- You need a topic and supervisor to pass this course
- Any data mining related topic which is complex enough and has a university supervisor will do
- Normally you should choose your BSc or MSc thesis topic
- Young PhD student can take something, which will bring it closer to the first article.
Academic supervisors
If you know what you want just contact these persons and try to get a seminar topic that interests them.
You can also look for their seminars for topics given out in previous years.
- Bioinformatics
- Hedi Peterson
- Kaur Alasoo
- Leopold Parts
- Dima Fishman
- Elena Sügis
- Jaak Vilo
- Robotics & Intelligent materials
- Alvo Aabloo
- Intelligent transportation, spacial-data, location tracking
- Artjom Lind
- Amnir Hadachi
- Neurosience
- Tambet Matiisen
- Ardi Tampuu
- Raul Vicente
- Natural language processing
- Sven Laur
- Kairit Sirts
- Mark Fishel
- Eduard Barbu
- Information Systems & Software
- Marlon Dumas
- Dietmar Pfahl
- Mario Ezequiel Scott
- Analysis of big data
- Ahmed Awad
- Radwa Elshawi
- Data-streams
- Riccardo Tommasini
- Medical data mining and personal medicine
- Raivo Kolde
- Sven Laur
- Sulev Resiberg
- Jaak Vilo
- Theoretical aspects in machine learning
- Meelis Kull
- Leopold Parts
Industry partners
These companies give out interesting research tasks.
If you can find co-supervisor
from the university then you are good to go!
- STACC
- Topic: Analysis of medical data. Fact extraction.
- Contact person: Sven Laur
- Topic: Media monitoring and general text processing.
- Contact person: Karl-Oskar Masing
- Haigekassa analüütika osakond
- Topics: Anomalities in health insurance bills
- Contact person: Mark Gimbutas
- Eesti Energia
- Topics: Energy consumption and generation
- Contact person: Kristjan Eljand
- AS DATEL
- Contact person: Anne Jääger (UT)
- Topics: Radar imaging and time-series analysis
- TEXTA
- Contact person: Raul Sirel
- Topics: Natural language processing and fact extraction