LAMI: Location-aware machine intelligence (5 cp) 3621597

Course description


We focus on application of machine intelligence on location-aware applications. Selected research topics include (but not limited to) the following topics: search engines, recommendation systems, web mining, event detection, clustering, social networks, GPS tracectory analysis, road network extraction.

Course requirements

The course consists of 24 hours lectures and 12 hours of interactive tutoring.

Prerequisites

Graduate level course targeted for MSc and PhD students of computer science. Suitable especially for students who are going to start his/her MSc thesis in near-future, PhD students and researchers interested in the topic. The course is a direct continuation of the Location-aware mobile applications development course, focusing merely on the research topics in this area.


Lectures

Teacher: Radu Mariescu-Istodor (TB341)
Schedule: 24 h, starting from 16.1. (TB248 / F211)

Schedule and Lecture Notes

Presentations

Teacher: Radu Mariescu-Istodor (TB341)
Schedule: 12 h, starting from 21.1. (TB180 / F213)

Grading

Pass/Fail

Passing the course will require:
Participation to at least 10 lectures
Giving presentation or project work
Being opponent to other presentations

Opponent roles

      Content reviewer:

          Was the introduction / body / conclusion of the presentation convincing?
          Did the presentation title correspond to the content of the presentation?
          Was the content correct for the target audience and was it useful?
          Was the audience able to keep up with the content and was it clear?

      Design reviewer (slides and visuals):

          Were the slides clear and easy to follow?
          Did the slides contain too much or too little information?
          Were the colors and sizes of the font and visual (pictures, graphs) adequate?
          Were the main points of the presentation properly emphasized?

      Performance reviewer:

          Was the speech clear and well paced?
          Did the presenter have good eye contact, posture and gestures?
          Was the presenter able to keep the attention of the audience?
          How the presenter managed the equipment? 

      Q&A reviewer:

          How prepared was the presenter for the Q&A?
          Did the presenter handle the questions well?
          Did the presenter answer correctly to the question? 
          Did the presenter answer to the question that was asked? 

Literature and Project info

Please chose two papers or the project you will be working on by 25.1.
The same paper can be presented at most twice. Mark your name in either of the two columns here.

If instead of giving a presentation you chose to work on a project or implement a method from a paper, you must give a brief report on the last day of the course (25.2.)
Teacher also expects updates during the course and questions if something is unclear or too difficult.