Mirko Giacchini

Postdoc at Columbia University

GitHub
mg5011 [AT] columbia [DOT] edu

Mirko Giacchini

I am a postdoctoral researcher at Columbia University, where I am an Italian Academy Fellow and I am advised by Eric Balkanski.

I obtained my Ph.D. in Computer Science from Sapienza University of Rome, where I was advised by Flavio Chierichetti and Alessandro Panconesi. My research focuses on online algorithms and theoretical foundations of machine learning. Specifically, I have worked on stochastic online bipartite matching and learning algorithms for discrete choice models, including random utility models and multinomial-logit/Plackett-Luce models.

I have served (or am serving) as PC member for KDD (2024), TheWebConf (2024, 2026), and AAAI (2026), and as reviewer for SODA (2025, 2026, 2027), ITCS (2025), ESA (2025), NeurIPS (2026), ICML (2026 Gold Reviewer), KDD (2023), TheWebConf (2025), SDM (2024), and TIST.

Teaching

Advanced Algorithms, Sapienza University of Rome, Spring 2026
Co-Lecturer with Flavio Chierichetti

Selected Publications

Beyond the Full Slate: Evaluating MNL Algorithms on All Slates

Flavio Chierichetti, Mirko Giacchini, Ravi Kumar, Silvio Lattanzi, Alessandro Panconesi, Erasmo Tani, Andrew Tomkins

NeurIPS 2026 (to appear)

Learning Multinomial Logits in O(n log n) time

Flavio Chierichetti, Mirko Giacchini, Ravi Kumar, Silvio Lattanzi, Alessandro Panconesi, Erasmo Tani, Andrew Tomkins

ICALP 2026 · Paper

A New Impossibility Result for Online Bipartite Matching Problems

Flavio Chierichetti, Mirko Giacchini, Alessandro Panconesi, Andrea Vattani

ICALP 2025 · Paper

Tight Bounds for Learning RUMs from Small Slates

Flavio Chierichetti, Mirko Giacchini, Ravi Kumar, Alessandro Panconesi, Andrew Tomkins

NeurIPS 2024 · Paper

See all publications