Find Academic Supervisors

• Structural Engineering
• Optimization
• Mechanics of Solid Bodies
• +5 more

Prof. İbrahim Aydoğdu is an Associate Professor at Akdeniz University, Faculty of Engineering, Department of Civil Engineering , with a concurrent Associate Professor role at Georgia Institute of Technology, Engineering Faculty, Mechanical Engineering . His career spans structural engineering, metaheuristic optimization, and thermohydraulic systems. PhD in Engineering Sciences from Middle East Technical University Postdoctoral research at Georgia Institute of Technology His research focuses on structural optimization , steel and composite structures , and metaheuristic algorithms . He has supervised 13 theses, including projects on seismic isolation, nanoscale beam optimization, and public transport efficiency. His work emphasizes computational methods for structural design, with funded research from TUBITAK and higher education institutions. Key trends in his 96 publications include applications of artificial bee colony algorithms , social spider optimization , and GPU-based parallel programming in civil and mechanical engineering contexts. He has contributed to books on harmony search methods and nature-inspired algorithms in structural design.

SEMA KAYHANView profile

Professor

• Image Processing
• Compressive Sensing
• Signal Processing
• +11 more

Professor Sema Kayhan is a faculty member at Gaziantep University , Faculty of Engineering , Department of Electrical and Electronic Engineering . She has held the academic rank of Professor since 2021, after progressing from Associate Professor (2016-2021) and Assistant Professor (2007-2015). Her career began at Gaziantep University as a Research Assistant (1996-2005) and includes administrative roles as Vice Head of Department (2013-2015). Doctorate: 1999-2005, Gaziantep University Institute of Science, Electrical and Electronic Engineering Degree: 1996-1999, Gaziantep University Faculty of Engineering, Electrical and Electronic Engineering & Computer Science Licence: 1991-1996, Gaziantep University Faculty of Engineering, Electrical and Electronics Engineering (English) Her research spans Image Processing , Compressive Sensing , Machine Learning , and Biomedical Signal Processing , with notable contributions to ECG signal reconstruction , chaotic encryption , and FPGA-based hardware acceleration . She has supervised 23 theses, including PhD works on hybrid deep learning for schizophrenia detection , sparse extreme learning machines , and smart home solar energy systems . Her 15 most recent publications (2015-2022) demonstrate expertise in image watermarking , encryption , antenna design , and ECG signal processing , often leveraging chaos theory , extreme learning machines , and FPGA implementations . She has also contributed to NLP for Arabic-alphabet languages and retinal blood vessel segmentation via transfer learning. Professor Kayhan's projects include renewing jacquard control systems (2007-2008) and ECG signal reconstruction via compressive sensing on FPGA (2016-2017). She co-designed a smart home model using solar energy (2017) and has been a Member of the Chamber of Electrical Engineers since 1997.

Ali KiliçView profile

Assistant Professor

• Mechanical Engineering
• Mechatronics
• Robotics
• +3 more

Ali Kiliç is an Assistant Professor at the Department of Mechanical Engineering , Gaziantep University Faculty of Engineering . He has been actively involved in education, research, and project leadership in mechanical engineering, robotics, mechatronics, and electrospinning technology since 2017. Education: Earned his Doctorate (2016), MSc (2010), and Bachelor's (2005) in Mechanical Engineering, all from Gaziantep University. Research Interests span advanced robotics, mechatronic system design, electrospinning technology, variable stiffness actuators, industrial automation, and 3D printing. His work bridges mechanical design with intelligent control systems and innovative material processing techniques. Article Trends focus on nanofiber production, robotic sorting systems, TRIZ-based design, and filament winding machines. His publications highlight interdisciplinary approaches combining materials science, mechanical engineering, and control theory, with a strong emphasis on industrial applications and process optimization. Thesis Supervision includes doctoral and master's students working on additive manufacturing, variable stiffness actuators, and deep learning applications in food sorting. Collaborations are frequently with Sadettin Kapucu , a prominent researcher in robotics and mechatronics.

