Topic outline

  • General

    Special project course can be taken anytime during the academic year by contacting professors or teachers of Communications Engineering major. 

    The optimal time to do special project is 1st year spring term of your masters studies. 

    This MyCo space is used in Spring 2023 course.


    Instructions

    In order to do Special project in Communications engineering course in Spring 2023:

    • Register to this course in SISU. This allows you to give course feedback later
    • The project can be done alone or in 2-5 students group. In group work case you may start finding other group members
    • There will be Special Project startup happening is in 12.1.2023 at 10.15 in AS4 were we discuss some of the course practicalities and present the department research groups.
    • After startup session you have two weeks time to select a suitable special project topic.
    • The work will be supervised in a research group agree with the prof/teacher: Problem setting, timetable, number of credits (2 - 10 cr - 5 cr is preferred) and output of the project work (report, program, simulations, etc).
    • The course has a final seminar on 11.05.2023 were you present your work result. 
    • You submit the project report into MyCourses. 

    Course schedule
    • Introductory lecture 12.01.2023 at 10.15  in AS4 (slides)
    • Final presentation 11.05.2023 at 9.15 in TU4 (TUAS)

    List of the profs & teachers:
    • Stephan Sigg,
    • Jukka Manner,
    • Patric Östergård,
    • Risto Wichman,
    • Olav Tirkkonen,
    • Jyri Hämäläinen,
    • Antti Oulasvirta,
    • Yu Xiao,
    • Visa Koivunen,
    • Sergiy Vorobyov,
    • Riku Jäntti,
    • Kalle Ruttik,
    • Pasi Lassila,
    • Samuli Aalto,
    • Yusein Ali
    Topics
    Ask for topics from professors and teachers
    from prof. Yu Xiao research group you can get following topics Topics_Set1
    Additionally she has two more topics (contact: yu.xiao@aalto.fi)
    • Topic 1:  A literature survey on federated learning for sensor-based human activity recognition (1 student, 5 credits)
    • Topic 2:  A literature survey on continual learning in sensor-based human activity recognition (1 student, 5 credit)
    Students are expected to have basic knowledge about machine learning. They are expected to write reports that summarize the existing works/methods, remained challenges, and potential future works.

    Kalle Ruttik has a few topics about backscattering communication (contact: kalle.ruttik@aalto.fi)
    • Backscattering signal measurement campaign
    • Modifying existing backscattering code for operating in LTE 700 MHz frequencies