Computer Engineering Department
CS5/690 Research Seminar I/II
Spring 2023

Coordinators, Time and Location

Özgür Ulusoy and Cevdet Aykanat

Mondays at 3:30pm as scheduled (Online via Zoom)

Announcements


Course Information

Graduate students present seminars on their ongoing research work (work in progress). Students registered in the Graduate Program in Computer Engineering Department are eligible to take this course. Students will usually take it after having spent some time doing research and just prior to defending their thesis.

The objective is to provide a forum for the communication of current research conducted in our department. It also aims to give the students the opportunity to discuss their research in a public forum and to improve their oral presentation style.

Grading for this course will be pass/fail. A passing grade can be obtained by sufficient attendance, a successful presentation, and active participation.

The seminar topic must be related to the current research of the student. The student is responsible for submitting a title and abstract to the coordinators two weeks prior to his/her presentation, and for informing their supervisor about the time & date of the talk. Supervisors are expected to attend their student's presentation.

Schedule

Week ofTimePresenterTitle
April 3 3:30pmSoheil AbadifardA Novel Ensemble Approach Based on Maximal Marginal Relevance (MMR) for Drifting Stream Classification
3:50pmMuhammad Umair AhmedAugmenting Bus Factor Analysis with Visualization
4:30pmSina BarazandehLearning to Generate 5' UTR Sequences for Optimized Ribosome Load and Gene Expression
4:50pmHakan SivükConditional Image Inpainting with Style Codes

April 17 3:30pmHamza IslamHySE: A Spring Embedder approach for hybrid graphs
3:50pmArçin Ülkü ErgüzenPersonality Style Transfer Between Animations with Deep Learning
4:30pmHamza PehlivanStyleRes: Transforming the Residuals for Real Image Editing with StyleGAN

April 24 3:30pmMuhammet Rafi ÇoktalaşStructural Variation Detection by Assembly-to-Assembly Comparison
3:50pmKutay TaşcıPartitioning for Communication Efficient Graph Neural Network Training
4:30pmOsama ZafarEffective Analysis of Big Data Through Graph Visualization with A Unified Complexity Management Framework

May 8 3:30pmGün KaynarPathway-informed deep learning model for survival analysis and pathological classification of gliomas
3:50pmYunus EsergünVision Transformer is All You Need
4:30pmİdil HanhanFinding Expert Developers Using Artifact Traceability Graphs
4:50pmVahid HaratianLeveraging File Significance in Bus Factor Estimation

Presentation Resources