Dimitris Michailidis

PhD Candidate at the Civic AI Lab, University of Amsterdam

Research

1. Michailidis, D., Röpke, W., Roijers, D., Ghebreab, S., Santos, F.P., "Scalable Multi-Objective Reinforcement Learning with Fairness Guarantees using Lorenz Dominance", arXiv pre-print. pdf.
2. van Oorschot, L., Michailidis, D., IJzerman, N., Jansen, S., Roijers, D., "Where (not) to Cross the Street", BNAIC/BeNeLearn (2024). pdf.
3. Michailidis, D., Khutsishvili, K., Konstantis, K., Tympas, A., Ibrahim, I.A., Ghebreab, S, "Enabling Inclusive Urban Transport Planning Through Civic Artificial Intelligence", Strengthening European Mobility Policy. Palgrave Macmillan, Cham (2024). pdf.
4. Tasnim, M., Michailidis, D., Ghebreab, S., Santos, F.P., Acar, E., "Mitigating School Segregation through Targeted School Relocation", In Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (Workshop on Citizen-Centric Multiagent Systems, Autonomous Agents and Multi-Agent Systems (2024). pdf code.
5. Michailidis, D., "Fair Transport Network Design using Multi-Agent Reinforcement Learning", Doctoral Consortium — 2023 International Conference on Autonomous Agents and Multiagent Systems. pdf.
6. Michailidis, D., Tasnim, M., Ghebreab, S., Santos, F.P., "Tackling school segregation with transportation network interventions: an agent-based modelling approach", Autonomous Agents Multi-Agent Systems 38, 22 (2024). [Most Visionary Paper Award, CMAS-AAMAS 2023] pdf.
7. Fiorista, R., Michailidis, D., Santos, F.P., "Equitable Public Transit Network Reduction", Transportation Research Board Annual Meeting (2023). [1st place, Network Modeling Student Problem Solving Competition, 2022 Transportation Research Board (USA National Academy of Sciences, Engineering, and Medicine)] research brief.
8. Michailidis, D., Röpke, W., Ghebreab, S., Roijers, D., Santos, F.P., "Fairness in Transport Network Design-A Multi-Objective Reinforcement Learning Approach", Adaptive and Learning Agents Workshop, 2023 International Conference on Autonomous Agents and Multiagent Systems (2023). pdf.
9. Michailidis, D., Ghebreab, S. and Santos, F.P., "Balancing Fairness and Efficiency in Transport Network Design through Reinforcement Learning", In Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (pp. 2532-2534). pdf, code.
10. Michailidis D., Stylianou N., Vlahavas I., "Real Time Location Based Sentiment Analysis on Twitter - The AirSent System", 10th Hellenic Conference on Artificial Intelligence, July 2018. pdf.

Blog Posts

• Designing Fair Public Transportation using Reinforcement Learning
• AIES 2021: Our Post-Event Review
• How can AI Help Tackle Mobility Poverty?

About me

I am a PhD candidate at the Civic AI Lab of the University of Amsterdam.

In my research, I use Machine Learning to design inclusive, accessible and sustainable cities.

My current focus is on using Reinforcement Learning to explore the trade-off between utility and equity/fairness when designing public transport networks.

In the near future, I would like to investigate how urban populations would adapt to such changes in a city's public transport networks.

My goal is to create a multi-agent framework that helps to envision alternative urban designs and their evolution in time.

Sounds interesting? Then please, get in touch!

Teaching & Supervision

Master's Students Supervision

• Riccardo Fiorista (Linkedin) - Equitable Public Transport Network Reduction: A Reinforcement Learning Approach - MSc Thesis, Spring 2022
• Paul Stepanov (Linkedin) - Fairness in Facility Location through Clustering - MSc Thesis, Spring 2022
• Lodewijk van Keizerswaard (Linkedin) - Rewarding rationality to improve reinforcement learning models on the metro network design problem - MSc AI Project, Summer 2022
• Laura Brafine (LinkedIn) - Measuring the Impact of Transportation Systems on Urban Segregation Through Random Walks - MSc Thesis Project, Spring 2023
• Leah van Oorschot (Linkedin) - Where (not) to Cross the Street: Automatically Detecting Crosswalks for Accessible Navigation - MSc Thesis, Spring 2024

Courses Taught

• Reinforcement Learning - Artificial Intelligence MSc (2023)
• Fundamentals of Data Science - Information Studies MSc - Data Science Track (2021, 2022)
• Fairness Accountability Confidentiality and Transparency in AI - Artificial Intelligence MSc (2022, 2023)

(Sub-)Reviewing

• Transportation Research Part C (2024)
• NetSciX (2024)
• AAAI (2024)
• ECAI (2023)
• Multi-Objective Decision Making Workshop (ECAI 2023, ECAI 2024)
• Public Transport Journal (2022)