RESERVE LIST - PhD Training week - MODULE 6

15mar9:00 am5:00 pmRESERVE LIST - PhD Training week - MODULE 6Introduction to Machine Learning and Artificial Intelligence: Methods and Applications9:00 am - 5:00 pm(GMT+01:00) Via del Pescarotto, 8, 35131 Padova PD

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Traditional Artificial Intelligence techniques are based on predefined rules and formal logic, that are effective for solving well-defined and structured problems. In contrast, Machine Learning refers to the automated process of extracting patterns from large collections of heterogeneous data such as the data managed by search engines, filtered by antispam filters, or collected by credit card transaction managers. The aforementioned applications of Machine Learning share the impossibility for a programmer to describe in an exhaustive and precise way the methods of detecting patterns.  The only way to detect those patterns is to instruct a machine which has to intelligently learn by means of known examples and dynamically adapt to unknown ones.

Speakers

Fabio Vandin is a Professor in the Department of Information Engineering at the University of Padova, Italy. He received his PhD in Information Engineering from the University of Padova (Italy), and he has held research positions with various titles at Brown University (USA), at the University of Southern Denmark, and at the University of California, Berkeley (USA). His research interests are in algorithms for machine learning and data mining, and their application for the analysis of large datasets from various domains, including biology and social networks. He has authored over 90 papers in international peer-reviewed venues, and he has used his methods for analyses published in Nature, Nature Genetics, Cell, NEJM. He has been a PI of projects funded by MUR of Italy and NSF. He is on the editorial board of J. of Graph Algorithms and Applications, and ACM Transactions on Intelligent Systems and Technology. His work has been recognized with Best Paper Awards (RECOMB 2013, ECML-PKDD 2022) and the Test of Time award at RECOMB 2023.

Leonardo Pellegrina is an Assistant Professor (RTDa) at the Department of Information Engineering of the University of Padova, and a Visiting Research Fellow at Brown University. His research activities focus on efficient and statistically sound Data Mining algorithms for pattern discovery from large data, with applications to computational biology. He received an Honorable mention for the 2021 SIGKDD Dissertation Award, and was selected as one of the Best Program Committee members at ACM The Web Conference 2022 and 2023. He has presented his research work in several international conferences and workshops (e.g., KDD, RECOMB, ISMB, ECCB), and presented tutorials at ACM KDD’19 and SDM’21.

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Time

March 15, 2024 9:00 am - 5:00 pm(GMT+02:00)

Location

Aula 3E Fiore di Botta building - University of Padua

Via del Pescarotto, 8, 35131 Padova PD

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Speakers for this event

  • Fabio Vandin

    Fabio Vandin

    Prof.

    University of Padua

    Fabio Vandin is a Professor in the Department of
    Information Engineering at the University of Padova, Italy. He received his PhD
    in Information Engineering from the University of Padova (Italy), and he has
    held research positions with various titles at Brown University (USA), at the
    University of Southern Denmark, and at the University of California, Berkeley
    (USA). His research interests are in algorithms for machine learning and
    data mining, and their application for the analysis of large datasets from
    various domains, including biology and social networks. He has authored over 90
    papers in international peer-reviewed venues, and he has used his methods for
    analyses published in Nature, Nature Genetics, Cell, NEJM. He has been a PI of
    projects funded by MUR of Italy and NSF. He is on the editorial board of J. of
    Graph Algorithms and Applications, and ACM Transactions on Intelligent Systems
    and Technology. His work has been recognized with Best Paper Awards (RECOMB
    2013, ECML-PKDD 2022) and the Test of Time award at RECOMB 2023.

    Prof.

  • Leonardo Pellegrina

    Leonardo Pellegrina

    Dr.

    University of Padua

    Leonardo Pellegrina is an Assistant Professor
    (RTDa) at the Department of Information Engineering of the University of
    Padova, and a Visiting Research Fellow at Brown University. His research
    activities focus on efficient and statistically sound Data Mining algorithms
    for pattern discovery from large data, with applications to computational
    biology. He received an Honorable mention for the 2021 SIGKDD Dissertation
    Award, and was selected as one of the Best Program Committee members at ACM The
    Web Conference 2022 and 2023. He has presented his research work in several
    international conferences and workshops (e.g., KDD, RECOMB, ISMB, ECCB), and
    presented tutorials at ACM KDD’19 and SDM’21.

    Dr.

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