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Hatice ÇOBANView profile

Assistant Professor

• Geometry
• Topology
• Mathematical Machine Learning
• +5 more

Dr. Hatice ÇOBAN is an Assistant Professor at Doğuş University , Faculty of Engineering, Department of Software Engineering, with expertise in geometry, topology, and mathematical machine learning. She has held academic positions at Altınbaş University (2022), Atılım University (2022–2023), and Istanbul Bilgi University (2021), and has worked part-time at various Turkish universities since 2021. Her research focuses on geometric topology, toric geometry, and real projective structures on manifolds.

• High Performance Computing (HPC)
• Data Locality
• GPU Computing
• +7 more

Dr. Didem Unat is an Associate Professor at Koç University, College of Engineering, Department of Computer Engineering . Her research focuses on High Performance Computing (HPC) , GPU Computing , and Compiler Design , with particular emphasis on data locality optimization, multi-GPU communication, and adaptive mesh refinement. She leads the Parallel and Multicore Computing Lab , driving innovations in exascale co-design and heterogeneous system optimization. ACM SIGHPC Emerging Woman Leader in Technical Computing Award (2021) ERC Starting Grant (1.5M EUR) for the SparCity Project (2025) EuroHPC Grant for Extreme Scale Technologies and Applications (2025) 2025 BAGEP Award (Science Academy) Her work bridges Computer Architecture and Machine Learning , addressing challenges in data locality , multi-GPU systems , and performance portability . Recent publications highlight trends in sparse tensor optimization , asynchronous AMR execution , and compiler support for heterogeneous memory . She has developed tools like ComScribe for intra-node GPU communication analysis and ReuseTracker for multicore reuse distance analysis. Dr. Unat’s research is supported by grants from ERC and EuroHPC , reflecting her leadership in exascale technologies and GPU-centric systems . She contributes to the evolution of tiling abstractions , dynamic LLM training , and lightweight communication detection for modern architectures.

• Web Search Engines
• Text-to-SQL Systems
• Online Social Network Analysis
• +5 more

Özgür Ulusoy is a Professor of Computer Engineering at Bilkent University, Turkey. He has held academic positions since 1993, including Assistant Professor (1993–2003) and Associate Professor (1998–2003) before becoming a full Professor in 2003. He earned his Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in 1992, following an M.S. (1988) and B.S. (1986) in Computer Engineering from Bilkent University and Middle East Technical University, respectively. His research focuses on web search engines, text-to-SQL systems, social network analysis, multimedia databases, and wireless/mobile systems. Notable projects include developing domain-specific web portals, optimizing query result caching, and exploring semantic relationships for search engine efficiency. He has directed over 20 sponsored projects funded by TÜBITAK, EU, and international collaborations, involving topics like data mining in mobile networks and real-time database scheduling. Ulusoy’s work bridges theoretical contributions with practical implementations, including prototyping video database systems and educational search engines. His research often emphasizes scalability, efficiency, and user-centric design. He has advised graduate students such as Arif Usta and Akifhan Karakayalı. His team’s contributions span algorithm development, system prototyping, and interdisciplinary applications in multimedia, social networks, and cloud computing. Key grants include projects on information retrieval paradigms in SQL translation (TÜBITAK, 2019–2021), refreshment strategies for web search caching (TÜBITAK, 2010–2011), and semantic relationships in search engines (TÜBITAK, 2008–2010). His recent work addresses challenges in IoT sensor networks, cloud resource scheduling, and mitigating misinformation in online platforms.

• Hybrid Control Systems
• Hierarchical Control Systems
• Distributed Consensus-Based Control
• +3 more

Jörg Raisch is a Professor of Control Systems at the Technische Universität Berlin since March 2006. He previously held positions at Otto-von-Guericke University Magdeburg and the Max Planck Institute for Dynamics of Complex Technical Systems. His research focuses on hybrid and hierarchical control systems , distributed consensus-based control , and control of time-dependent event-discrete systems using tropical algebras. Alma Mater: University of Stuttgart (Technical Cybernetics), UMIST Manchester (Control Systems) Postdoctoral work: University of Toronto (Systems Control Group) His work spans applications in process technology , medical systems , and energy technology . Recent publications emphasize max-plus algebra , P-time event graphs , and over-the-air consensus in clustered networks. He has served on editorial boards of journals like Automatica and Discrete Event Dynamic Systems , and led the IFAC Technical Committee TC1.3 on Discrete Event and Hybrid Systems from 2017-2020. Awards: DFG fellowship for habilitation