Bekir Tevfik AkgünView profile

Professor

• Artificial Intelligence
• Information Security
• Internet of Things
• +4 more

Prof. Bekir Tevfik Akgün serves as Professor and Dean of the Faculty of Computer and Information Sciences at Yeditepe University, with prior academic appointments at Istanbul Okan University (Department Head, Institute Director), Ohio State University, and Yildiz Technical University (Dean). His expertise spans artificial intelligence, information security, computer graphics, and distributed systems, supported by extensive research funding and supervision of 19 graduate students. Educational background includes: Ph.D. in Control and Computer Engineering, Istanbul Technical University (1991) M.S. in Control and Computer Engineering, Istanbul Technical University (1984) B.S. in Electrical Engineering, Istanbul State Academy of Engineering and Architecture (1981) His research integrates theoretical and applied computer science, with recent focus on AI-driven environmental monitoring (forest fire detection via drone-IoT networks), bioinformatics security, and advanced color models. Early work established foundational contributions in digital art (marbled paper techniques) and real-time operating systems, evolving into contemporary applications in energy management and autonomous systems. Publication trends since 2001 reveal consistent innovation across domains: computer graphics (2004-2024), distributed systems (2001), and emerging AI/IoT applications (2022-2024). The interdisciplinary nature of his work bridges theoretical computer science with practical implementations in security, environmental science, and human-computer interaction. Scientific Awards: No major scientific awards were listed in the provided information. Advising and Grants: Supervised 18 master's theses and 1 doctoral dissertation covering autonomous vehicles, deep learning, and IoT systems. Secured over 1.5 million Turkish Lira in research funding through TÜBİTAK projects including Smart Renewable Energy Management System (2018-2021, 159,636 TL) and Advanced Autonomous Bus System (2018-2021, 915,810.99 TL), with additional projects in battery management and metrobus efficiency. Labs and Teams: Project descriptions indicate leadership in autonomous systems teams and energy management research groups, though specific laboratory affiliations are not detailed in the source text.

• Software Engineering
• Parallel Algorithms
• Computer Networks
• +7 more

Prof. Hasan BULUT is a full-time faculty member at Ege University's Faculty of Computer and Information Sciences, Department of Computer Engineering. His primary research focuses on software engineering, parallel algorithms, computer networks, artificial intelligence, and algorithm design. He has contributed to fields like distributed systems, data structures, and bioinformatics through innovative algorithmic solutions. His academic work spans over two decades, with notable contributions to machine learning applications in energy forecasting, DNA sequence analysis, and cloud computing optimization. Key areas of expertise include hybrid machine translation models, real-time data clustering, and optimization techniques for computational problems. Prof. BULUT's recent publications emphasize interdisciplinary approaches, combining deep learning with traditional methods to solve challenges in healthcare informatics, financial prediction, and bioengineering. His work on network slicing techniques for 5G and beyond networks highlights cutting-edge contributions to modern communication systems. Despite an extensive publication record and collaborations within Ege University, no formal scientific awards or grant information is explicitly mentioned in the provided texts. His academic career includes supervising numerous research projects but specific student advisee details are not documented here.

Hande AlemdarView profile

Assistant Professor

• Machine Learning
• Data Science
• Big Data Analytics
• +6 more

Hande Alemdar is an Assistant Professor at the Department of Computer Engineering, Middle East Technical University, specializing in machine learning, data science, and big data analytics. She earned her BSc, MSc, and PhD in Computer Engineering from Boğaziçi University in 2004, 2009, and 2015, respectively, with her PhD thesis awarded the Bogazici University Research Fund (BAP) Best Thesis Award. PhD in Computer Engineering (2015), Boğaziçi University MSc in Computer Engineering (2009), Boğaziçi University BSc in Computer Engineering (2004), Boğaziçi University Her research focuses on applying machine learning to resource-efficient hardware, wireless sensor networks, and smart environments. She has pioneered work on ternary neural networks for FPGA-based AI, which reduce computational costs while maintaining accuracy. Her work spans diverse applications like activity recognition, fall detection, and sports analytics. Her recent publications reflect trends in deep learning for hardware efficiency, smart healthcare via ambient sensors, and network security with machine learning. These studies often integrate multi-modal sensor fusion and real-time data analysis , emphasizing deployability in resource-constrained scenarios. Scientific Awards Bogazici University BAP Best Thesis Award Hande has collaborated with Grenoble Informatics Institute and industry leaders like ST Microelectronics on energy-efficient AI. Her work has been published in journals and conferences such as Sensors, Computers & Graphics, and FPL, addressing topics from elite football performance analysis to covert channel detection in SDN. She leads research in scalable architectures for smart environments and is involved in the H2020 FET Project 'ROBOtic Replicants for Optimizing the Yield by Augmenting Living Ecosystems', demonstrating her commitment to interdisciplinary AI applications.

