Davide Vega D'Aurelio

Most of my teaching and supervision at Uppsala University fails within one of my research areas or in the field of software engineering and project management.

Uppsala and prospective students:
If you are keen on pursuing a research and/or development project for a master/bachelor thesis or a course project feel free to get in touch! You can find the updated list of project proposals for the next period below, or at the website of the UU-InfoLab research group. Normally, students must have spent at least a semester at Uppsala University and are required to have taken at least one course in either data science (such as 1DL007, 1DL370, 1MS031, 1RT003) or in software engineering (such as 1DL251, 1DL242) relevant for the project.

Summer interships:
I am no longer hosting summer interns.

Letters of recommendation:
If you consider asking me for a letter of recommendation, please consider these guidelines by Sarah Park.

Courses

  • InfoLab - Introduction to Network Science (Spring 2024)

    PhD level, 5 credits. Uppsala University.
    Also taught in Spring 2022

  • 1DL007 - Introduction to Computational Social Science (Spring 2024)

    Bachelor level, 7.5 credits. Uppsala University.
    Also taught in Spring 2022 and Spring 2023

  • 1DL251 - Software Engineering and Project Management (Autumn 2023)

    Master level, 5 credits. Uppsala University.
    Also taught in Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2023 and Spring 2023

  • 1DL242 - Advanced Software Design (Autumn 2021)

    Master level, 5 credits. Uppsala University.
    Also taught in Autumn 2020

  • 1DL601 - Maintenance Programming (Autumn 2021)

    Master level, 5 credits. Uppsala University.
    Also taught in Autumn 2019

Supervised Projects

The Allure of Automated Machine Learning Services: How SMEs and non-expert users can benefit from AutoML frameworks

Felix Lux Dryselius
Master Thesis, Uppsala University, Uppsala, Sweden.
DiVA Abstract

Automated Extraction of Insurance Policy Information

Jacob Hedberg and Erik Furberg
Master Thesis, Uppsala University, Uppsala, Sweden.
DiVA Abstract

Evaluating the Ownership of Personal data in the Cloud by Optimizing the IT Architecture

Tilda Myrsell and Sofia Hulteberg
Master Thesis, Uppsala University, Uppsala, Sweden.
DiVA Abstract

International mobility patterns in competitive sports events

Liv Cerdin, Elias Insulander and David Wiberg
Project in Data Science, Uppsala University, Uppsala, Sweden.
Abstract

Scalable Network Analysis Platform

Nikitha Thodkar and Weilin Zhang
Project in Data Science, Uppsala University, Uppsala, Sweden.
Abstract

Tracking the Conversation around NATO in the Nordic States Using Machine Learning

Benedict Treeby
Master Thesis, Uppsala University, Uppsala, Sweden.
DiVA Abstract

The Portrayal of the 2022 Russian Invasion of Ukraine on Social Media

Alexander Tsakiris
Master Thesis, Uppsala University, Uppsala, Sweden.
DiVA Abstract

Exploring How Swedish News are Framed Online

Alexander Bergkvist, Benedict Treeby, Joakim Michalak and Mathilde Abolgassemi
Project in Data Science, Uppsala University, Uppsala, Sweden.
Abstract

A Scalable Platform for Data-Intensive Visualization

Suling Xu and Zezhong Zeng
Master Thesis, Uppsala University, Uppsala, Sweden.
DiVA Abstract

Listening in on Productivity: Applying the Four Key Metrics to measure productivity in a software development company

Johanna Dagfalk and Ellen Kyhle
Master Thesis, Uppsala University, Uppsala, Sweden.
DiVA Abstract

Computational Analysis of Swedish Newspapers Using Topic Detection and Sentiment Analysis

Simon Wallbing
Bachelor Thesis, Uppsala University, Uppsala, Sweden.
DiVA Abstract

Stochastic blockmodeling methods for bipartite graphs

Deepthi Hulithala Venkataramana and Naeim Rashidfarokhi
Project in Computational Science, Uppsala University, Uppsala, Sweden.
Abstract

A system for GDPR-compliant collection of social media data: from legal to software requirements

Fredrik Jonasson
Bachelor Thesis, Uppsala University, Uppsala, Sweden.
DiVA Abstract

Text to features for Swedish text

Man Dan Ly
Bachelor Thesis, Uppsala University, Uppsala, Sweden.
DiVA Abstract

Pattern Detection in Bipartite Temporal Network

Nam Nguyen Hai
Master Thesis, Uppsala University, Uppsala, Sweden.
DiVA Abstract

Cyber Challenge Competition 2019

Clara Engman, Gustav Fredriksson, Frida Kornsäter and Elin Sjörman
Project, Swedish Defence University, Swedish Civil Contingencies Agency MSB, Stockholm, Sweden.
Abstract

Measure development and social media analysis using temporal text networks

Hampus Falk
Bachelor Thesis, Uppsala University, Uppsala, Sweden.
DiVA Abstract