Banu Günel KılıçView profile

Professor

• Signal Processing
• Artificial Intelligence
• Software Engineering
• +4 more

Prof. Banu Günel Kılıç is a full-time faculty member at Middle East Technical University (METU), where she holds the rank of Professor in the Graduate School of Informatics, Department of Information Systems. She has served in various academic roles since 2004, including previous appointments as Associate Professor (2014-2022) and Assistant Professor (2010-2014), and currently directs the Graduate School of Informatics. Doctorate: Queen's University of Belfast (2001-2004) Postgraduate: University of Bristol (2000-2001) Undergraduate: METU, Electrical Engineering (1995-2000) Her research focuses on signal processing, cybersecurity, and machine learning, with particular emphasis on intrusion detection systems in software-defined networks, acoustic gunshot localization, auditory attention modeling, and security visualization infrastructures. She has supervised 14+ graduate theses, including work on microservice call graphs and institutional investor networks. Recent publications demonstrate strong interdisciplinary work in machine learning and cybersecurity , with specific applications in intrusion detection, cloud resource allocation, and acoustic signal processing. She has contributed to over 25 peer-reviewed publications and holds two standard patents in acoustic source separation technology. Prof. Kılıç has participated in multiple European Union funded projects including EuroCC2 (2023-2026), EUMaster4HPC (2022-2025), and prior FP7 projects like IRIS and DIOMEDES. Her work bridges traditional acoustic signal processing with modern cybersecurity applications in enterprise environments.

Feza BuzlucaView profile

Associate Professor

• Computer Software
• Computer and Communication Networks
• Object-Oriented Modeling
• +4 more

Assoc. Prof. Feza Buzluca is affiliated with Istanbul Technical University as an Associate Professor in the Faculty of Computer and Informatics, Department of Computer Engineering . His academic career spans over two decades at ITU, including administrative roles like Vice Dean (2015-2018) and Faculty Board Membership (2016-). PhD in Control and Computer Engineering from Istanbul Technical University Fields: Computer Software, Communication Networks, Object-Oriented Modeling, Microservices His research focuses on software quality assessment , particularly for microservices architectures using fuzzy logic and code metrics. He explores object-oriented systems through machine learning for defect prediction, module extraction, and design pattern analysis. Recent work includes embedded software testing prioritization and cognitive radio network optimization . Key projects: Personal website and ORCID profile highlight 41 research outputs (2001-2024) and 1 project on microservices-based e-payment systems . Collaborations span IEEE/ACM conferences and journals like Journal of Systems and Software . Contact: Office 4318, Ayazaga Campus, 34000 Istanbul | buzluca@itu.edu.tr

Emine Ulku SaritasView profile

Associate Professor

• Biomedical Imaging
• Magnetic Resonance Imaging (MRI)
• Magnetic Particle Imaging (MPI)
• +3 more

Emine Ulku Saritas is an Associate Professor at Bilkent University, affiliated with the Department of Electrical and Electronics Engineering and the National Magnetic Resonance Research Center (UMRAM) . Her work bridges biomedical engineering, medical imaging, and advanced instrumentation. Research Interests: Dr. Saritas specializes in Magnetic Resonance Imaging (MRI) and Magnetic Particle Imaging (MPI) , focusing on novel contrast mechanisms , high-resolution imaging , and artificial intelligence applications for diagnostic imaging. Her research spans hardware design, algorithm development, and biomedical translation. Publication Trends: Recent work emphasizes deep learning for artifact correction , microfluidic nanoparticle analysis , hybrid imaging systems , and physics-informed models for medical imaging. Collaborative efforts include multimodal imaging and nano-platform development for photothermia and diagnostics. Laboratory & Collaborations: She contributes to the National Magnetic Resonance Research Center (UMRAM) and the Aysel Sabuncu Brain Research Center, advancing brain imaging technologies and magnetic fluid hyperthermia .

• Software Testing
• Model-Based Testing
• Software Product Lines
• +7 more

Assoc. Prof. Tugkan Tuglular is affiliated with the Department of Computer Engineering at Izmir Institute of Technology, leading the Safety, Security and Reliability of Software Systems (S2RS2) Laboratory. His research focuses on software testing methodologies, model-based systems, and security applications across software product lines. His work spans formal methods for testing (e.g., event sequence graphs, feature modeling), blockchain-enhanced data sharing, and empirical software engineering. He has extensively studied automated test case generation, change impact analysis, and robustness measurement using Bayesian networks. Notable contributions include domain-specific languages for business applications and frameworks for incremental testing in evolving systems. Recent efforts explore federated platforms for source code quality analysis and AI-driven methods for completing graphical software models. His research integrates theoretical foundations with practical tools, emphasizing security and reliability across diverse software domains. Awards: No specific awards listed. Advising/Grants: No student advising records or grant details provided in the text. His lab (S2RS2) focuses on advancing software safety and security through rigorous testing and modeling approaches. Labs/Teams: Leads the S2RS2 Lab, which investigates software systems' reliability through advanced testing techniques and formal modeling.

