جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۵ مورد دیگر

Prof. Dr. Mehmet Reşit Tolun is a full-time Professor in the Department of Software Engineering at Çankaya University (Turkey) since 2022. Previously held full-time professor positions at Konya Food and Agriculture University (2020-2022), Aksaray University (2013-2017), and TED University (2011-2013), along with a part-time professorship at Başkent University (2017-2020). Specializes in Artificial Intelligence , Machine Learning , and Data Mining , with a focus on deep learning applications in aerospace, biomedical data analysis, and software process improvement. PhD in Computer Science (University of Kent, 1985) MSc in Computer Science (University of Kent, 1982) BSc in Physics and Computer Science (University of Kent, 1981) Research Interests span deep learning frameworks, hybrid expert systems, software engineering methodologies, and biomedical signal processing. Publications emphasize practical implementations in medical diagnostics, robotics, and agricultural pest detection. Scientific Awards include the IEEE Third Millenium Medal (2000). Supervised over 55 graduate students, including Burak Çetin, Uğur Özotuk, and Mahinur Doğan. Collaborated with researchers from Orta Doğu Teknik Üniversitesi , Çankaya University , and Aksaray University .

Serdar ARSLANمشاهده پروفایل

مدرس

• Database Management Systems
• Data Structures and Algorithms
• Machine Learning
• +۳ مورد دیگر

Dr. Serdar Arslan is a Lecturer at the Department of Computer Engineering at Cankaya University. He holds a PhD in Computer Engineering from Middle East Technical University (METU), with a thesis on multidimensional data indexing. His academic background includes a Master's (2005) and Bachelor's (2001) in Computer Engineering from METU and Hacettepe University, respectively. His research focuses on database systems, machine learning, multimedia data indexing, and forecasting models. Education: Bachelor of Engineering, Computer Engineering, Hacettepe University (2001) Master of Science, Computer Engineering, METU (2005) Doctor of Philosophy, Computer Engineering, METU (2018) Research Interests: Machine Learning applications in healthcare forecasting and financial markets Advanced indexing techniques for multimedia databases (e.g., MM-FOOD structure) Natural language processing for stance detection in political discourse Hybrid forecasting models combining LSTM and Prophet algorithms Domain-specific NLP for product name extraction in Turkish text Publications: His recent work emphasizes machine learning-driven solutions for complex systems, including pandemic modeling, cryptocurrency analysis, and conflict discourse analysis. His earlier contributions focused on multimedia indexing and image retrieval systems using MPEG-7 standards. The 2025 paper on OSINT architecture frameworks highlights his expanding focus on cybersecurity and system design. Labs/Teams: While no specific lab is mentioned, his GitHub repositories (e.g., Forecasting, NLP projects) suggest active involvement in collaborative research projects related to his domains.

Anıl Koyuncuمشاهده پروفایل

استادیار

• Automated Program Repair
• Bug Localization
• Fix Pattern Mining
• +۳ مورد دیگر

Dr. Anıl Koyuncu is an Assistant Professor in the Department of Computer Engineering at Bilkent University. His research focuses on automated program repair, bug localization, and applying machine learning techniques to software engineering challenges. He actively contributes to academic service as a reviewer for journals like TOSEM and SoSyM, and serves on program committees for top conferences such as ICSE and ISSTA. He teaches courses including Automated Program Repair, Object-Oriented Software Engineering, and Software Design Patterns. His research group, the Automated Program Repair and Tools for Software Maintenance team, explores improving practitioner adoption of automated repair systems through data mining, program analysis, and fault localization. Key contributions include FixMiner for mining fix patterns and iFixR for bug-report-driven repair. Dr. Koyuncu has received the Best ERA Paper Award at APSEC 2018. His work emphasizes empirical studies on repair system evaluation, fault localization biases, and combining engineered features with learned embeddings for patch prediction.

Eray Tüzünمشاهده پروفایل

دانشیار

• Software Analytics
• Mining Software Repositories
• Empirical Software Engineering
• +۳ مورد دیگر

Eray Tüzün is an Associate Professor of Computer Engineering at Bilkent University, leading the BILSEN Research Group focused on Software Engineering and Data Analytics. He holds a PhD in Information Systems alongside bachelor's and master's degrees in Computer Science. With over 20 years of industry experience, he previously worked at Havelsan, Microsoft, Howard Hughes Medical Institute, and CWRU Genomics Center in roles spanning software engineering and project management. His research emphasizes software analytics, mining software repositories, and empirical software engineering practices. He actively contributes to the International Software Engineering Research Network (ISERN) and holds certifications such as PSM, PSPO, and MCSD. Tüzün advocates for bridging educational and industrial gaps through interactive teaching methods and serious games for developer training. His work on code review practices, traceability tools (e.g., RSTrace+), and bus factor estimation (BFSig, Bus Factor Explorer) highlights practical software engineering challenges. He explores applications of AI in code generation evaluation and process improvement. Tüzün's BILSEN Lab engages in projects like BugCraft (bug reproduction) and SmartDelta (automated QA). He maintains active IEEE and ACM SIGSOFT memberships and contributes to conferences like ICSSP and ICGSE. His educational initiatives include board games (ToolStackers) and plugins for teaching DevOps and version control. Current research trends focus on LLM applications in code review, data cleaning impacts, and developer productivity metrics. Grants and collaborations involve industrial partnerships and national/international research networks. He supervises graduate students in masters/PhD programs and undergraduate volunteers, emphasizing empirical studies and tool development. Future work includes expanding AI-driven software analytics and educational technology integration.