• Computer Science
• Artificial Intelligence
• Algorithms
• +4 more

F. Yeşim İKİKAT serves as a Researcher at the Department of Computer Engineering within the Faculty of Engineering at Turkish-German University, a position held since 2022. Her academic foundation spans computational engineering with interdisciplinary applications in security systems and semantic analysis. Her educational qualifications include: Doctorate in Computer Engineering from Istanbul Technical University Institute of Graduate Education (2019) Master's in Computer Engineering from Yildiz Technical University Institute of Science (2014-2019, with thesis) Bachelor's in Computer Engineering from Atilim University Faculty of Engineering (2007-2012) Research interests center on Artificial Intelligence, Algorithms and Computational Theory, and Information Security and Cryptology, with specialized work in Parallel Algorithms, Natural Language Processing, and Image Encryption. Her methodology combines computational modeling with cryptographic techniques to solve complex engineering and information system challenges, particularly in high-performance computing environments and secure data transformation. Publication trends reveal evolving expertise from computational mechanics (2012 thermoelasticity simulations) to security applications (2018 image encryption) and semantic analysis (2015 Wikipedia linking). This progression demonstrates consistent application of algorithmic innovation across engineering simulations, multimedia security, and knowledge representation domains. No scientific awards were documented in the source material. Advising activities and research grants are not referenced in the available information. Laboratory affiliations or research team memberships were not specified in the provided text.

Can ÖzturanView profile

Professor

• Blockchain Technologies
• Parallel Processing
• High Performance Computing
• +4 more

Can Özturan is a Professor in the Department of Computer Engineering at Bogazici University in Istanbul, Turkey. He joined the department as a faculty member in 1996 after completing his Ph.D. in Computer Science from Rensselaer Polytechnic Institute in 1995 and working as a Postdoctoral Staff Scientist at the ICASE (Institute for Computer Applications in Science), NASA Langley Research Center. His research interests span Blockchain Technologies, Parallel Processing, High Performance Computing, Graph Algorithms, Scientific Computing, Resource Management, and Grid/Cloud Computing. Over his career, his research focus has evolved from parallel processing and graph algorithms toward blockchain technologies, particularly focusing on privacy-preserving techniques, fraud detection, and performance optimization in Ethereum systems. An analysis of his recent publications (2021-2025) reveals a strong concentration on blockchain applications, with particular emphasis on privacy-preserving protocols using zero-knowledge proofs, fraud detection in transaction graphs, and performance optimization for blockchain systems. His work bridges theoretical computer science with practical blockchain implementations, often applying parallel processing techniques to blockchain challenges. Professor Özturan teaches courses in Blockchain Programming (CMPE483), Parallel Processing (CMPE478), Systems Programming (CMPE230), Graph Algorithms (CMPE528), and Compiler Design (CMPE425), demonstrating his expertise across both foundational and emerging areas of computer engineering.

• Operations Research
• Fuzzy Logic
• Modeling and Optimization
• +3 more

Assistant Professor Tusan Derya is affiliated with Başkent University in the College of Engineering , Industrial Engineering Department . Their research focuses on Operations Research Fuzzy Logic Modeling and Optimization with applications in routing problems and logistics. Their recent publications address variations of the Traveling Salesman Problem (2020-2024), Team Orienteering (2016), and Vehicle Routing (2011) using Mixed-Integer Programming and Fuzzy Logic approaches. They have contributed to Portfolio Optimization models (2024) and Autonomous Distribution Systems (2024).