Onur DemirörsView profile

Professor

• Software Engineering
• Software Process Improvement
• Business Process Management
• +4 more

Onur Demirörs is a Professor and Chair of the Computer Engineering Department at Izmir Institute of Technology. His academic journey includes a B.Sc. from Middle East Technical University (1987), two M.Sc.s (Ege University, 1990; Southern Methodist University, 1993), and a Ph.D. from Southern Methodist University (1995). He has held academic positions at institutions like Dokuz Eylül University and Middle East Technical University before joining Izmir Institute of Technology in 2017. His research focuses on software process improvement , business process management , software quality , and microservices architecture . Notable projects include developing the BIM-CAREM model for construction industry process assessment and leading a TÜBİTAK-funded project on microservice-based software size measurement. Recent publications emphasize agile methodologies , microservices , and software measurement . His work bridges academic research with industry practice, such as exploring event-driven systems and effort estimation techniques. He teaches courses like Software Engineering and Microservice-Based Systems Analysis . Key contributions include advancing process modeling frameworks (e.g., Plural ), tool development for functional size estimation ( EFES ), and integrating ontologies with business processes ( PROMPTUM ). His research often addresses challenges in software lifecycle management, process automation, and cross-domain collaboration.

Michal ValkoView profile

Researcher

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

Roles & Affiliations: Michal Valko is the Chief Models Officer at a stealth startup, a tenured researcher at Inria (Inria Lille - Nord Europe), and a lecturer in the MVA Master program at École Normale Supérieure Paris-Saclay. He previously held roles including Principal Llama Engineer at Meta and Senior Staff Research Scientist at Google DeepMind. Education: Ph.D. in Machine Learning from the University of Pittsburgh (2011), Habilitation à Diriger des Recherches (HdR) from École Normale Supérieure Paris-Saclay (2016). Research Interests: Michal focuses on minimizing human supervision in AI systems, including deep reinforcement learning, bandit algorithms, self-supervised learning, and large language models (LLMs). His work emphasizes scalable test-time inference, fine-tuning, and alignment of LLMs. He also explores theoretical foundations of reinforcement learning and representation learning. Awards: Recipient of the Outstanding Paper Award at ICML 2023, Inria's Prime d'Excellence Scientifique (2014–2017 and 2018–2021), Homer Warner Best Paper Award (2010), and Google Best Paper Award (2010). Advising & Grants: Advised over 20 PhD and postdoctoral students, including notable alumni like Daniele Calandriello and Jean Tarbouriech. His research has been supported by grants from ANR (Extra-Learn, BOLD), Intel, and collaborative projects like EduBand with Carnegie Mellon. Labs & Teams: Co-founder of the SequeL team at Inria and a key contributor to the DeepMind Paris and Meta GenAI research groups. Active in organizing conferences like ICML, NeurIPS, and workshops on Graphs in Machine Learning.

Lale AkarunView profile

Professor

• Biometrics
• 3-D Face Recognition
• Hand Vein Recognition
• +8 more

Lale Akarun is Professor of Computer Engineering at Boğaziçi University, Istanbul, where she also serves as Director of the TETAM research center. She leads the Media Laboratory (MEDIALAB) and the Perceptual Intelligence Laboratory (PILAB), focusing on biometrics, sign-language recognition, computer vision and image processing. Research Interests: Biometrics: 3-D Face & Hand-vein Recognition Gesture & Sign-Language Recognition for HCI Computer Vision, Image Processing & Graphics Her recent work (2023-2025) targets robust sign-language translation via self-supervised learning, multi-cue skeleton fusion, cross-dataset transfer and attention modeling, while also contributing new benchmarks for 3-D object reconstruction and occlusion-aware human-pose estimation. Laboratories & Teams: Media Laboratory (MEDIALAB) Perceptual Intelligence Laboratory (PILAB) She advises graduate researchers and has released influential datasets such as BosphorusSign22k, fostering advances in Turkish sign-language recognition and low-resource transfer learning.

