Andreas Maggiori

I am a Postdoctoral Researcher at the Data Science Institute (DSI) at Columbia University, where I am working with Eric Balkanski and Will Ma. I am interested in the intersection of Online Decision Making, Machine Learning and Theoretical Computer Science with a particular focus on learning augmented algorithms.

Prior to that, I earned my PhD at EPFL, advised by Rudiger Urbanke and Ola Svensson. During my PhD, I visited the Simons Institute, UC Berkeley for 2 months for the Data-Driven Decision Processes program. I also interned twice at Google Zurich, hosted by Nikos Parotsidis and Ehsan Kazemi accordingly.

Before joining EPFL, I did my undergrad in Greece, in the Electrical and Computer Engineering department of National Technical University of Athens.

Email  /  Google Scholar  /  CV

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I am on the job market!
News
Publications
(Authors are in alphabetical order)

Fair Secretaries with Unfair Predictions
with Eric Balkanski and Will Ma
to appear at NeurIPS 2024

Dynamic Correlation Clustering in Sublinear Update Time
with Vincent Cohen-Addad, Silvio Lattanzi and Nikos Parotsidis
ICML 2024, Spotlight

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
arxiv/ talk/ code

Learning Augmented Energy Minimization via Speed Scaling
with Etienne Bamas, Lars Rohwedder and Ola Svensson
NeurIPS 2020, Spotlight
arxiv/ slides/ code

Online Matching with General Arrivals
with Buddhima Gamlath, Michael Kapralov, Ola Svensson and David Wajc
FOCS 2019
arxiv/ David's talk

Teaching/Study groups/Workshops

  • 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)

  • I am/was teaching assistant for the following courses:
    • NTUA: Algorithms and Complexity, Discrete Mathematics
    • EPFL: Theory of Computation, Machine Learning, Learning Theory, Algorithms, Advanced Probability and Applications, Foundations of data science

More

  • I am from Athens, Greece and enjoy gelato, rod fishing, kayaking, snowboarding and basketball. When I am in Athens, your chances of finding me at Amorgiano listening to Thanassis are pretty high.












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