Find Academic Supervisors

Yusuf Sinan AkgulView profile

Associate Professor

• Computer Vision
• Medical Image Processing
• Machine Learning
• +7 more

Yusuf Sinan Akgul is an Associate Professor at the Department of Computer Engineering, Gebze Institute of Technology (GIT), Turkey. He has been affiliated with GIT since 2005 and is part of the GIT Vision Lab. His research focuses on computer vision, medical imaging, and machine learning. He holds a Ph.D. from the University of Delaware (2000), where he also earned his M.S. (1995) and B.S. (1992) in computer engineering. His work includes contributions to image segmentation, stereo vision, and 3D structure recovery, with over 30 peer-reviewed publications and multiple patents. Education Ph.D. 2000, University of Delaware, USA M.S. 1995, University of Delaware, USA B.S. 1992, Middle East Technical University, Turkey Research Interests Akgul’s research spans computer vision fundamentals and applications, including medical image analysis, image segmentation techniques, 3D reconstruction from stereo data, and real-time surveillance systems. His work integrates machine learning and statistical methods to address challenges in biomedical engineering and video analysis. Key contributions include modular frameworks for anatomical contour extraction and adaptive focus measurement algorithms. Scientific Awards Frank Pehrson Graduate Student Achievement Award (1999) TUBITAK Career Grant (2006) Advising & Grants He has supervised 3 Ph.D. and 2 M.S. theses. Current funded projects include developing X-ray baggage inspection systems and operator-performance-tuned surveillance systems. Past grants include projects on 3D structure recovery using dual meshes. Labs & Teams He leads the GIT Vision Lab, focusing on interdisciplinary computer vision research with applications in healthcare and surveillance.

• RF Power Amplifier Design
• Control Systems
• MEMS-IMU Systems
• +5 more

Murat Üçüncü is an Associate Professor in the Department of Electrical and Electronics Engineering at Başkent University . He holds a PhD (1989), MSc (1985), and BSc (1983) from Boğaziçi University, and an additional BSc from Kara Harp Okulu (1980). His academic career spans over 35 years, with a focus on RF systems, control theory, and defense technologies. PhD, Boğaziçi University (1989) MSc, Boğaziçi University (1985) BSc, Boğaziçi University (1983) BSc, Kara Harp Okulu (1980) His research interests include RF power amplifier design, MEMS-IMU systems, underwater communication, and graph signal processing for automotive RADAR. Recent work emphasizes adaptive Kalman filtering, avionics network simulations, and autonomous systems for UAVs. Key article trends show expertise in RF circuit optimization , Kalman filter adaptation , and graph-based classification algorithms . No scientific awards are mentioned in the provided data. Advised 21+ students in areas spanning control systems, avionics, and defense technologies Led projects on shaped charges, underwater communication systems, and avionics networks

• Stochastics
• Probability theory
• Stochastic processes
• +7 more

Lasse Leskelä is an Associate Professor at the Department of Mathematics and Systems Analysis at Aalto University. His research focuses on stochastics, particularly statistical network models, random graphs, and stochastic processes acting on networks. He aims to derive mathematical laws for predicting macroscopic behavior in large random systems and improving statistical learning algorithms for high-dimensional data analysis. Probability theory Stochastic processes Random graphs Statistical network models Queueing Theory Applied probability Leskelä's work spans theoretical and applied domains, with applications in information networks, social networks, biological systems, and financial modeling. His research group actively explores models like random intersection graphs, stochastic block models, and graphons to understand complex systems. Leskelä's recent publications in journals such as the IEEE Transactions on Network Science and Engineering and PLoS Computational Biology highlight his contributions to community detection, hypergraph connectivity, and epidemic modeling. His work bridges mathematical theory with practical applications in data science and network analysis. Varma-Sampo MSc thesis prize , Finnish Mathematical Society McKinsey Prize for the best MSc degree completed in 1999 at the Helsinki University of Technology Leskelä has collaborated with leading researchers across disciplines. His research includes grants from Aalto University and international institutions, focusing on advancing stochastic modeling and data analysis techniques.

