Professor Cem Evrendilek is a faculty member in the Department of Computer Engineering at Izmir University of Economics, Turkey, holding the rank of Professor with current active status. His institutional email is cem.evrendilek@ieu.edu.tr. His research spans algorithmic complexity and geometric computation, with primary focus areas including: Computational Geometry (specializing in orthogonal polygon covering problems) Wireless Sensor Network Localization (energy-efficient methods and trilateration) NP-hard Problem Analysis (proving complexity for geometric and network problems) Approximation Algorithms for combinatorial optimization Analysis of his 2008-2018 publications reveals consistent work on geometric covering problems and sensor network localization. Key trends include proving NP-completeness for orthogonal polygon covering variants, developing energy-efficient mobile beacon localization techniques, and analyzing trilateration with noisy measurements. His work frequently intersects computational geometry with practical wireless network applications, demonstrating strong theoretical foundations applied to real-world constraints. Collaborative patterns show frequent co-authorship with Hüseyin Akcan (on localization algorithms), Burkay Genç, and Brahim Hnich (on computational geometry problems).
Tülin Haşlaman is an Associate Professor at the Department of Elementary Education - Primary Education, TED University. She holds roles as a Coordinator and Vice Head of Department. Her teaching portfolio includes courses such as Instructional Technologies, Technology-Enhanced Language Learning, and Micro Teaching, reflecting her expertise in educational technology and pedagogical innovation. Her research focuses on ICT integration in education, self-regulated learning strategies, and teacher development. Notable areas of interest include the use of digital storytelling for computational thinking, infographics in supporting student autonomy, and smartphone addiction among university students. She has also studied the impact of social media platforms like Facebook on teacher training and the integration of ICT into teaching processes. Dr. Haşlaman’s work emphasizes bridging technology with educational practices, particularly in primary education contexts. Her articles highlight themes such as pre-service teacher digital competency, disabled teachers’ technology integration challenges, and peer assessment in online environments. Despite her extensive academic contributions, she has no explicitly listed awards or grants in the provided materials. Her courses over the years span foundational education topics like Learning Environments, Observation in Schools, and Research Methods, demonstrating a commitment to both theoretical and applied aspects of education. While she has not specified any affiliated labs or teams, her teaching and research activities suggest active engagement in educational technology initiatives and teacher professional development programs.
Gökhan Seçinti is an Assistant Professor in the Department of Computer Engineering at Istanbul Technical University, Faculty of Computer and Informatics. He currently serves as Vice Dean and has previously held the role of Vice Department Head. His research focuses on next-generation wireless networks, UAV communications, semantic communication, and AI-driven networking solutions. Research Interests: His work spans Unmanned Aerial Vehicles (UAVs) , Semantic and Task-Oriented Communication , Software-Defined and Cognitive Networks , 6G Communications , and AI in Networking . He develops practical testbeds for deep learning-based communication architectures and explores digital twin applications in aerial networks. Publication Trends: Recent publications emphasize decentralized UAV service deployment, beam alignment using UWB localization, TDMA scheduling for aerial swarms, and semantic flow control. These reflect a strong trend toward intelligent, adaptive, and context-aware communication systems for IoT and mobility. Best Paper Award, IEEE, 2022 Best Conference Paper, IEEE, 2016 Best Poster Paper Award, IEEE, 2015 Advising and Grants: He has supervised 4 academic works and leads multiple funded research projects, including TÜBİTAK and SRP grants on federated learning in flying networks, semantic VANETs, AI-based intrusion detection, and UAV-assisted IoT for crisis management. Labs and Teams: His work is supported by active research teams at ITU, focusing on testbed development using SDRs, digital twins, and real-world deployment of UAV networks. He collaborates internationally, including past affiliations with Northeastern University.
