Alexandros Tsigonias-Dimitriadis

Alexandros Tsigonias-Dimitriadis

PhD trainee, European Central Bank

Hi, I’m Alexandros!

I am currently a PhD trainee at the European Central Bank. Until very recently, I was a postdoctoral researcher at the Department of Industrial Engineering of the University of Chile hosted by Prof. José Correa. I was a member of the Information and Computation in Market Design (ICMD) team. I obtained my PhD from the School of Computation, Information and Technology of the Technical University of Munich. At TUM, I was advised by Prof. Andreas S. Schulz and was a member of the interdisciplinary research group Advanced Optimization in a Networked Economy (AdONE) and the Operations Research Group. Before that, I received my Diploma from the National Technical University of Athens, where I was advised by Prof. Dimitris Fotakis. During my PhD and postdoc, I had the opportunity to spend some time at Google Zurich and the Sapienza University of Rome.

My main research topic recently has been on the design of algorithms and mechanisms for fair and efficient resource allocation with applications in pricing, recommender systems, apportionment, and generally complex scenarios arising in (online) markets and platforms. I have a background and extensive training in both Computer Science and Operations Research. In my research, I have used a broad set of tools from algorithms, economics, operations, mechanism design, machine learning, and optimization. I enjoy developing algorithms with strong theoretical guarantees and demonstrating their applicability via experimentation on real-world data whenever possible. Apart from my research expertise, I have a strong interest in adjacent fields such as econometrics and causal inference. I love broadening my knowledge and exploring new topics and I aspire to work on projects, new technologies, and products with societal impact.

You can find a copy of my CV here (last update: September 2023).

Interests
  • Economics and Computation
  • Online Decision-Making in Resource Allocation
  • Algorithmic Mechanism Design
  • Pricing and Revenue Management
Education

  • PhD in Operations Research, 2022

    Technical University of Munich

  • Diploma in Electrical and Computer Engineering, 2018

    National Technical University of Athens

News

  • [September 2023] Our paper with Tomer, Stefano, Rebecca, and Matteo has been accepted to WINE 2023!

  • [July 2023] I just started a new position at the European Central Bank! I will be here for the forthcoming months working on improving the ECB’s communication with the general public using a variety of data-driven approaches.

  • [May 2023] I just started a research visit at Google Zurich hosted by Paul Dütting! I will be here for two months working on exciting algorithmic questions.

  • [May 2023] Our paper on the Prophet Secretary problem with Paul, Evangelia, Rojin, and Yifeng has been accepted to EC ‘23! We will post the full paper very soon on arXiv.

  • [August 2022] I completed my PhD at TU Munich. Next, I will be moving to the University of Chile, where I will do a one-year postdoc working with Prof. José Correa and other members of the ICMD team!

  • [July 2022] Check out our new preprint on “Prophet Inequalities via the Expected Competitive Ratio”.

  • [May 2022] Our paper on robust revenue maximization has been accepted to ACM TEAC!

  • [January 2022] In March, I will visit Prof. Stefano Leonardi and his group at the Sapienza Università di Roma, as part of the COST STSM program!

  • [October 2021] I will (virtually) present our work on The Secretary Problem with Independent Sampling at the INFORMS Annual Meeting (VTA21, 26/10 at 6AM PT).

Journal Articles

José Correa, Andrés Cristi, Laurent Feuilloley, Tim Oosterwijk, Alexandros Tsigonias-Dimitriadis (2023). The Secretary Problem with Independent Sampling. Minor Revision, Management Science.

Yiannis Giannakopoulos, Diogo Poças, Alexandros Tsigonias-Dimitriadis (2022). Robust Revenue Maximization Under Minimal Statistical Information. Forthcoming, ACM Transactions on Economics and Computation (ACM TEAC).

Cite DOI arXiv

Conference Publications

Tomer Ezra, Stefano Leonardi, Rebecca Reiffenhäuser, Matteo Russo, Alexandros Tsigonias-Dimitriadis (2023). Prophet Inequalities via the Expected Competitive Ratio. To appear in the 19th Conference on Web and Internet Economics (WINE ‘23).

arXiv slides

Paul Dütting, Evangelia Gergatsouli, Rojin Rezvan, Yifeng Teng, Alexandros Tsigonias-Dimitriadis (2023). Prophet Secretary Against the Online Optimal. In the proceedings of the 24th Conference on Economics and Computation (EC ‘23).

arXiv DOI poster

José Correa, Andrés Cristi, Laurent Feuilloley, Tim Oosterwijk, Alexandros Tsigonias-Dimitriadis (2021). The Secretary Problem with Independent Sampling. Extended abstract in the 2021 ACM-SIAM Symposium on Discrete Algorithms (SODA ‘21).

DOI arXiv slides poster

Yiannis Giannakopoulos, Diogo Poças, Alexandros Tsigonias-Dimitriadis (2020). Robust Revenue Maximization Under Minimal Statistical Information. Extended abstract in the 16th Conference on Web and Internet Economics (WINE ‘20).

DOI slides video

Working Papers

Javier Cembrano, José Correa, Ulrike Schmidt-Kraepelin, Alexandros Tsigonias-Dimitriadis, Victor Verdugo (2023). Political Apportionment: The Power of Divisor Methods and Randomization. In preparation for submission.

José Correa, Émile Naquin, Nicolás Stier-Moses, Alexandros Tsigonias-Dimitriadis, Victor Verdugo (2023). Online Policies for Content Recommendation with Fairness Constraints. Working paper.

Paul Dütting, Evangelia Gergatsouli, Rojin Rezvan, Yifeng Teng, Alexandros Tsigonias-Dimitriadis (2023). Prophet Secretary Against the Online Optimal. Submitted journal version.

Eleni Batziou, Giorgos Bouritsas, Alexandros Tsigonias-Dimitriadis (2023). Preference Elicitation in Combinatorial Domains: An Improved Approach using Reinforcement Learning. Working paper.

Teaching / Supervision

I have been a teaching assistant for the following courses:

I have co-supervised Master theses on the following topics:

  • “Iterative Combinatorial Auctions: Improved Running Time via Machine Learning”, 2021
  • “Experimental Evaluation of Robust Revenue-Maximizing Auctions”, 2021

Contact