Osman DarcanView profile

Associate Professor

• Programming Techniques
• Object Oriented System Development
• Simulation
• +2 more

Osman Darcan is an Associate Professor at Bogazici University in Istanbul, Turkey, with a verified institutional email osman.darcan@boun.edu.tr. His academic career spans over two decades with consistent research output in computational fields. Education Background: Undergraduate: Boğazici University, Computer Engineering Masters: Boğaziçi University, Computer Engineering Ph.D.: Boğaziçi University, Industrial Engineering His research focuses on practical applications of computational techniques across multiple domains. Darcan's work in Programming Techniques emphasizes object-oriented development frameworks and visualization tools for educational purposes. His Simulation research includes distributed systems and load balancing algorithms, while Artificial Intelligence applications target data mining for student profiling and e-commerce. The E-Learning strand features innovative tools for linear programming, geometric problem-solving, and programming education, demonstrating a strong commitment to pedagogical innovation through technology. Publication trends (2000-2012) reveal an evolution from foundational work in distributed simulation (2000-2006) toward applied data mining in education and e-commerce (2009-2012). His research consistently bridges theoretical computer science with practical educational and business applications, particularly in cluster analysis for student performance and agent-based modeling for market simulations. No scientific awards were documented in the source material. While specific advising records and grant details weren't provided, Darcan's publication pattern indicates supervision of students in data mining and simulation projects. His international conference presence (IBIMA, PICMET, World Conference on E-Learning) suggests active participation in global academic networks. The absence of lab/team mentions implies independent or small-group research operations focused on software tool development.

Belgin Ergenç BostanoğluView profile

Associate Professor

• Database Systems
• Data Mining
• Privacy-Preserving Techniques
• +3 more

Belgin Ergenç Bostanoğlu is an Associate Professor in the Computer Engineering Department at Izmir Institute of Technology (Turkey). Her research focuses on query optimization in distributed databases, association rule mining, privacy-preserving data mining, and graph-based algorithms. She leads the Dworld research laboratory and has held academic and industry roles since the 1980s. Education: B.Sc. in Computer Engineering, Middle East Technical University (1983) M.Sc. in Computer Engineering, Izmir Institute of Technology (2002) Ph.D. in Computer Engineering, Paul Sabatier University, France (2008) Research Interests: Dynamic frequent itemset mining and hiding under multiple support thresholds Subgraph mining in evolving graphs Federated query processing over linked data Privacy-preserving techniques in distributed databases Medical NLP applications (e.g., TurkMedNLI dataset) Her recent work emphasizes large-scale graph analysis, medical NLP dataset development, and adaptive join operators for federated SPARQL queries. She has contributed to over 30 peer-reviewed publications and led projects like the TÜBİTAK ARDEB 3501 platform for dynamic frequent itemset mining. Teaching: Courses include Advanced Database Management Systems, Knowledge Discovery, and Privacy-Preserving Data Mining. Labs & Projects: Manages Dworld lab and coordinates projects such as 'Turkish Medical NLP Model Development' (BAP-funded) and the Behavioral Next Generation Wireless Networks COST Action.

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

Ethem Alpaydin is a Professor of Computer Science at Özyeğin University in Istanbul, Turkey. He is a prominent researcher in machine learning and artificial intelligence, with affiliations including membership in The Science Academy, Turkey, and Academia Europaea. He also holds a fellowship with the Asia-Pacific Artificial Intelligence Association. His research focuses on foundational aspects of machine learning, including statistical methods, neural networks, and deep learning. He has contributed to areas such as generative adversarial networks (GANs), decision pathways in neural networks, and distributed decision trees. His work bridges theoretical advancements with practical applications in domains like natural language processing and computer vision. Alpaydin has authored influential textbooks such as Introduction to Machine Learning and Maschinelles Lernen , which are widely used in academic curricula. His publications emphasize model interpretability, regularization techniques, and cross-lingual learning for languages like Turkish. Awards include recognition from leading scientific institutions for his contributions to AI and data science.