Attila Gursoy is a Professor at the Department of Computer Engineering, College of Engineering, Koç University. He serves as the Dean of the College of Engineering and leads research in computational biology, bioinformatics, and high-performance computing. Education : PhD in Computer Science from University of Illinois (1994), MSc from Bilkent University (1988), BSc from Middle East Technical University (1986) His research focuses on protein-protein interactions , computational structural biology , and systems pharmacology , with applications in drug repurposing and inflammatory disease mechanisms . He has pioneered structural analysis of Ras signaling and developed tools like COSBI for computational systems biology. Recent publications highlight his work on viral protein mimicry , neurodegenerative pathways , and microbiome dynamics . His team maintains datasets like PPInterface and DiPPI for structural drug discovery. 2005 : Werner-von-Siemens Excellence Award
Hüsnü Dal is a Professor at Middle East Technical University (METU) in Ankara, Turkey, specializing in computational mechanics of materials. His research bridges engineering and biomedical applications through advanced computational modeling techniques. Education: Bachelor's Degree, Middle East Technical University, 2001 Master's Degree, University of Stuttgart, 2005 PhD, Dresden University of Technology, 2011 Research Focus: Prof. Dal's work centers on computational micromechanics, multiscale and multifield problems, and materials theory. He investigates fracture in multiphysics media with applications in lithium-ion batteries and tissue mechanics, developing novel constitutive models for complex material behaviors under extreme conditions. His research integrates thermomechanical coupling, viscoplasticity, and data-driven approaches to solve engineering challenges in both synthetic polymers and biological systems. Publication Trends: Recent publications (2023-2025) reveal a dominant focus on data-driven constitutive modeling and phase-field fracture methods. His work spans rubber mechanics, polymeric foams, biological tissues, and battery materials, characterized by strong interdisciplinary connections between materials science, biomechanics, and computational engineering. Key themes include anisotropic hyperelasticity, thermo-viscoplastic fracture, and spatial property variations in additively manufactured materials.
Prof. Erdem Günay is a full Professor in the Department of Energy Systems Engineering at Istanbul Bilgi University, where he has been serving since 2013, rising through the academic ranks. He holds a Ph.D. in Chemical Engineering from Bogazici University, where he also completed his B.S. and M.S. degrees, and conducted postdoctoral research. His academic journey reflects a deep commitment to energy systems and sustainable technologies. B.S. in Chemical Engineering, Bogazici University, 2002 M.S. in Chemical Engineering, Bogazici University, 2005 Ph.D. in Chemical Engineering, Bogazici University, 2012 Postdoctoral Research Associate, Catalyst Design and Reaction Engineering Laboratory, Bogazici University, 2013 Prof. Günay’s research centers on the integration of machine learning and artificial intelligence with energy systems engineering. His work spans renewable energy (solar, wind, bioenergy), hydrogen production, CO₂ utilization, fuel cells, and energy demand forecasting. He employs advanced data mining, neural networks, and explainable AI to model, simulate, and optimize complex energy processes, contributing significantly to sustainable energy solutions. His interdisciplinary approach bridges chemical engineering, environmental science, and computational modeling. His recent publications demonstrate a strong trend in applying machine learning to sustainable bioenergy, catalysis, and environmental management. From optimizing biochar production to forecasting global temperature anomalies and enhancing microbial fuel cells, his research leverages AI to address pressing energy and environmental challenges. The articles reflect a consistent focus on sustainability, efficiency, and innovation in energy technologies, with a growing emphasis on explainability and real-world applicability of AI models. Prof. Günay has not been mentioned to have received any specific scientific awards, but his extensive publication record in high-impact journals indicates strong recognition in his field. He has advised several Master’s students, including Muaaz Jnani, Duru Akalın, and co-advised Ahmet Coşgun and Meltem Baysal. He actively supervises senior design projects in areas such as biogas production, biodiesel from shea butter, pyrolysis, and solar desalination, fostering hands-on learning and innovation among students. While no external grants are explicitly mentioned, his research output suggests active involvement in funded projects. His teaching portfolio includes core courses such as Thermodynamics, Fluid Mechanics, Fuels and Combustion, and Energy Systems Modeling and Simulation. Although specific lab or research team names are not provided, his frequent collaborations with researchers like Ramazan Yıldırım, N. Alper Tapan, and Ahmet Coşgun suggest active participation in a research group focused on AI-driven energy and catalysis research at Istanbul Bilgi University.
Barış Ethem Süzek is an Associate Professor in the Department of Computer Engineering at the Faculty of Engineering, Muğla Sitki Koçman University. His academic career spans institutions including Middle East Technical University (BS), Johns Hopkins University (MS), and George Mason University (PhD) in Computational Biology. He specializes in bioinformatics and computational biology, focusing on protein informatics, genetic analysis, and machine learning applications in medical research. Education BS: Middle East Technical University - Computer Engineering (1997) MS: Johns Hopkins University - Computer Science (2000) PhD: George Mason University - Computational Biology (2012) His research integrates bioinformatics with molecular dynamics, particularly in host-pathogen interactions, regenerative medicine, and genomic data analysis. He has developed machine learning tools for viral interaction prediction and variant analysis systems. His work with UniProt and cancer Biomedical Informatics Grid projects demonstrates expertise in large-scale biological data integration. Scientific awards include Collaboration, Outstanding Achievement, and Change Agent Awards from the cancer Biomedical Informatics Grid, plus multiple patent recognitions for biomedical systems. He has supervised numerous graduate students in bioinformatics, computational genetics, and forensic biology projects.