Fahrettin ÇakırView profile

Assistant Professor

• Managerial Sciences
• Operations Research
• Business Analytics
• +3 more

Fahrettin Çakır is an Assistant Professor at Boğaziçi University , where he teaches courses in management and operations research. His academic background includes a double undergraduate degree in Economics and Mathematics from Boğaziçi University, followed by a Master's and Ph.D. in Economics and Business Administration from The University of Iowa. MIS 113 - Principles of Management MIS 128 - Managerial Communication His research focuses on Managerial Sciences , Operations Research , and Business Analytics , with a particular emphasis on predictive modeling in the Orienteering Problem with Stochastic Profits and routing optimization. He has also explored Islamic Economics through studies on interest-free rotating savings and credit associations (ROSCA) in Turkey. Recent publications highlight his work on AI applications in corporate social responsibility analysis, stochastic routing strategies, and simulation-based model evaluation. These studies span interdisciplinary domains such as organizational behavior, environmental sustainability in airport operations, and computational finance.

• Signal Processing
• Biomedical Signal and Image Processing
• Artificial Intelligence Applications
• +5 more

Prof. Dr. Aydın Akan is a Professor at the Department of Electrical and Electronics Engineering, Izmir University of Economics. He has held academic and leadership roles at Istanbul University (1996-2017), Izmir Katip Celebi University (2017-2020), serving as Department Chair, Dean of School of Engineering and Architecture, and Director of Biomedical Test and Calibration R&D Center. B.Sc. in Electronics Engineering (1988), Uludag University M.Sc. in Electronics and Telecommunications (1991), Technical University of Istanbul Ph.D. in Electrical Engineering (1996), University of Pittsburgh His research focuses on nonstationary signal processing , time-frequency analysis , and machine learning applications to biomedical engineering and wireless communications. Recent publications emphasize EEG-based diagnostics for neurological disorders, deep learning for biomedical signal classification, and synchronization analysis in brain activity. Article trends highlight interdisciplinary work bridging neuroscience , electrical engineering , and AI , with methodologies like time-frequency transforms, CNNs, and signal decomposition applied to epilepsy, ADHD, and Alzheimer's detection. Scientific honors include: TÜBİTAK scholarship (2004) Senior Member of IEEE Signal Processing and Engineering in Medicine & Biology Societies EURASIP Biomedical Image and Signal Analytics Committee member He has participated in numerous TÜBİTAK and university-funded research projects as principal investigator or researcher, contributed to books/journals, and serves on editorial boards including Elsevier's Digital Signal Processing Journal.

• Localization
• Wireless Sensor Networks
• Algorithms
• +3 more

Hüseyin Akcan is a Professor in the Department of Software Engineering at Izmir University of Economics, Turkey, specializing in algorithmic solutions for wireless sensor networks with emphasis on localization and calibration systems. His academic credentials include: Ph.D. in Computer Science from NYU Tandon School of Engineering (2008) M.S. in Computer Science from NYU Tandon School of Engineering (2005) B.S. in Control and Computer Engineering from Istanbul Technical University (1999) Research focuses on computationally complex problems in sensor networks, particularly energy-efficient localization techniques without GPS infrastructure, calibration algorithms for embedded systems, and NP-hard problem resolution through genetic and approximation methods. His work bridges theoretical computer science with practical network applications in distributed systems. Publication trends (2010-2022) reveal consistent development in wireless localization methodologies, evolving from foundational GPS-free techniques to advanced mobile beacon systems and genetic algorithm implementations, with recent expansion into virtual reality applications for body anthropomorphism studies.

• Control Theory and Applications
• Artificial Intelligence
• Machine Learning

Mert Can is a Research Assistant at Istanbul Technical University in the Control and Automation Engineering department. His work spans interdisciplinary fields combining control theory with artificial intelligence. Doctorate in Control and Automation Engineering (2020) Master's in Control and Automation Engineering (2017) Bachelor's in Control and Automation Engineering (2012) His research focuses on: Optimizing variable-order fractional derivatives for adaptive control systems Applying AI to friction damper distribution in seismic protection Developing robust loss functions using fractional calculus Recent publications demonstrate expertise in quadcopter position control and graph neural networks for neuroimaging data fusion. Key trends include: Integration of AI with traditional control systems Advancements in fractional calculus applications Optimization methods for structural engineering No scientific awards are currently recorded.

