Graduate School of Informatics

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Recent Submissions

Identification and validation of a previously missed mutational signature in colorectal cancer Kazachkova, Mariya; Otlu Sarıtaş, Burçak; Díaz-Gay, Marcos; Abbasi, Ammal; Moody, Sarah; Jiang, Zichen; Perdomo, Sandra; Wedge, David. C.; Brennan, Paul; Stratton, Michael. R.; Alexandrov, Ludmil. B. (2026-12-01) Mutational signature analysis has enhanced our understanding of mutagenic processes. In a recent study, we analyzed 802 microsatellite-stable colorectal cancers (CRC) and identified a de novo signature, SBS_D, which was de...
Exploring the genetic landscape of COVID-19 susceptibility and severity among patients in Türkiye Er, Ahmet Gorkem; Çakır, Yavuzhan; Er, Berrin; Burduroğlu, Hüseyin Cahit; Çakmak, Mehmet; ÖZIŞIK, LALE; DURUSU TANRIÖVER, MİNE; Topeli, Arzu; Aydın Son, Yeşim; Ünal, Serhat (2026-12-01) Background: One of the most challenging factors for clinicians in managing COVID-19 has been differences in the clinical course. To investigate the parameters associated with severe disease in detail, along with examining ...
SALGINTR: development and early evaluation of a low-cost cloud-based digital participatory surveillance system for influenza-like Illness among physicians in Türkiye — a proof of concept ÖNTAŞ, ERAY; Güçlü, Hasan; Aydın Son, Yeşim (2026-12-01) Background: Participatory surveillance complements sentinel influenza monitoring in high-income settings, yet no such platform has targeted physicians as both participants and clinical sentinels. We established SALGINTR, a...
Mitigating Spatial Disorientation via Spatial Audio: A Psychoacoustics Study Cengiz, Gamze; Çakır, Murat Perit; Hacıhabiboğlu, Hüseyin; Department of Cognitive Sciences (2026-9-04) Spatial disorientation (SD) is a perceptual phenomenon affecting pilots, implicated in roughly one-fifth of USAF Class A aviation mishaps. While the vestibular, visual, and auditory sys- tems collectively maintain spatial ...
EFFICIENT MULTIMODAL CNN-TRANSFORMER ARCHITECTURE WITH FEATURE DISTILLATION FOR REMOTE SENSING UNDER MISSING MODALITIES Moridsedaghat, Laya; Akagündüz, Erdem; İREM, ÜLKÜ; Department of Data Informatics (2026-9-3) Multimodal remote sensing semantic segmentation can benefit from combining different types of spectral information, such as RGB, near-infrared (NIR), and shortwave infrared (SWIR) bands. Since each modality provides differ...
AN ANALYSIS OF INCIDENT INVESTIGATION DURATION PERFORMANCE IN HOME HEALTH CARE Korkmaz, Ramis; Özkan Yıldırım, Sevgi; Department of Information Systems (2026-9-03) Incident management systems play an important role in documenting adverse events and supporting organizational learning in healthcare. However, while incident reporting and investigation quality have received considerable ...
Layer-wise structural and mechanistic interpretation of OpenVLA using controlled perturbations Yıldız, Turgay; Özge, Umut; Ataman, Duygu; Department of Cognitive Sciences (2026-9-02) Limitations of conventional policies in robot learning have driven the adoption of large-scale pretrained models, known as foundation models, leading to the emergence of Vision-Language- Action (VLA) models. Although VLA m...
SALGINTR: Development and Evaluation of a Digital Participatory Surveillance System to Monitor Influenza-like Illness in Türkiye Based on Self-Reported Data from A Physician Cohort Öntaş, Eray; Aydın Son, Yeşim; Güçlü, Hasan; Department of Medical Informatics (2026-9-2) Influenza sentinel surveillance is laboratory-anchored but narrow in coverage, slow and costly to run. We developed SALGINTR, a physician-based digital participatory system in which physicians self-report their own weekly ...
GENERATIVE LANGUAGE MODELS VERSUS ENCODER-BASED LANGUAGE MODELS FOR MULTILINGUAL PHISHING EMAIL DETECTION Bor, Nesil; Acar, Aybar Can; Department of Cybersecurity (2026-9-2) This thesis evaluates 25 language models to compare generative and classification architectures for phishing email detection in resource-constrained local environments. A major challenge in modern cybersecurity is the lack...