Hacer Atar Yıldız is an Associate Professor at the Department of Electronics and Communication Engineering, Faculty of Electrical and Electronics Engineering at Istanbul Technical University (ITU). She holds a B.Sc. (1997) and M.Sc. (2000) in Electronics Engineering from Karadeniz Technical University, and a Ph.D. (2015) in Electronics Engineering from ITU. Her research focuses on analog circuit design, integrated circuits, analog filters, memristor structures, and graphene sensors. Education: Ph.D. in Electronics Engineering (2015), Istanbul Technical University M.Sc. in Electronics Engineering (2000), Karadeniz Technical University B.Sc. in Electronic Communication Engineering (1997), Karadeniz Technical University German Language Education (2001), Munich Technical University Research Interests: Her work emphasizes innovative analog circuit solutions, including memristor-based systems, neural networks, and sensor technologies. Notable contributions include memcapacitor/meminductor emulator circuits and cryogenic bandgap designs. She also explores applications in plant identification using copula models and thermal compensation for microbolometers. Professional Experience: Associate Professor at ITU (2022–present) Researcher at Virginia University (2018) Expert Engineer at Türk Telekom (2003–2009) Intern at Marco GmbH (Munich, 2001–2002) Teaching: She has taught courses such as Introduction to Electronics, Electronic Design, and Analog Circuits at both undergraduate and graduate levels. Recent courses include EHB 222E and EHB 335. Languages & Hobbies: Fluent in English and German. Enjoys swimming, long-distance running, Turkish folk music, and outdoor activities.
Caner Özer is a Researcher affiliated with Istanbul Technical University's Department of Artificial Intelligence and Data Engineering and the University of Twente's MIA group. He holds a PhD in Computer Engineering from Istanbul Technical University (2020), an MSc in Telecommunication Engineering (2017-2020), and a BSc in Electronics and Communications Engineering (2013-2017). His research focuses on medical imaging AI, explainable artificial intelligence (XAI), deep learning applications in healthcare, and computer vision techniques for artifact detection in medical imaging. He has conducted visiting research at the University of Twente (2024) and serves on academic committees at Istanbul Technical University. Research interests include developing explainable models for mammogram analysis, enhancing medical image quality assessment via transformers and neural networks, and addressing challenges in cardiovascular MRI segmentation through motion artifact detection. His work bridges deep learning theory with practical clinical applications, emphasizing transparency and accuracy in AI-driven medical diagnostics. Notable contributions include cross-domain artifact correction for cardiac MRI, joint CNN-RNN models for intracranial hemorrhage detection, and XAI methods for chest X-ray analysis. His research has been published in top-tier venues with a focus on medical imaging and deep learning advancements.
Ramazan Yeniçeri is a Lecturer at Istanbul Technical University's Department of Aeronautical Engineering. His research focuses on Unmanned Aerial Vehicles (UAVs), Field Programmable Gate Arrays (FPGAs), and computational fluid dynamics, with applications in hardware acceleration and autonomous flight systems. Academic Rank: Lecturer University: Istanbul Technical University Department: Aeronautical Engineering Research Interests: Yeniçeri's work bridges aerospace engineering and computer science, emphasizing: FPGA-based hardware acceleration for aerospace systems UAV communication networks (FANETs) and formation flight Dynamical modeling for 6-DoF systems Autopilot software and real-time operating systems Scientific Awards: He has received the BOEING Academic Work Encouragement Award (2017) and the Best Doctoral Thesis Award (2015) . Project Leadership: As Principal Investigator (PI), he leads projects like: "IHA Kayıt, Takip, Kontrol ve Hava Trafik Yönetim Sistemi" (2024–2025) "FPGA Tabanlı 6DoF Dinamik Hızlandırıcı Tasarımı" (2024) "EU Sürü İHA" (2020–2022) His recent publications highlight trends in UAV communication, FPGA acceleration, and multi-sensor tracking.
