Andreas Maggiori

Dr. Andreas Maggiori is a Postdoctoral Research Scientist at Columbia University's Data Science Institute, collaborating with Professors Will Ma and Eric Balkanski. His research focuses on the intersection of Online Decision Making, Machine Learning, and Theoretical Computer Science, emphasizing learning-augmented algorithms to enhance decision-making processes.

He earned a PhD from École Polytechnique Fédérale de Lausanne (EPFL), advised by Rudiger Urbanke and Ola Svensson. During his PhD, he visited the Simons Institute at UC Berkeley for the Data-Driven Decision Processes program. He holds a bachelor’s degree in Electrical and Computer Engineering from the National Technical University of Athens.

His work spans algorithmic fairness, dynamic clustering, and optimization, with applications in online matching and energy-efficient scheduling. He interned at Google Zurich, collaborating with Nikos Parotsidis and Ehsan Kazemi on algorithmic research.

Key research directions include:

• Learning-augmented algorithms for decision-making
• Sublinear-time dynamic algorithms
• Algorithmic fairness in clustering and matching
• Energy-minimization via speed scaling

No scientific awards are explicitly mentioned in the provided text.

Advising: No formal advisees listed. Grants: No specific grants detailed. His research is supported through institutional and collaborative affiliations.

Labs/Teams: Active in the Data Science Institute at Columbia, with interdisciplinary collaborations across academia and industry (e.g., Google, Simons Institute).