CS554 Seminar in Computing Research
Syllabus | International University of Sarajevo - Last Update on Feb 02, 2026
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Computer Sciences and Engineering
Özge Büyükdağlı
Course Lecturer
Course Objectives
Seminar course develops students' research and presentation skills through periodic presentations with peer and faculty feedback. It also includes expert talks by guest speakers and faculty on advanced topics and research trends.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
TBD by the course instructor
Additional Literature
Selected books and peer-reviewed scientific papers provided by the instructorTeaching Methods
Lectures
Discussions
Peer feedback sessions
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Course Introduction and Seminar Framework | |
| 2 | Research Positioning and Topic Contextualisation | |
| 3 | Presentation Skills Workshop | |
| 4 | Student Presentations: Research topic presentations | |
| 5 | Student Presentations: Research topic presentations | |
| 6 | Student Presentations: Research topic presentations | |
| 7 | Student Presentations: Research topic presentations | |
| 8 | External Content: Emerging Research Trends in Computing | |
| 9 | Student Presentations: Work-in-Progress Presentation | |
| 10 | Student Presentations: Work-in-Progress Presentation | |
| 11 | Student Presentations: Work-in-Progress Presentation | |
| 12 | Student Presentations: Work-in-Progress Presentation | |
| 13 | Reflection and Research Refinement Session | |
| 14 | Mock Conference Session (with attendance of all faculty) | |
| 15 | External Content: Emerging Research Trends in Computing |
Course Schedule (All Sections)
Office Hours & Room
Assessment Methods and Criteria
Assessment Components
Work-in-Progress Presentation
AI: Not AllowedAlignment with Learning Outcomes : 1 3 4 5
Research Topic Presentation
AI: Not AllowedAlignment with Learning Outcomes : 1 3 5
Peer Feedback and Discussion Participation
AI: Not AllowedAlignment with Learning Outcomes : 2 3
IUS Grading System
| Grading Scale | IUS Grading System | IUS Coeff. | Letter (B&H) | Numerical (B&H) |
|---|---|---|---|---|
| 0 - 44 | F | 0 | F | 5 |
| 45 - 54 | E | 1 | ||
| 55 - 64 | C | 2 | E | 6 |
| 65 - 69 | C+ | 2.3 | D | 7 |
| 70 -74 | B- | 2.7 | ||
| 75 - 79 | B | 3 | C | 8 |
| 80 - 84 | B+ | 3.3 | ||
| 85 - 94 | A- | 3.7 | B | 9 |
| 95 - 100 | A | 4 | A | 10 |
Late Work Policy
Information about late submission policies will be shared during class and posted in this section. Please check back for official guidelines.
ECTS Credit Calculation
📚 Student Workload
This 6 ECTS credit course corresponds to 150 hours of total student workload, distributed as follows:
Lectures and presentations
42 hours ⏳ (14 week × 3 h)
Individual consultations and feedback sessions
10 hours ⏳ (10 week × 1 h)
Home study (reading and preparation)
98 hours ⏳ (14 week × 7 h)
150 Total Workload Hours
6 ECTS Credits
Course Policies
Academic Integrity
All work submitted must be your own. Plagiarism, cheating, or any form of academic dishonesty will result in disciplinary action according to university policies. When in doubt about citation practices, consult the instructor.
Attendance Policy
Students are expected to adhere to the attendance requirements as outlined in the International University of Sarajevo Study Rules and Regulations. Excessive absences, whether excused or unexcused, may impact academic performance and eligibility for assessment. Mandatory sessions (e.g., labs, workshops) require attendance unless formally exempted. For detailed policies on absences, documentation, and penalties, please refer to the official university regulations.
Technology & AI Policy
Laptops/tablets may be used for note-taking only during lectures. Phones should be silenced and put away during all class sessions. Audio/video recording requires prior permission from the instructor.
Artificial Intelligence (AI) Usage: The use of AI tools (e.g., ChatGPT, Copilot, Gemini) varies by assessment component. Please refer to the AI usage indicator next to each assessment item in the Assessment Methods and Criteria section above. Submitting AI-generated content as your own work, where AI is not explicitly allowed, constitutes an academic integrity violation.
Communication Policy
All course-related communication should occur through official university channels (institutional email or SIS). Emails should include [CS554] in the subject line.
Academic Quality Assurance Policy
Course Academic Quality Assurance is achieved through Semester Student Survey. At the end of each academic year, the institution of higher education is obliged to evaluate work of the academic staff, or the success of realization of the curricula.
Learning Tips
Be prepared to contribute thoughtfully during class discussions, labs, or collaborative work. Active participation deepens understanding and encourages critical thinking.
Complete assigned readings or prep materials before class. Take notes, highlight key ideas, and jot down questions. Aim to grasp core concepts and their applications—not just facts.
Use course frameworks or methodologies to analyze problems, case studies, or projects. Begin early to allow time for reflection and refinement. Seek feedback to improve your work.
Don’t hesitate to reach out when something is unclear. Use office hours, discussion boards, or peer networks to clarify concepts and stay on track.
Syllabus Last Updated on Feb 02, 2026 | International University of Sarajevo
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Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| CS554 | Seminar in Computing Research | 3 | 0 | 6 | ||||||
| Prerequisite | None | It is a prerequisite to | - | |||||||
| Lecturer | Özge Büyükdağlı | Office Hours / Room / Phone | Monday: 15:00-17:00 Tuesday: 12:00-17:00 Wednesday: 15:00-17:00 |
|||||||
| obuyukdagli@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | Seminar course develops students' research and presentation skills through periodic presentations with peer and faculty feedback. It also includes expert talks by guest speakers and faculty on advanced topics and research trends. |
|||||||||
| Textbook | TBD by the course instructor | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
||||||||||
| Teaching Methods | Lectures, discussions, Peer feedback sessions | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Course Introduction and Seminar Framework | |||||||||
| Week 2 | Research Positioning and Topic Contextualisation | |||||||||
| Week 3 | Presentation Skills Workshop | |||||||||
| Week 4 | Student Presentations: Research topic presentations | |||||||||
| Week 5 | Student Presentations: Research topic presentations | |||||||||
| Week 6 | Student Presentations: Research topic presentations | |||||||||
| Week 7 | Student Presentations: Research topic presentations | |||||||||
| Week 8 | External Content: Emerging Research Trends in Computing | |||||||||
| Week 9 | Student Presentations: Work-in-Progress Presentation | |||||||||
| Week 10 | Student Presentations: Work-in-Progress Presentation | |||||||||
| Week 11 | Student Presentations: Work-in-Progress Presentation | |||||||||
| Week 12 | Student Presentations: Work-in-Progress Presentation | |||||||||
| Week 13 | Reflection and Research Refinement Session | |||||||||
| Week 14 | Mock Conference Session (with attendance of all faculty) | |||||||||
| Week 15 | External Content: Emerging Research Trends in Computing | |||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Semester Evaluation Components | |||||
| Work-in-Progress Presentation | 1 | 30 | 1, 3, 4, 5 | Not Allowed | |
| Research Topic Presentation | 1 | 30 | 1, 3, 5 | Not Allowed | |
| Peer Feedback and Discussion Participation | 1 | 40 | 2, 3 | Not Allowed | |
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lectures and presentations | 3 | 14 | 42 | Individual consultations and feedback sessions | 1 | 10 | 10 | |||
| Home study (reading and preparation) | 7 | 14 | 98 | |||||||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 12/02/2026 | |||||||||