Find Academic Supervisors

Ahmet SayarView profile

Associate Professor

• Distributed Systems
• Big Data
• Data-Intensive Computing
• +7 more

Assoc. Prof. Dr. Ahmet Sayar is an Associate Professor at the Department of Computer Engineering, Faculty of Engineering at Kocaeli University, Turkey. He holds an M.Sc. (2001) and Ph.D. (2009) in Computer Science from Syracuse and Indiana Universities, USA. His research focuses on Distributed Systems, Big Data, Data-Intensive Computing, Geographic Information Systems (GIS), and Exploratory Data Analysis (EDA). He has co-authored over 150 papers, 15 book chapters, and 1 book. Currently, he serves as Head of Student Affairs at Kocaeli University and as an associate editor for multiple journals. Education: M.Sc. in Computer Science, Syracuse University (2001) Ph.D. in Computer Science, Indiana University (2009) Research Interests: Parallel and Distributed Algorithms Big Data Analytics & Cloud Computing Machine Learning Applications (e.g., Image Processing, NLP) GIS and Remote Sensing Blockchain Technology for IoT and Logistics Recent Trends in Articles: His recent work emphasizes real-time data processing (e.g., video stream analytics), blockchain for supply chains, and AI-driven solutions for healthcare, transportation, and urban management. He explores ethical aspects of web scraping and low-code platforms for process automation. Advising & Grants: Advised 18 master’s/phd theses. Involved in TÜBİTAK projects and KOSGEB innovation programs. Member of editorial boards and national advisory committees. Labs/Teams: Leads university-level student affairs initiatives and collaborates on interdisciplinary projects involving distributed systems and big data frameworks.

• Distributed Database Design
• Query Optimization
• Evolutionary Algorithms
• +8 more

Prof. Ahmet Cosar is a faculty member in the Department of Computer Engineering at the Middle East Technical University (METU), Ankara, Turkey. He holds a PhD in Computer Science from the University of Minnesota (1996), an MS in Computer Engineering from Bilkent University (1988), and a BS in Computer Engineering from METU (1986). His research focuses on distributed database design, query optimization, evolutionary algorithms, computer networks, and cloud computing. He leads the Intelligent Data Analysis Group (IDAG) and teaches courses such as CENG 240, CMPE 275, and CENG 280. Education: PhD, Computer Science, University of Minnesota, 1996 MS, Computer Engineering, Bilkent University, 1988 BS, Computer Engineering, METU, 1986 Research Interests: Query optimization in distributed databases Evolutionary algorithms (e.g., genetic algorithms, particle swarm optimization) Cloud computing and data warehouse design Machine learning applications in cybersecurity Wireless sensor networks and data fusion Publications: Over 50 peer-reviewed articles in journals like Computers & Industrial Engineering and Neurocomputing , focusing on optimization algorithms, cloud resource allocation, and machine learning techniques. Recent work includes island-parallel metaheuristics for graph coloring and reinforcement learning for adaptive interventions. Advising & Grants: Supervised over 30 graduate students (PhD and MS) in areas like evolutionary algorithms, cloud databases, and sensor networks. Active in research grants related to distributed systems and big data. Labs/Teams: Leads the Intelligent Data Analysis Group (IDAG), collaborating on projects in optimization, machine learning, and cloud computing.

Murat SARANView profile

Assistant Professor

• Human-Computer Interaction
• Gamification
• Intelligent Learning Systems
• +5 more

Dr. Murat SARAN is an Assistant Professor in the Department of Computer Engineering at Çankaya University, Ankara, Turkey. He serves as Director of the Distance Education Application and Research Center (DEARC), focusing on innovative educational technologies. His academic background includes a PhD (2009) and MSc (2003) in Computer and Educational Technologies from Middle East Technical University (1999-2009). Education: Bachelor's: Middle East Technical University, Computer and Educational Technologies (1999) Master's: Middle East Technical University, Computer and Educational Technologies (2003) PhD: Middle East Technical University, Computer and Educational Technologies (2009) Research Interests: Dr. SARAN specializes in Human-Computer Interaction, Gamification, and Mobile Learning. His work spans algorithmic thinking, context-aware systems, virtual reality integration in education, and data augmentation techniques for machine learning. He has contributed to projects addressing digital literacy in primary education and emotion recognition via computer vision. Key Projects: ICOINS (2018–2020): Developed Industry 4.0 training tools for SMEs (€203,858) Mesh-Based Mobile Education Platform (2012–2014): Managed a TL 373,128 project for SME/educational institutions HESAPRO (2011–2013): Analyzed health-safety-productivity links in workplaces (€103,000) Grants & Labs: His research has been supported by TÜBİTAK and EU grants. He leads the DEARC lab, focusing on distance education innovation and mobile learning systems.