• Real-Time Systems
• Multiprocessor Scheduling
• Real-Time Operating Systems
• +4 more

Cláudio Maia is a Lecturer and Integrated PhD Researcher at the Faculty of Engineering of the University of Porto, Portugal. He holds a B.Sc. and M.Sc. in Computer Engineering from the Polytechnic Institute of Porto and a Ph.D. in Electrical and Computer Engineering from the University of Porto (2018). His research focuses on real-time systems, including real-time operating systems, hypervisors, multiprocessor architectures, and scheduling theory. He has contributed to advancements in task scheduling for multiprocessor platforms, resource contention analysis, and WCRT (Worst-Case Response Time) methodologies. His work has been published in venues such as RTCSA, RTNS, and DATE, and includes a Best Paper award at ICESS 2021. He is affiliated with the CISTER Research Centre, where he collaborates on projects involving embedded systems, real-time critical CPS, and automotive systems integration. His recent research explores memory and bus contention analysis in real-time task models, with applications to multiprocessor systems and industrial automation. Education: Bachelor’s Degree (B.Sc.) in Computer Engineering, School of Engineering, Polytechnic Institute of Porto Master’s Degree (M.Sc.) in Computer Engineering, School of Engineering, Polytechnic Institute of Porto Ph.D. in Electrical and Computer Engineering, University of Porto (2018) Research Interests: Real-Time Scheduling (WCRT Analysis, Partitioned/Global Scheduling) Multiprocessor Architectures and Resource Contention Real-Time Operating Systems and Hypervisors Parallel Task Models (Fork-Join, 3-Phase Tasks) Embedded Systems and Cyber-Physical Systems (CPS) Awards: Best Paper Award at ICESS 2021 for 'Bus-Contention Aware WCRT Analysis' Key Contributions: Developed contention-aware scheduling models for real-time multiprocessor systems Advanced WCRT analysis techniques for 3-Phase Task Models Contributed to frameworks for automotive systems integration and CPS emulation Labs/Teams: Active member of the CISTER Research Centre, collaborating on industrial and academic projects in real-time systems and embedded computing.

Ahmet DuranView profile

Professor

• Mathematics
• Applied Mathematics
• Wind Energy
• +3 more

Professor Ahmet Duran at Istanbul Technical University's Department of Mathematics specializes in applied mathematics with interdisciplinary applications in renewable energy systems, financial mathematics, and computational modeling. His research focuses on differential equations, numerical methods, and optimization techniques. Current projects involve EU collaborations on supercomputing (GPGPU for bio-fluid applications) and sparse direct solvers for linear equations. Recent publications emphasize wind/solar energy prediction, climate resilience, and financial portfolio optimization via principal component analysis. Technical expertise spans spectral analysis, fuzzy logic modeling, and high-performance computing using frameworks like SuperLU.

Baha ZaferView profile

Associate Professor

• Aeroacoustics
• Computational Fluid Dynamics
• Hydroacoustics
• +3 more

Baha Zafer is an Associate Professor in the Department of Aeronautical Engineering at Istanbul Technical University. His research primarily focuses on advanced computational methods in fluid dynamics and aeroacoustics, with applications in aerospace, marine, and energy systems. Research interests span aeroacoustics, hydroacoustics, computational fluid dynamics (CFD), and machine learning applications in flow optimization. Key areas include transonic/supersonic cavity flows, wind turbine acoustics, supercavitation phenomena, and generative adversarial networks for flow field prediction. Recent publications (2019–2025) show strong trends in applying open-source CFD tools and machine learning to aeroacoustic problems. Dominant themes include unsteady transonic flows (38% of recent work), optimization via ML (25%), and hydroacoustics (20%), reflecting a shift toward AI-enhanced simulation techniques since 2023. Currently advises 5 graduate theses. No major scientific awards are documented.