SOT-GLP: Sparse optimal transport guided local-global prompt learning Kizaroglu, Deniz; Kucuktas, Ulku Tuncer; Cakmakyurdu, Emre; Temizel, Alptekin (2026-09-01) Few-shot adaptation of vision-language models (VLMs) like CLIP typically relies on learning textual prompts matched to global image embeddings. Recent works extend this paradigm by incorporating local image-text alignment ...
A process-centric mapping of non-technical debt instances to ISO/IEC 5338 in AI-enabled projects Kapiyasheva, Diana; Özcan Top, Özden; Taşkaya Temizel, Tuğba (2026-09-01) Non-Technical Debt (NTD), arising mainly from organizational, cultural, and people-related inefficiencies, significantly compromises the quality and sustainability of AI-enabled software systems. While a growing ecosystem ...
Valorisation of Composted Spent Coffee Grounds as a Sustainable Peat Substitute to Enhance Growth and Visual Quality of <i>Dieffenbachia amoena</i> Özdemir, Serkan; Ozer, Hasan; Eren, Beytullah; Ozdemir, Saim (2026-09-01) This study explores the reutilisation of spent coffee grounds (SCG) in the horticultural sector as an eco-functional additive to develop innovative growing media that enhance the propagation of stem cuttings. Raw SCG under...
Implicit security requirements classification with large language models using the OWASP application security verification standard: a shift-left approach Gür, Yusuf; Taşkaya Temizel, Tuğba; Günel Kılıç, Banu (2026-09-01) Cybersecurity threats require early integration of security, starting from the requirements analysis phase of the Software Development Life Cycle (SDLC). However, security requirements in Software Requirements Specificatio...
GRAPH-GUIDED RETRIEVAL-AUGMENTED GENERATION FOR ENTERPRISE ELECTRONIC PRODUCT DOCUMENTATION Özen, Şeymanur; Temizel, Tuğba Taşkaya; Department of Data Informatics (2026-8-31) Technical documentation for enterprise electronic products is a primary source of engineering and product knowledge. It spans several formats, such as datasheets and brochures, each presenting information differently: broc...
Benchmarking and reducing hallucination in large language models through hypothetical terms Uluoğlakcı, Cem; Taşkaya Temizel, Tuğba; Department of Information Systems (2026-8-31) Supervised fine-tuning biases language models toward answering even without relevant knowledge, producing confident, unsupported statements, a failure better described as confabulation than hallucination. Training models t...
A robust machine learning framework for predicting the higher heating value of poultry litter using proximate analysis Eren, Beytullah; Uzun, Suleyman; Özdemir, Serkan (2026-08-01) Accurate estimation of the higher heating value (HHV) of poultry litter is critical for its valorization as a renewable energy feedstock. However, the heterogeneity of poultry litter and data scarcity pose challenges for p...
Synthesizing longitudinal ulcerative colitis progression via disentangled latent diffusion Dundar, Umut; Temizel, Alptekin (2026-08-01)
Large language models for UML diagram generation: evaluating and improving local models against a hosted reference model Ateş, Onur; Günel Kılıç, Banu; Department of Information Systems (2026-8) Large language models and agentic tools are taking on more of the implementation phase, and the developer’s role is shifting toward defining intent and verifying that the output matches it. Code is generated more rapidly a...
Prior therapy defines mutation profiles in childhood cancer at relapse Layeghifard, Mehdi; et. al. (2026-07-22) Children with cancer develop many short- and long-term side-effects of treatment1, but the amount of DNA damage associated with chemotherapy exposure is unclear2. Here we used mutational signatures to measure this damage u...
An ICAP-informed rubric for analyzing students' questions to generative AI: engagement patterns and dynamics exploration Ding, Lu; Rodenberg, Rachel; Er, Erkan; Nguyen, Ha; Yoon, Meehyun (2026-07-22) As generative AI (genAI) tools such as ChatGPT become increasingly integrated into education, understanding how students use them to support learning is essential. This study examines undergraduate students' questioning st...

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