Graduate School of Informatics, Thesis

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Thesis (1020)

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Akyol, Mehmet Ali (2)
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1998 - 1999 (3)
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2010 - 2019 (495)
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Master Thesis (770)
Ph.D. Thesis (250)

Recent Submissions

Enhancement of Demand Forecasting for Agrochemical Products Through Advanced Analytics Kaya, Gizem; Eren, Pekin Erhan; Department of Data Informatics (2026-1-20) Demand forecasting is an essential part of supply chain planning. Accurate prediction of sales directly affect the resource efficiency and success of inventory management process. However it is especially challenging for s...
DATA GOVERNANCE CAPABILITY MATURITY MODEL Gökalp, Selin; Koçyiğit, Altan; Department of Information Systems (2026-1-16) Organizations increasingly witness data as a strategic asset, but quite a few of organizations still confront significant difficulties in the development of coherent and scalable data governance practices that can create v...
A Hybrid Deep Learning Framework for Advanced Detection of Domain Generation Algorithms Düztaş, Sinan; Tezcan, Cihangir; Department of Cybersecurity (2026-1-16) Cyber threat actors (CTAs) rely on botnets to carry out a wide range of malicious operations. These botnets are controlled by command-and-control (C2) servers. If these servers are exposed, CTAs can be detected and their a...
MORTALITY SALIENCE AND RISK-TAKING IN DECISION MAKING: CAUSAL AND COGNITIVE MODELLING OF BEHAVIORAL AND NEURAL MECHANISMS Başerdem, Elif Öykü; Yet, Barbaros; Department of Cognitive Sciences (2026-1-14) The replication crisis poses a significant challenge for Terror Management Theory (TMT), particularly regarding the link between Mortality Salience (MS) and risk-taking. While TMT argues that reminders of mortality directl...
ID-SDM: EXTENDING INFLUENCE DIAGRAMS FOR SHARED DECISION-MAKING AND CLINICIAN-PATIENT RELATIONSHIP YILDIRIM, ZELIHA; YET, BARBAROS; Department of Cognitive Sciences (2026-1-13) Shared Decision-Making (SDM) is a patient-centered healthcare approach emphasizing patients as equal partners with physicians in a two-way information exchange. This dissertation introduces a novel framework, ID-SDM (Influ...
AN ADAPTIVE HYBRID EXTREME-VALUE FRAMEWORK FOR DAILY VALUE-AT-RISK ESTIMATION IN THE TURKISH EQUITY MARKET Kulu, Ali Rıfat; Koçyiğit, Altan; Department of Information Systems (2026-1-12) Standard risk management frameworks, particularly those relying on the Value-at-Risk (VaR) metric under normality assumptions, might fail to capture the extreme volatility observed in emerging markets. This thesis evaluate...
A DATA DRIVEN FRAMEWORK FOR SURFACE ROUGHNESS PREDICTION IN ADDITIVE MANUFACTURING Erkan, Engin Deniz; Sürer, Elif; Yaman, Ulaş; Department of Data Informatics (2026-1-6) Additive manufacturing is a technology that aims to fabricate three-dimensional objects by adding layers of materials on top of each other. However, the surface quality of objects fabricated via additive manufacturing may ...
Unified Local-Global Prompt Learning for Few-Shot Vision-Language Adaptation via Optimal Transport Kizaroğlu, Deniz; Temizel, Alptekin; Department of Data Informatics (2026-1-05) Few-shot adaptation of large-scale vision-language models typically relies on learning soft prompts matched to holistic image embeddings. While effective for general recognition, this global approach often fails to capture...
A modular framework for PDTB-style multilingual discourse parsing Er, Mustafa Erolcan; Zeyrek Bozşahin, Deniz; Kurfalı, Murathan; Department of Cognitive Sciences (2025-12-23) Discourse parsing is one of the most challenging tasks in the field of Natural Language Processing (NLP) due to its inherent complexity. However, advancements in large language model techniques have begun to demonstrate re...
Analysis of Generative AI Technologies' Adoption Using Interpretive Structural Modeling: Empirical Findings from Small and Medium-Sized IT Enterprises in Türkiye Şimşek, Buse; Özkan Yıldırım, Sevgi; Department of Information Systems (2025-12-22) In today’s evolving technological landscape, Generative Artificial Intelligence (GenAI) has emerged as a transformative component within digitalization processes across industries. In the IT sector, GenAI is increasingly b...