A. Ercüment ÇiçekView profile

Associate Professor

• Computational Biology
• Genomics
• Machine Learning
• +5 more

A. Ercüment Çiçek is an Associate Professor at the Computer Engineering Department of Bilkent University and an Adjunct Faculty Member at Carnegie Mellon University's Computational Biology Department. He holds editorial roles, including Associate Editor for IEEE/ACM Transactions in Computational Biology and Bioinformatics. His research focuses on computational biology, machine learning applications in genomics, privacy in genomic data, and neurodevelopmental disorders. He has conducted visiting professorships at EPFL (2022-2023) and has been recognized with awards such as the Turkish Intelligence Foundation Akıngüç Award and the Bilkent University Aziz Sancar Incentive Award. Education includes a Ph.D. in Computer Science from Case Western Reserve University (2009-2013), M.Sc. from Sabancı University (2007-2009), and B.Sc. from Sabancı University (2003-2007). His academic journey includes fellowships like the Lane Fellowship at CMU and Fulbright Doctorate Fellowship. Research interests span machine learning for genomics, privacy-preserving data sharing, metabolic network analysis, and algorithm development for bioinformatics. Notable projects include SPADIS for SNP selection and HERCULES for long-read error correction. His work bridges computer science and biology, with applications in neurodevelopmental disorders and precision medicine. He has delivered keynotes and presentations globally, including at UCLA, EPFL, and RECOMB conferences. Teaching responsibilities include courses like Introduction to Machine Learning and Computational Systems Biology at Bilkent University. Active in interdisciplinary collaborations, he has led research teams and contributed to lab initiatives like the Laboratory for Neurodevelopmental Systems Biology. Awards: Turkish Intelligence Foundation Akıngüç Award 2025, Distinguished Teaching Award 2022, etc. Grants: Lane Fellowship, METU Parlar Foundation, etc. Labs: Collaborated with the Laboratory for Neurodevelopmental Systems Biology at EPFL and Lane Center for Computational Biology at CMU.

Damla OğuzView profile

Assistant Professor

• Data Mining
• Database Systems
• Query Optimization
• +6 more

Damla Oğuz is an Assistant Professor and Deputy Head of Department in the Department of Computer Engineering at Izmir Institute of Technology. She has held this position since December 2019, following her appointment as an Assistant Professor in the Department of Software Engineering at Yaşar University from 2017 to 2019. Her educational background includes: B.Sc. in Software Engineering (2008) and Industrial Systems Engineering (2009) from Izmir University of Economics M.Sc. in Computer Engineering (2012) from Izmir Institute of Technology Ph.D. in Computer Science (2017) from Paul Sabatier University, France (completed as part of a cotutelle program with Ege University) Damla Oğuz's research focuses on data mining and query optimization in distributed databases . Her work spans multiple areas including high-utility itemset mining, federated query processing, knowledge base evaluation, and the application of large language models in education. She has made significant contributions to understanding how to efficiently process queries across distributed data sources, particularly in the context of semantic web technologies and linked data. Her research often addresses the challenges of scalability, privacy, and performance in large-scale data management systems. Her recent publications demonstrate a clear trend toward addressing contemporary challenges in data management and analysis. Starting with foundational work in itemset mining algorithms, her research has evolved to tackle more complex problems in federated query processing, knowledge base evaluation, and the integration of large language models into educational contexts. The breadth of her work spans theoretical algorithm development, practical system implementation, and educational applications. Her teaching portfolio includes: CENG 212 - Concept of Programming Languages SEDS 502 - Modern Database Management Systems SEDS 535 - Information Extraction CENG 544/SEDS 542 - Large Scale Data Management CENG 465 - Principles of Data-Intensive Systems Her professional activities include: Deputy Head of Department at Izmir Institute of Technology Active research in data management and mining Teaching undergraduate and graduate courses in computer engineering

Esra ErdemView profile

Professor

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Answer Set Programming
• +6 more

Esra Erdem is a Professor in the Department of Computer Science and Engineering at Sabanci University, Faculty of Engineering and Natural Sciences. Her research focuses on the mathematical foundations of knowledge representation, automated reasoning, and answer set programming, with applications in bioinformatics, logistics, cognitive robotics, and economics. She has developed frameworks for hybrid planning, spatial-temporal reasoning, and multi-agent coordination using logic-based methods. She earned her Ph.D. in Computer Sciences (2002) at the University of Texas at Austin under Vladimir Lifschitz. Her academic genealogy traces back to Nikolai Shanin, Pavel Aleksandrov, and Karl Weierstrass. Her recent publications emphasize answer set programming for robotics, including collaborative assembly, path finding, and spatial reasoning. She applies these techniques to real-world challenges in cognitive factories and rehabilitation robotics. Erdem co-edited proceedings for KR 2021 and ICLP 2019 Technical Communications. She serves as an academic advisor and has contributed to educational tools like ReAct! for AI planning in robotics.

