Kaisa_2012_3_photo by Veikko Somerpuro


Interested in constraints & optimization, data compression, or sequence analysis?

There is still room in the seminar, so if you find some of the topics below of interest, please contact one of the organizers. You can also propose your own topic.

Constraints & optimization:
Local search for bit-precise reasoning, Computational mathematics: determining Schur Number Five using SAT solvers, Verification of deep neural networks (reserved), Constraint acquisition, The stable matching problem with couples, Software model synthesis / learning finite-state automata, Knowledge compilation: sentential decision diagrams, Model counting, Constraint integer programming, The exponential time hypothesis and lower bounds for polynomial-time problems

Data compression:
Compression by Substring Enumeration & Synchronization Codes, String Attractors, Succinct Data Structures Library, Succinct Range Minimum Queries (reserved)

Sequence analysis:
Min-Hashing, Minimizers, Bloom filters & de Bruijn graphs, Compression & colored/weighted de Bruijn graphs, Alignments on Graphs.

See Materials section for references related to these topics.



Tästä osiosta löydät kurssin opetusaikataulun. Tarkista mahdolliset muut aikataulut kuvauksesta.

Ti 16.1.2018
12:15 - 14:00
Ti 23.1.2018
12:15 - 14:00
Ti 30.1.2018
12:15 - 14:00
Ti 6.2.2018
12:15 - 14:00
Ti 13.2.2018
12:15 - 14:00
Ti 20.2.2018
12:15 - 14:00
Ti 27.2.2018
12:15 - 14:00
Ti 13.3.2018
12:15 - 14:00
Ti 20.3.2018
12:15 - 14:00
Ti 27.3.2018
12:15 - 14:00
Ti 10.4.2018
12:15 - 14:00
Ti 17.4.2018
12:15 - 14:00
Ti 24.4.2018
12:15 - 14:00
Ti 8.5.2018
12:15 - 14:00
Ti 15.5.2018
12:15 - 14:00
Ti 22.5.2018
12:15 - 14:00
Ti 29.5.2018
12:15 - 14:00



16.1 12-14 CK108: Introduction to topics
23.1 12-14 CK108: Continued discussion & scheduling
30.1 12-14 No meeting
6.2 12-14 CK108: 5 minute presentations on each topic
13.2, 20.2, 27.2, 6.3 No meetings

- Draft of your presentation
- Draft of your seminar paper

13.3 12-14 CK108: Verification of deep neural networks (Pavel, opponent Erkki); Genome rearrangements (Tuukka)
20.3 12-14 CK108: Succinct Range Minimum Queries (Simo, opponent Jouko); AMS-Lex (Kari, opponent Pavel)
27.3 12-14 CK108: Learned index structure (QJ, opponent Simo); Software model synthesis / learning finite-state automata (Erkki, opponent Kari)
3.4 Easter break
10.4 12-13 CK108: Min-hashing (Jouko, opponent QJ)
17.4 No meeting
24.4 No meeting
27.4 Deadline for seminar paper
15.5 Short presentation or a poster on the hands-on project at Computer Science Colloquium

Kurssin suorittaminen

Course requirements (preliminary):
- Preliminary topic presentation (~5 min) 6.2.
- Give a seminar presentation (~40 min) on your topic. 13.-27.3
- Write a seminar report (~15 pages) on your topic to accompany the presentation
- Act as an opponent to one other student
- Active participation in the seminar meetings
- Individual hands-on project related to your topic (for 5 ECTS only)
- Project presentations 15.5.

The details of the individual project assignment will be agreed on together with the teacher in charge of the chosen topic. (For students guaranteed to graduate with the old MSc study requirements, it is also possible to pass the course as a 3-ETCS seminar without the project assignment. Please consult the teachers if you want to take the 3-ECTS option.)


Master's Programme in Computer Science is responsible for the course

  • Discrete Algorithms course package CSM12100
  • Module in Discrete Algorithms CSM22100
  • Algorithmic bioinformatics LSI310

The course is available to students from other degree programmes, especially from the Life Science informatics / Algorithmic Bioinformatics study track

The topics of the course are related to recently lectured courses in discrete algorithms. One should have taken at least one earlier discrete algorithms course to attend the research seminar.

To continue with a Master's thesis in computer science related to the topic of the seminar.

Academic writing courses

An ability to give scientific presentations. An ability to peer-review and give feedback on written work and on presentations. Improved scientific writing skills on discrete algorithms topics. In-depth theoretical understanding of an advanced topic in discrete algorithms and/or experience in implementing and experimentally evaluating an advanced discrete algorithm.

After the Data Compression Techniques course or during the Biological Sequence Analysis course. There are also topics not related directly to these courses.

The course is offered in Spring 2018

The topics of the course are related to recently lectured courses in discrete algorithms.

Grading is 1..5. Presentation and written work of the seminar part are evaluated with a common grade. The 2-cr project part can be evaluated also as pass/fail.

The final grade is a weighted average of the parts.

The course is separated into a 3-cr seminar part and a 2-cr implementation project part, which can be taken independently. The seminar part includes a presentation and written work. The project is an implementation of an algorithm and its evaluation, reported as a (poster) presentation and short report.