Domenico Mandaglio

Assistant Professor (RTDa), University of Calabria (Italy)

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Office:

Building 44Z, 1st floor

via P. Bucci

Rende (CS), 87036, Italy

I am an Assistant Professor (RTDa) within the Machine Learning, NLP and Network Science Team @Artificial Intelligence and Data Science Lab at the Department of Computer Engineering, Modeling, Electronics, and Systems Engineering (DIMES), University of Calabria, in Rende (Italy). Previously, I was a postdoctoral researcher at the DIMES Department. I received my PhD (2021) in Information and Communication Technologies from University of Calabria. There I completed my M.Sc. (2017) and B.Sc. (2014) in Computer Science and Engineering.

My research interests lie primarily in the broad areas of artificial intelligence and (algorithmic) data science, with the main goal of tackling (novel) problems and designing effective yet efficient algorithms that are useful to gain knowledge from data. Due to the fact that much of today’s data can be represented as graphs, my emphasis has primarily been on formalizing data-driven challenges as graph problems. More specifically, my recent research interests include graph mining and learning, correlation clustering and explainable AI.

Selected publications

  1. MACH
    Neural Discovery of Balance-aware Polarized Communities
    Francesco Gullo, Domenico Mandaglio, and Andrea Tagarelli
    Machine Learning (MACH), 2024
    PDF Code
  2. WWW
    Link Prediction on Multilayer Networks through Learning of Within-Layer and Across-Layer Node-Pair Structural Features and Node Embedding Similarity
    Lorenzo Zangari, Domenico Mandaglio, and Andrea Tagarelli
    In Proceedings of the ACM Web Conference (WWW), 2024
    PDF Code Poster
  3. DAMI
    A Combinatorial Multi-Armed Bandit Approach to Correlation Clustering
    Francesco Gullo, Domenico Mandaglio, and Andrea Tagarelli
    Data Mining and Knowledge Discovery (DAMI), 2023
    PDF Code Slides
  4. ECML-PKDD
    Correlation Clustering with Global Weight Bounds
    Domenico Mandaglio, Andrea Tagarelli, and Francesco Gullo
    In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2021
    PDF Code Poster Slides
  5. KDD
    In and Out: Optimizing Overall Interaction in Probabilistic Graphs under Clustering Constraints
    Domenico Mandaglio, Andrea Tagarelli, and Francesco Gullo
    In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2020
    PDF Code Slides