Samet GÜNERView profile

Professor

• Operations Research
• Supply Chain Management
• Airport Efficiency Analysis
• +5 more

Prof. Dr. Samet GÜNER is a faculty member at the Department of Business Administration, Faculty of Business Administration, Sakarya University. His research focuses on transportation efficiency analysis, supply chain management, and multi-criteria decision-making frameworks. He specializes in applying data envelopment analysis (DEA), network science, and social media analytics to evaluate operational efficiencies in airports, seaports, and public transportation systems. Key research areas include airport network centrality, sustainable logistics, and policy implications derived from social media data. His work bridges complex systems analysis with practical applications in infrastructure planning and green supply chains. Recent studies examine pandemic impacts on aviation productivity and barriers to sustainable mobility initiatives. Prof. GÜNER has published extensively on transportation systems optimization, with notable contributions to DEA methodology innovations and global airport benchmarking. His articles integrate quantitative models like system dynamics and fuzzy logic to address sector-specific challenges in logistics, urban planning, and crisis management. He holds a professorship position without part-time designation and can be contacted via sguner@sakarya.edu.tr. His academic contributions span over two decades with a focus on operational efficiency in public infrastructure sectors.

• Signal Processing
• Image Analysis
• Medical Diagnostics
• +5 more

Burak Acar is a Full-Time Professor of Electrical and Electronics Engineering at Bogazici University, Turkey, and director of the VAV Lab. He holds affiliations with the Bogazici University Center for Life Sciences and Koç University’s KUIS AI Lab. His academic journey includes a BS, MS, and PhD in Electrical and Electronics Engineering from Bilkent University (1994–2000), followed by postdoctoral research at Stanford University’s Medical School (2000–2003). He has served as a Mercator Visiting Professor at TU Munich (2012–2013). His research focuses on signal/image processing for medical and industrial diagnostics, network modeling, and machine learning applications. Key interests include Alzheimer’s disease diagnostics, medical imaging analysis, and predictive maintenance systems. He leads interdisciplinary projects in computational neuroscience and AI-driven medical diagnostics. Education: PhD, Electrical and Electronics Engineering, Bilkent University (2000) MS, Electrical and Electronics Engineering, Bilkent University (1996) BS, Electrical and Electronics Engineering, Bilkent University (1994) Awards: Excellence in Research Award, Bogazici University Foundation (2006) Young Researcher Award, Turkish Academy of Sciences (2008) His work spans over 2000 citations and includes 7 US patents. Current research emphasizes brain connectivity analysis for Alzheimer’s disease, AI-driven medical imaging tools, and industrial diagnostics through machine learning. He collaborates internationally and directs the VAV Lab, which develops cutting-edge algorithms for medical and engineering challenges.

Meral TosunView profile

Professor

• Singularities in Algebraic Geometry
• Resolution of Singularities
• Topology of Singularities
• +4 more

Meral Tosun is a Professor in the Department of Mathematics at Galatasaray University, Istanbul, Turkey. She holds a DEA in Mathematics from Université Paris VII (1994) and a Ph.D. in Mathematics from Université d'Aix-Marseille I (1998), advised by Prof. Lê Dũng Trang. Her research focuses on singularities in algebraic geometry, including resolution and deformations of singularities, topology of singularities, classification of singularities, Lie algebras related to surface singularities, toric geometry, and tropical geometry. Education: DEA in Mathematics, Université Paris VII, Paris, France (1994) Ph.D. in Mathematics, Université d'Aix-Marseille I, Marseille, France (1998) Research Interests: Her work explores the interplay between algebraic geometry and singularity theory, with emphasis on resolution algorithms, topological properties of singularities, and their connections to Lie algebras and toric geometry. Notable contributions include studies on rational triple points, non-isolated singularities, and applications of toric methods in surface singularities. Recent Research Trends: Recent articles highlight advancements in minimal embedded resolution techniques (e.g., toric methods for rational triple points), exploration of Lojasiewicz exponents in surfaces, and the role of Lie algebras in singularity classification. She has also contributed to geometric invariant theory and quantum key distribution in turbulence channels. Awards & Grants: No specific awards listed, but her extensive postdoctoral fellowships (ICTP, UNAM) and supervisory roles indicate sustained academic recognition. She has advised 9 graduate students and mentored 6 post-doctoral researchers at institutions including Galatasaray University and Gebze Technical University. Labs & Collaborations: Active in organizing workshops and schools at Galatasaray University, contributing to Turkish mathematical communities like the Nesin Mathematics Village and Istanbul Mathematical Sciences Center (IMBM).

