News

HIBIT 2021 (14th The International Symposium on Health Informatics and Bioinformatics) will be organized as a virtual event by Bilkent University. Dr. Ercument Cicek will chair the event.

The International Symposium on Health Informatics and Bioinformatics  is in its fourteenth year. It aims to bring together academics, researchers, and practitioners from medical, biological, and information technology sectors to create a synergy. It is one of the few conferences emphasizing such a synergy. It provides a forum for discussion, exploration, and development of theoretical and practical aspects of health informatics and bioinformatics. Also, it gives researchers a chance to follow current research in their field by constructing networks.

More information can be obtained from: HIBIT 2021.

Computer Engineering Department Graduation Ceremony was held on June 21, 2021, at 11:00am in Bilkent Odeon. Our 2021 graduates received their diplomas. Congratulations to all of them. The ceremony can be watched at the following youtube address:

Computer Engineering Graduation Ceremony 2021

Bilkent AI Summer School is organized by Computer Engineering Department for high school students. The students get opportunity to learn about computer engineering, basic programming, and contemporary artificial intelligence  and machine learning topics. Besides lectures, there are labs that enable the students to apply what they learn. At the end of the education, students are able to do some basic programming and AI projects on their own.

This year the summer school took place on July 27-29, 2021. Dr. Hamdi Dibeklioglu from Computer Engineering Department gave the lectures. A team of teaching assistants coordinated the labs and helped the students in their hands-on assignments.

To get more information, please visit the website of the summer school.

Asst. Prof. Dr. Ayşegül Dündar’s project on “Semantically conditioned multi-modal image inpainting” received TÜBİTAK 3501 support.

Image inpainting, the task of filling missing pixels in the most realistic manner, is a difficult task requiring a high level of understanding of the scene. A successful image inpainting algorithm provides an important image editing tool that can be used by daily users as well as architects and designers. Recently, deep learning methods have also dominated this task as it happened in other computer vision tasks. Even though much progress has achieved in this domain, results are far from perfect. In this project, a multimodal representation for semantically conditioned image  inpainting algorithm will be designed to synthesize diverse results and provide controllobility to the user of the inpainted area.