feb 2018 – Feb 2019 Rome, Italy
  1. Library receptionist (Sep 2018-Feb 2019):
  • Entrusted with running the library during the evenings and weekends.
  1. Secretary assistant (Feb 2018-Jul 2019):
  • Responsible for organizing lectures and exams at Centro Linguistico di Ateneo.
 
 
 
 
 

Freelance Animator

Arya Arman Pasargad

Jan 2018 – Feb 2018 Tehran, Iran
Produced , directed and narrated a promotional video explaining the benefits of GPS systems.

Side Projects

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All Data Science Business Intelligence Deep Learning Python Program

FaceRunner

FaceRunner is a program written in Python for face detection and mask overlays possible through existing images or streaming live through a webcam.

Accidents in NYC

A project where the the effect of speed limits and the weather conditions on road accidents in New York City was studied extensively.

Taxi Trips in Chicago

Determining whether the weather (i.e. rain and snow) influences the length of the taxi trips in the city of Chicago.

COVID-19 identification from X-rays

Using deep learning, and neural networks, to identify COVID-19 and viral pneumonia from the x-ray scans of patients.

Modelling COVID-19

Modelling COVID-19 using a SIR model (Suscepitble, Infectious, Recovered/Removed) commonly implemented for epidemiological studies.

Glassdoor+Text Mining

Text mining techniques applied to employer reviews from Glassdoor.com with the aim of predicting the stars given to the employers.

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