Ayşe Tosun KühnView profile

Associate Professor

• Software Engineering
• Software Quality
• Defect Prediction
• +9 more

Ayşe Tosun Kühn is an Associate Professor in the Department of Computer Engineering at Istanbul Technical University (ITU), where she also serves in administrative roles such as Deputy Dean and Management Board Member of the ITU Artificial Intelligence and Data Science Application and Research Center. She earned her Ph.D. in Computer Engineering from Boğaziçi University and has held academic positions at Sabancı University and the University of Oulu. Her research lies at the intersection of software engineering, empirical methods, and data science, with a focus on software quality, defect prediction, technical debt, vulnerability analysis, and test-driven development. She leads numerous funded research projects, including those supported by TÜBİTAK and industry collaborations, applying machine learning and reinforcement learning to software engineering challenges. Her recent publications reflect a strong trend in applying advanced machine learning techniques—particularly deep learning and reinforcement learning—to problems in software analytics, developer behavior modeling, and delivery optimization. She has made significant contributions to empirical studies on test-driven development, defect prediction models, and vulnerability detection in code. Her work is frequently published in high-impact journals such as IEEE Transactions on Software Engineering, Empirical Software Engineering, and Journal of Systems and Software. She has served as a guest editor and editorial board member for the Turkish Journal of Electrical Engineering and Computer Sciences , and has contributed book chapters on data science in software engineering. Her research has been cited over 1,700 times, with an h-index of 23. Scientific Awards: None explicitly mentioned. She advises several graduate students and has collaborated extensively with researchers in Turkey and internationally. She has also contributed to industry applications through projects on software measurement, defect prediction, and AI-based analytics. She is actively involved in organizing and contributing to major software engineering conferences and workshops. She is a key member of ITU’s AI and Data Science initiatives, contributing to both academic research and practical implementations in software engineering.

TOLGA ERENView profile

Professor

• Cooperative Localization
• Formation Control
• Wireless Sensor Networks
• +3 more

Professor Tolga Eren serves as a faculty member in the Department of Electrical and Electronic Engineering at Kirikkale University's Faculty of Engineering and Natural Sciences. Holding a PhD from Yale University with postdoctoral training at Columbia University, he previously held a visiting professorship at KTH Royal Institute of Technology and earned his BSc from Bilkent University under full scholarship. His educational trajectory includes: BSc in Electrical and Electronics Engineering, Bilkent University (full scholarship) MSc from University of Massachusetts and Yale University PhD from Yale University Postdoctoral research at Columbia University Eren's research centers on networked systems with dual focus on cooperative localization in wireless sensor networks and formation control for multi-robot systems. He pioneers applications of optimization algorithms like Particle Swarm and Bat Algorithm for positioning challenges while advancing rigidity theory for network stability. His work bridges theoretical frameworks with practical implementations in constrained environments. Analysis of his 2019-2021 publications reveals three dominant trends: (1) Hybrid optimization approaches for wireless sensor network localization using swarm intelligence variants, (2) Rigidity-theoretic foundations for formation control under input constraints, and (3) Geometric methods for robot path smoothing and shape maintenance. These intersect at the nexus of graph theory, control systems, and distributed computing. Professor Eren has advised at least one graduate student, Gülçin AKTAŞ, who completed her departmental thesis in 2014. While no specific grants are documented in the available records, his research output demonstrates sustained investigation into networked system fundamentals through institutional support at Kirikkale University.

