Disputation: Andrea Raffo

Doctoral candidate Andrea Raffo at the Department of Mathematics, Faculty of Mathematics and Natural Sciences, is defending the thesis Mathematical methods for geometry reconstruction and shape analysis for the degree of Philosophiae Doctor.

Picture of the candidate.

Doctoral candidate Andrea Raffo

The PhD defence will be fully digital streamed directly using Zoom. The host of the session will moderate the technicalities while the chair of the defence will moderate the disputation.

Ex auditorio questions: the chair of the defence will invite the audience to ask questions ex auditorio at the end of the defence. If you would like to ask a question, click 'Raise hand' and wait to be unmuted.

  • Join the disputation

    The webinar opens for participation just before the disputation starts, participants who join early will be put in a waiting room.
    • Download Zoom

    • Submit the request to get access to the thesis (available from 4th March 12:00 until 18th March 12:00)

Trial lecture

17th of March, time: 13.15 am, Zoom

"Approximating measured data points by tensor product surfaces” 
  • Join the trial lecture
    The webinar opens for participation just before the trial lecture starts, participants who join early will be put in a waiting room.

Main research findings

The last decades have witnessed an exponential growth in the amounts of data that are collected, stored and shared worldwide daily. Yet, much of it remains, totally or partially, unexploited.

In many scientific disciplines, information consists of a set of sample points describing some phenomena. A natural question deals with geometry reconstruction, i.e., the recovery of the shape of such data points through some representations. Approximation theory has traditionally focused on the case of data points sampled from smooth curves and surfaces; however, in most real-world scenarios, data is affected by noise and potentially other imperfections which can significantly reduce the capability to generalize on unseen data. When dealing with the need of analysing and comparing data automatically, shape descriptions are often preferred to shape representations: despite the latter being more complete than the former, they do not necessarily disclose any high-level information useful to discriminate between shapes.

This thesis addresses a range of problems in geometry reconstruction and shape analysis, motivated in the light of real-world applications, including the need to identify geometric relationships in mechanical engineering, the approximation of noisy point clouds in life and earth sciences and the recognition of proteins from an ensemble of geometries in structural biology.

Adjudication committee

Professor Tamas Varady, Budapest University of Technology and Economics
Associate Professor Costanza Conti, Università degli Studi di Firenze
Associate Professor Arne Bernhard SletsjøeUniversitetet i Oslo

Supervisors

Professor Michael Stephen Floater, University of Oslo
Chief Scientist Tor DokkenSINTEF
Senior Research Scientists Georg Muntingh, SINTEF
Senior Data Scientist Heidi Elisabeth Iuell Dahl, Posten Norge AS
Senior Research Scientists Oliver Joseph David Barrowclough, SINTEF

Chair of defence

Head of Department Geir Dahl, University of Oslo

Host of the session

Associate Professor Arne Bernhard Sletsjøe, Universitetet i Oslo

Published Mar. 4, 2022 7:30 PM - Last modified Oct. 19, 2022 11:12 AM