Publications
(Authors are in alphabetical order)
Cost-Free Fairness in Online Correlation Clustering
with
Eric Balkanski, and
Iason Chatzitheodorou
ALT 2025
Data-Driven Solution Portfolios
with
Marina Drygala,
Silvio Lattanzi,
Miltiadis Stouras,
Ola Svensson, and
Sergei Vassilvitskii
ITCS 2025
Fair Secretaries with Unfair Predictions
with
Eric Balkanski and
Will Ma
NeurIPS 2024
Dynamic Correlation Clustering in Sublinear Update Time
with
Vincent Cohen-Addad,
Silvio Lattanzi and
Nikos Parotsidis
ICML 2024, Spotlight (3% acceptance rate)
Online and Consistent Correlation Clustering
with
Vincent Cohen-Addad,
Silvio Lattanzi and
Nikos Parotsidis
ICML 2022
slides/
talk
An Improved Analysis of Greedy for Online Steiner Forest
with
Etienne Bamas and
Marina Drygala
SODA 2022
arxiv/
slides
The Primal-Dual method for Learning Augmented Algorithms
with
Etienne Bamas and
Ola Svensson
NeurIPS 2020, Oral talk (1% acceptance rate)
arxiv/
talk/
code
Learning Augmented Energy Minimization via Speed Scaling
with
Etienne Bamas,
Lars Rohwedder and
Ola Svensson
NeurIPS 2020, Spotlight (3% acceptance rate)
arxiv/
slides/
code
Online Matching with General Arrivals
with
Buddhima Gamlath,
Michael Kapralov,
Ola Svensson and
David Wajc
FOCS 2019
arxiv/
David's talk
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Invited Talks
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Fair Secretaries with Unfair Predictions
- 11/2024 University of Massachusetts, Amherst, USA
- 11/2024 Drexel University, Philadelphia, USA
- 10/2024 Yale SOM Operations Seminar, Yale University, USA
- 09/2024 Rutgers/DIMACS Theory of Computing Seminar, Rutgers University, USA
- 07/2024 INFORMS Revenue Management and Pricing Section Conference, UCLA, USA
- 07/2024 Workshop on Algorithms with Predictions, Columbia University, USA
- 06/2024 INFORMS Workshop on Market Design, Yale University, USA
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Data-Driven Solution Portfolios
- 10/2024 NYU Theory Seminar, New York University, USA
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Online and Consistent Correlation Clustering
- 06/2023 INFORMS Applied Probability Society Conference, Nancy, France
- 09/2022 University of Massachusetts, Amherst, USA
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The Primal-Dual method for Learning Augmented Algorithms
- 09/2022 Simons Institute for the Theory of Computing, UC Berkeley, USA
- 09/2022 University of Massachusetts, Amherst, USA
- 06/2021 Google Zurich, Switzerland
Teaching/Study groups/Workshops
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I organized a study-group on how continuous optimization methods can be used to tackle combinatorial problems. The website of the study-group with notes and recorded lectures can be found here. (If you do not have an ETH account and you want to have access to the lecture videos, please drop me an email)
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I am/was teaching assistant for the following courses:
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NTUA: Algorithms and Complexity, Discrete Mathematics
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EPFL: Theory of Computation, Machine Learning, Learning Theory, Algorithms, Advanced Probability and Applications, Foundations of data science
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