Stefano Civelli

Stefano Civelli

HDR Student in AI at UQ

I am a Master of Philosophy (MPhil) student in Computer Science at The University of Queensland, focusing on Large Language Models (LLMs).

Previously, I worked for a small startup in Milan, obtained my Master's degree in Computer Science from Politecnico di Milano (POLIMI) and then worked as a Research Assistant at The University of Queensland.

I am also Tutor for DATA7201 at UQ.

Recent Research

The Impact of Persona-based Political Perspectives on Hateful Content Detection

Stefano Civelli, Pietro Bernardelle, Gianluca Demartini
TheWebConf'25: MM4SG Workshop. 2025
Paper

Mapping and Influencing the Political Ideology of Large Language Models using Synthetic Personas

Pietro Bernardelle, Leon Fröhling, Stefano Civelli, Riccardo Lunardi, Kevin Roitero, Gianluca Demartini
TheWebConf'25: Short Paper. 2025
PaperCode

Resume

  • PhD in Artificial Intelligence at The University of Queensland
    Oct. 2024
    Researching core aspects of Large Language Models (LLMs) like prompt complexity and bias. Developing novel methods to measure and predict query complexity for LLMs.
  • Research Assistant at The University of Queensland
    Feb. 2024 - Aug. 2024
    Conducted research on LLMs for classification of harmful content. Implemented multimodal ML models in PyTorch. Analyzed Facebook ads for political campaigns. Deployed AWS-based dashboard for campaign analysis.
  • ML Engineer Intern at ML cube
    Apr. 2023 - Dec. 2023
    Developed RL solution for AGV mission time estimation. Implemented classic and distributional RL algorithms for time estimation.
  • M.Sc. in Computer Science and Engineering at POLIMI
    Sep. 2021 - Dec. 2023
    Graduated with 110L/110. Main courses: Machine Learning, Neural Networks, Distributed Systems, Data Streaming, Recommender Systems. Received Merit-Based Scholarship for two consecutive years.
  • B.Sc. in Computer Science and Engineering at POLIMI
    Sep. 2018 - Jul. 2021
    Graduated with 109/110. Main courses: software engineering, databases, algorithms & data structures, statistics, linear algebra. Awarded Best freshmen 2018/2019.