Machine Learning Paper Review

COURSE SYLLABUS, third-cycle courses

ECTS/HP: 0.5 ECTS per paper (can be taken up to four times)

Course code:
SRT0006

Educational level: third-cycle course

Entry requirements:

• Basic knowledge in Machine Learning
• Admission to third-cycle studies involving Machine Learning or Machine Learning applications
• Fundamental knowledge in Scientific Reading.

Course content:
The course involves a critical review of a scientific publication (typically a conference or journal submission to be evaluated in a peer-review process). The paper is selected together with a member of the machine learning group and guided and supervised by that group member.

Learning outcomes:

• demonstrate broad knowledge and systematic understanding of the research domain as well as advanced and up-to-date specialised knowledge in a limited area of the research domain
• demonstrate the capacity for scholarly analysis and synthesis as well as to review and assess new and complex phenomena, issues and situations autonomously and critically

Course methods:
The paper will within the Machine Learning Subject. Then, in a given time frame, the student has to read the paper and write a critical review. This review is then discussed and improved together with a senior member of the Machine Learning Group.

Every iteration this course is taken, there will be an increasing complexity of the paper to read. Furthermore, it is expected to perform more independent work in the later iterations.

Examination form:
Written report (review).

Grading scale: Pass/Fail

Course literature:
Recent publication in machine learning and applications (to be decided together with and approved by a senior member of the Machine Learning Group).

Education cycle:
Any stage of PhD studies

Course is given periodically: Continuously

Send application to: any senior member of the machine learning group
Doctoral student enter name, civic registration number, e-mail, Division and Department in the application

Deadline for application:
continuous participation possible

Course open for application by doctoral students admitted to other universities than LTU: Yes □

Limited number of students: No □

Tuition:
If the course is allocated resources via internal resource allocation system, the course is free of charge for doctoral students admitted at LTU, for doctoral students admitted to other universities, course fees may be required. For other courses the Department decides on course fees.

Contact person:
Rajkumar Saini (Rajkumar.Saini@ltu.se)

Examiner:
Marcus Liwicki

Course syllabus decided by:
Johan Carlson, Forskarutbildningsledare SRT, LTU-2636-2026

Date of decision: 2026-03-24