SPLIT-FED LEARNING APPROACH FOR HOUSE PRICE PREDICTION WITH HETEROGENEOUS FEATURES Nikel, Ayşenur; Koçyiğit, Altan; Department of Information Systems (2025-12-17) Federated Learning is an emerging approach for collaborative training of a common global model without disclosing raw data available in multiple clients. Previous studies mainly focus on two distinct types of heterogeneity...
DEVELOPING AN APPROACH FOR MIGRATION OF SMALL AND MEDIUM ENTERPRISES TO CLOUD COMPUTING ENVIRONMENTS Bol, Furkan; Eren, Pekin Erhan; Department of Information Systems (2025-12-1) Technology is rapidly evolving, and many organizations must adapt to this rapid development. Cloud computing, one of the most important aspects of technological advancement, is also part of this digitalization. All organiz...
Factors Influencing Employee Turnover in the IT Sector Tutlübük Pala, Şifa; Eren, Pekin Erhan; Department of Data Informatics (2025-12-1) Employee turnover is one of the most important problems that organizations face, especially in rapidly developing and competitive sectors such as information technology (IT). This study aims to employ machine learning tech...
ANALYZING ADVERSE EVENTS OF FDA APPROVED AI-ENABLED MEDICAL DEVICES FOR RISK-AWARE DEVELOPMENT Yang, Annie; Özcan Top, Özden; Department of Information Systems (2025-11-26) There is increased research interest and development of artificial intelligence (AI) in various industries, especially in healthcare. Regulatory bodies are evolving to promote patient safety and product efficacy. As theori...
Evaluating the Impact of Human Values on Responsible AI Development from Stakeholder Perspectives İlhan, Merve; Özcan Top, Özden; Department of Information Systems (2025-11-5) This thesis addresses the need for responsible design and development of artificial intelligence (AI) technologies that are rapidly integrating into every aspect of life. With this rapid integration, the influence of stake...
SITE-SPECIFIC STRONG MOTION GENERATION AND LATENT SPACE ANALYSIS AT SEISMIC STATIONS Bevan Deniz , Çılğın; Akagündüz, Erdem; Tileylioğlu, Salih; Department of Data Informatics (2025-11-3) Modeling the strong motion data is crucial for seismic hazard assessment. In our study, we aim to unveil the nature of strong motion data and soil characteristics using generative AI. We created a generative model that eff...
Deciphering sequence variations and splicing sensitivity: predictive analysis of PSI in SRRM4 response groups Böler, Ümit Sude; Otlu Sarıtaş, Burçak; Dias, Mafalda; Department of Bioinformatics (2025-9-01) Alternative splicing is essential for the expansion of transcriptomic complexity, with microexons representing some of the most functionally critical and tightly regulated splicing events in neural development. Because mic...
Exploring Technical Debt Across ML Project Lifecycle: A Process-Oriented Analysis Based on ISO Standards Yorgancılar Akgül, Nilay; Taşkaya Temizel, Tuğba; Özcan Top, Özden; Department of Data Informatics (2025-9) AI-integrated software systems are increasingly adopted across various domains, offering improved capabilities but also introducing unique technical challenges. Compared to traditional software systems, AI systems are more...
FLAW DETECTION IN ALUMINIUM CASTINGS LEVERAGING SYNTHETIC DATA FOR NON-DESTRUCTIVE TESTING Erkan, Umut Can; Sürer, Elif; Yaman, Ulaş; Department of Modeling and Simulation (2025-9-01) Non-destructive testing (NDT) using radiographic imaging plays a vital role in quality assurance for industrial manufacturing, particularly in detecting internal flaws in aluminum castings. However, the application of deep...
Modeling Disease Progression with Diffusion-Based Generative Models KURT, Meryem Mine; Temizel, Alptekin; Department of Modeling and Simulation (2025-8-29) Disease progression modeling in medical imaging presents significant challenges due to the scarcity of longitudinal data and the inherent class imbalance in medical datasets. This thesis introduces a novel conditional diff...

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