Hakan EmekciView profile

Assistant Professor

• Artificial Intelligence
• Data Science
• Machine Learning
• +5 more

Hakan Emekci is an Assistant Professor at TED University's Graduate School of Applied Data Science. He teaches courses such as Statistical Learning, Data Analytics, and Information Retrieval in the Applied Data Science Master Program. His research focuses on AI applications in healthcare, education technology, econometrics, and data-driven methodologies. Emekci has published works on specialized language models for medical contexts, RAG systems optimization, and the integration of AI in educational frameworks. His recent studies emphasize domain-specific AI solutions and their practical implementations across diverse sectors. Emekci's academic contributions include analyzing central bank policies' impact on financial markets and developing computational frameworks for data mining. He actively teaches advanced courses at both undergraduate and graduate levels, including Data Structures and Algorithms. His work bridges theoretical data science concepts with real-world applications in healthcare, education, and finance. Notable research areas include: Healthcare informatics & AI-driven diagnostic systems Educational technology innovations Machine learning model optimization Financial econometric analysis Domain-specific large language models His publications from 2025 highlight advancements in multi-agent medical frameworks and comparative studies of retrieval-augmented generation techniques. Earlier work (2017-2018) established foundational research in econometric policy analysis and R-based data mining methodologies.

• Natural Language Processing (NLP)
• Computational Linguistics
• Artificial Intelligence
• +11 more

Prof. Dr. Gülşen Cebiroğlu Eryiğit is a Professor at Istanbul Technical University (ITU) in the Department of Artificial Intelligence and Data Engineering under the Faculty of Computer and Informatics. As the founder and director of the ITU Natural Language Processing Group , she leads Turkey's foremost research team in Turkish-language NLP. Her work has achieved global impact through the first software export from ITU in NLP, with 6,000+ Google Scholar citations as of 2023. Education: MSc & PhD, Computer Engineering, ITU (2002-2007) BSc, Computer Engineering, Marmara University (1995-2000) High School: Saint-Michel (French curriculum) Her research focuses on natural language processing for morphologically complex languages like Turkish, with specializations in: Dependency parsing and treebank development Multilingual transfer learning systems Abstract meaning representation Language technology infrastructure Coreference resolution in agglutinative languages Gamification of linguistic education Recent publications show active research trends in: Transforming financial document analysis with BiLSTM-CRF architectures Advancing Turkish language models through ViBERTgrid implementations Developing multilingual frameworks under EU COST Actions Creating semantic search engines for job matching platforms Optimizing automotive demand management through dialogue systems Building large language models (LLMs) for Turkish Scientific recognition includes: Siemens Excellence Award (2007) for doctoral research Above Threshold Award (TÜBİTAK, 2015) EU 7th Framework Certificate of Appreciation (2012) ITU Thank You Plaque (2017) Current leadership roles: Senior Action Editor, ACL RR Director, ITU TÖMER (Turkish Language Teaching Center) Coordinator, ITU NLP Group Co-Chair, EU UniDive COST Action WG3 Principal Investigator on 3 active projects

• Data Engineering
• Data Science
• Indoor Location-Based Services
• +3 more

Tiantian Liu is an Assistant Professor in the Department of Computer Science at Aalborg University, under the Technical Faculty of IT and Design. Her research focuses on data engineering and systems, particularly in the context of indoor location-based services and data science. Research Interests: Her work spans data management, indoor positioning, spatiotemporal databases, and scalable systems. She applies techniques from data science and computer science to solve challenges in real-time data processing, data quality, and context-aware applications. The publication trend from 2020 to 2024 shows a consistent focus on data engineering, with topics including indoor LBS, query optimization, distributed systems, and data integration. Her research combines theoretical database principles with practical system implementations. Scientific Awards: Prize (1) Advising and Grants: While no formal students are listed, she has participated in externally funded research projects. She was a project participant in Data Management Foundations for Indoor LBS (2019–2021), contributing to foundational work in indoor data systems. Labs and Teams: She is a member of the Data Engineering, Science and Systems research group at Aalborg University, collaborating on data-intensive systems and applications.