Mats Sjöberg

Postdoctoral Researcher, D.Sc. (Tech.)
CBIR research group
Department of Computer Science, Aalto University Mats Sjöberg

Contact information

Room B326, 3rd floor of the Computer Science building,
Konemiehentie 2, Espoo, Finland
Postal Address:
Aalto University,
Department of Computer Science,
P.O.Box 15400,
FI-00076 Aalto,
Email: (GPG: 99E8E6D3) (permanent address, redirects to current work address)

Research interests

My research has focused on applying machine learning to recognise patterns in huge datasets, in particular visual data and personal log data.

Current topics

Earlier topics



Digital Me

The idea of the Digital Me (DiMe) server is to collect your personal data from various loggers into a central place that you control. The focus is on tracking knowledge work and developing applications that can help the knowledge worker manage their working life better.

[Source code] - the source code is freely licensed (MIT).
[QE2017 slides PDF] - my slides from the Quantified Employee 2017 event explaining DiMe and time tracking.
[MyData 2016 slides PDF] - my slides from the MyData 2016 conference explaining Re:Know and Digital Me.
[Pre-print PDF] - Digital Me position paper presented at the Symbiotic 2016 workshop.

Pair annotation for multimedia

A web-based tool for performing pair-wise annotation of multimedia (videos or images), used in several MediaEval tasks. [Source code on GitHub].

Selected publications

Full list of publications in the TUHAT database.

Google Scholar profile.

My ORCID is 0000-0002-3157-7668.

Doctoral thesis

From pixels to semantics: visual concept detection and its applications.
Department of Information and Computer Science, Aalto University School of Science.
[Available online]

Master's thesis

Content-based retrieval of hierarchical objects with PicSOM
Laboratory of Computer and Information Science, Helsinki University of Technology.
[Abstract PDF] [Entire document PDF].