Numan CELEBİView profile

Professor

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

Prof. Dr. Numan CELEBİ serves as a Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Information Systems Engineering, where he has held academic positions since 2007. His career progression includes promotion to Associate Professor in 2013 and subsequent advancement to full Professor. His educational foundation comprises a Doctorate in Industrial Engineering from Sakarya University (1998-2004) with thesis Inductive-rough clustering approach to part family generation , a Master's in Electrical and Electronics Engineering (1995-1997) with thesis Development of computer program for the implementation of Adapazari medium voltage distribution network (SCADA) system , and a Licence from Istanbul Technical University's Electrical-Electronic Engineering program (1985-1989). CELEBİ's research spans Artificial Intelligence , Machine Learning , and Computer Vision , with significant contributions to optimization algorithms (Polar Bear Algorithm, Tug of War Optimization), intelligent transportation systems (traffic congestion detection, vehicle rerouting), and computer vision applications (object tracking, saliency detection, UAV-based plant recognition). His methodology frequently integrates Rough Set Theory and fuzzy systems for data analysis and decision support. Analysis of his 15 most recent publications (2007-2023) reveals a clear research trajectory toward applying metaheuristic optimization and deep learning to real-world problems. His work demonstrates increasing focus on transportation systems (40% of recent publications), agricultural technology via UAVs (15%), and novel optimization frameworks (25%), with consistent methodological emphasis on hybrid algorithm design and real-time implementation. As an educator, CELEBİ supervises graduate research through courses like ENF 524 Project and teaches specialized subjects including Meta Heuristic Optimization Methods , Intelligent Techniques in Data Analysis , and Data Science across undergraduate and graduate programs. His teaching portfolio spans discrete mathematics, computer networks, and cloud computing, reflecting interdisciplinary expertise.

• Artificial Intelligence
• Robotics
• Reinforcement Learning
• +3 more

Ozgur S. Oguz is an Assistant Professor in the Department of Computer Engineering at Bilkent University, leading the Learning for Intelligent Robotic Agents (LiRA) Lab. His research focuses on developing algorithms for autonomous agents, emphasizing learning, reasoning, and planning capabilities in robotics and decision-making domains. Prior to joining Bilkent, he was a postdoctoral researcher at the Max Planck Institute for Intelligent Systems and Stuttgart University, and earned his PhD from TU Munich in Human-Robot Interaction (HRI). He holds degrees from UBC and Koç University. His research interests span AI, robotics, reinforcement learning, and robotic manipulation planning. Notable contributions include work on curriculum-based reinforcement learning, safe learning frameworks for dynamical systems, and hybrid planning algorithms for sequential manipulation tasks. He actively teaches courses such as Learning for Robotics (CS 449/549) and Artificial Intelligence (CS 461). Recent publications highlight advancements in diffusion-based curriculum learning, corrected experience replay methods, and neural field representations for articulated object manipulation. His work frequently appears in top venues like NeurIPS, ICRA, and IROS. He mentors graduate and undergraduate students in AI and robotics, with current opportunities for postdoctoral researchers. Key collaborations include projects with the Cluster of Excellence IntCDC and the LiRA Lab’s focus on interdisciplinary robotics research.

Dilek Günneç DanışView profile

Associate Professor

• Combinatorial optimization
• Network optimization models
• Social network analysis
• +7 more

Dilek Günneç Danış is an Associate Professor in the Industrial Engineering Department at Özyeğin University, Turkey. Her academic work spans network optimization, social network analysis, and humanitarian logistics with applications in disaster management, marketing, and public health. Ph.D. in Operations Management/Management Science, University of Maryland (2012) M.Sc. in Industrial Engineering, Koç University (2007) B.Sc. in Mathematics with Minor in Operations Research, Middle East Technical University (2005) Research Interests : Combinatorial optimization and complex systems Network modeling for information propagation New product development under social influences Humanitarian logistics in refugee crises Disaster mitigation and infrastructure resilience Scientific Contributions : Developed agent-based models for refugee migration paths Created capacitated mobile facility location frameworks Advanced influence maximization algorithms for social networks Optimized disaster response logistics systems Scientific Awards : Best Poster Award (Business Analytics Workshop, 2017) Advised team: Third Place INFORMS Student Competition (2020)