• Algorithms and Data Structures
• Big Data
• High Performance Computing
• +7 more

Francesco Silvestri is an Associate Professor in Computer Engineering at the Department of Information Engineering, University of Padova. Previously, he held roles including Assistant Professor (2016-2019) and post-doctoral positions at the University of Padova and IT University of Copenhagen. He also served as a part-time lecturer at IT University of Copenhagen (2013-2014) and as a visiting scholar at the University of Texas at Austin (2006-2007). He earned his Ph.D. in Computer Engineering from the University of Padova in 2009. His research focuses on algorithms and data structures, emphasizing big data efficiency, high performance computing, and modern architectures. Key areas include similarity search, dimensionality reduction, graph mining, and parallel algorithms. He supervises PhD students and collaborates with researchers globally. His work has been recognized with awards such as the ICDT Best Paper Award (2023) and the ACM SIGMOD Research Highlights Award (2020). Teaching includes courses like Big Data Computing and Algorithm Design at the University of Padova and IT University of Copenhagen. He has served on program committees for major conferences like Euro-Par, IPDPS, and SIGMOD. His contributions span academic publications and industrial collaborations, including work on mobility data analysis and resilient algorithms. He is affiliated with the AIDA Lab (Algorithms for Intelligent Data Analytics) and actively contributes to the academic community through editorial roles, such as being an Associated Editor of the ACM Transactions on Parallel Computing.

• Graph Neural Networks
• Recommendation Systems
• Data Mining
• +3 more

Res. Asst. Sümeyye Öztürk is affiliated with Istanbul Technical University's Faculty of Computer and Informatics, working in the Department of Computer Engineering. She is part of the Artificial Intelligence and Data Engineering unit and contributes to the Learning from Data Lab. Her research focuses on advancing recommendation systems through graph neural networks and data mining techniques. Education: PhD in Computer Engineering from Istanbul Technical University (2024). Research Interests: Sümeyye specializes in leveraging graph isomorphism networks to enhance cross-market recommendation systems. Her work addresses personalized user experience challenges by integrating machine learning and data-driven approaches. Recent contributions include a 2024 publication on optimizing recommendation systems using graph neural networks. Labs/Teams: Active member of the Learning from Data Lab (Lab-4311).

Volkan AtalayView profile

Professor

• Machine Learning
• Bioinformatics
• Data Stream Analysis
• +3 more

Volkan Atalay is a Professor in the Department of Computer Engineering at Middle East Technical University (METU), Ankara, Turkey. His research focuses on machine learning applications in bioinformatics, data stream analysis, and drug discovery. He has held leadership roles including Vice President for Research at METU (2010–2016) and chaired the Department of Computer Engineering (2007–2008). Education: Ph.D. in Computer Science from Université Paris Descartes (1993), followed by postdoctoral work at Virginia Tech (2004–2005). Research Interests: Machine learning for bioinformatics (drug-target interaction prediction, protein function annotation), data stream clustering algorithms, and deep learning applications in drug discovery. Key projects include CROssBAR (biomedical knowledge graphs) and DEEPScreen (drug-target interaction prediction tools). Recent publications (2020–2023) emphasize hybrid deep learning models, data fusion for energy forecasting, and open-source protein annotation benchmarks. Awards include the Best Poster Award at GLBIO 2017 for iBioProVis visualization work. Current grants: SmartHome Consortium (data stream analytics) and projects on biomedical relation curation. Labs/Teams: Leads the Cancer Systems Biology Laboratory and collaborates with international consortia like the CAFA challenge.

Metin SezginView profile

Professor

• Artificial Intelligence
• Computer Vision
• Human-Computer Interaction
• +3 more

Prof. Metin Sezgin is a Professor in the Department of Computer Engineering at Koç University, College of Engineering. He specializes in Artificial Intelligence, Computer Vision, and Human-Computer Interaction, with notable contributions to sketch recognition, multimodal interaction, and educational technologies. His recent work includes advancing AI-driven systems for comic analysis, human-robot engagement, and child-centered machine learning pipelines. Prof. Sezgin has been appointed as Türkiye's representative in the Global Partnership for AI (GPAI), emphasizing his leadership in AI policy and research. He leads projects like the eHRI database for human-robot interaction analysis and develops tools for classroom engagement monitoring. His research integrates computer vision with real-world applications, including tangible programming interfaces for children and affective computing systems. Grants: TÜBİTAK 1001 Grant (2023) Labs: Koç University Parallel and Multicore Computing Lab Key Areas: Sketch Recognition, Multimodal Datasets, Human-Robot Interaction, Educational Technology His publications span domains from AI ethics to technical advancements in vision systems, with a focus on bridging theoretical research and practical societal impact.