Şule Alıcı is an Associate Professor in the Department of Basic Education, Faculty of Education, at Kırşehir Ahi Evran University , Turkey. Since 2022 she has held the rank of Doçent (Associate Professor) on a full-time basis, and since 2022 she also serves as Deputy Director of the University Research & Application Centre. Previously she was Assistant Professor (Dr. Öğretim Üyesi) at the same university (2022-2025) and Research Assistant at Middle East Technical University (2007-2018) and Queensland University of Technology (2017). Education PhD in Preschool Education, Middle East Technical University, Institute of Social Sciences, 2013-2018 MA in Preschool Education (Thesis), Middle East Technical University, Institute of Social Sciences, 2009-2013 BA in Mathematics & Science Education, Gazi University, Gazi Faculty of Education, 2002-2007 Research Focus Dr Alıcı’s scholarship lies at the intersection of early childhood education , education for sustainability , creative drama , and media literacy . She explores how preschool teachers can be empowered to integrate sustainability principles into daily practice, how creative drama can be harnessed to enhance children’s environmental awareness, and how critical media literacy can be used as a transformative tool in teacher professional development. Her work spans curriculum development, teacher education reform, and cross-cultural comparative analyses. Her recent publications reveal a consistent trajectory toward re-orienting early childhood teacher education for sustainability . Using mixed-methods and case-study designs, she investigates teacher candidates’ experiences during practicum, the role of forest schools and outdoor learning, and generational changes in traditional children’s play. Collectively, these studies highlight systemic challenges and innovative pathways for embedding sustainability and creativity within Turkish and international ECE contexts. Awards & Recognition TÜBİTAK Publication Incentive Award (2023) OMEP Special Achievement Commendation – Education for Sustainable Development (2017) National Publication Incentive Award (2011) Projects & Grants Dr Alıcı has led or co-investigated five funded projects, including ReNCitReScArCe (2024, UN & EU supported), Dijital Dünyada Siber Kimlik Farkındalığı (TÜBA-TÜBİTAK 2021-2022), and Müzede Yeşeren Umutlar (Ministry of Development, 2019). These initiatives engage pre-service teachers, school counsellors, rural women, and museum visitors in sustainability and digital citizenship education. Professional Service & Leadership She is Vice-Chair of the Transnational Dialogues in Research in Early Childhood Education for Sustainability network and of the EECERA Sustainability SIG , an active member of AERA, EECERA, OMEP and TEMA, and has organised several international conferences and special journal issues.
Prof. Hasan F. Ateş is a Professor at Özyeğin University's Faculty of Engineering, Department of Computer Engineering, specializing in Artificial Intelligence. He joined Özyeğin University as a full-time Professor in 2022 after holding positions at Sabancı University (2004-2005), Işık University (2005-2018), and İstanbul Medipol University (2018-2022). His academic journey began with a B.S. in Electrical and Electronics Engineering from Bilkent University in 1998, followed by M.A. and Ph.D. degrees in Electrical Engineering from Princeton University in 2000 and 2004, respectively. Prof. Ateş's educational background includes: Doctorate in Electrical Engineering, Princeton University, 2004 Master's in Electrical Engineering, Princeton University, 2000 Bachelor's in Electrical and Electronics Engineering, Bilkent University, 1998 His research focuses on the intersection of deep learning and visual information processing, with particular emphasis on image/video processing, computer vision, remote sensing, autonomous systems, and artificial intelligence. Prof. Ateş leads the Deep-VIP Laboratory, which applies deep learning to solve diverse problems in computer vision and image processing. The lab's work spans multiple sectors including defense, telecommunications, medicine, retail, and consumer electronics. Analysis of Prof. Ateş's recent publications reveals a strong focus on advanced deep learning techniques for visual information processing. His work prominently features state-space models, transformer architectures, and hybrid neural approaches applied to problems like super-resolution, 3D reconstruction, object detection, and medical imaging. Notably, there's a growing emphasis on domain adaptation techniques and cross-spectral registration methods, reflecting the increasing complexity of real-world vision applications. Prof. Ateş's contributions have been recognized through several prestigious awards: First place in the 24th Alper Atalay Best Student Paper Competition (2025) Third place in the Master's Thesis category of the 5DT Thesis Competition (2025) As a dedicated mentor, Prof. Ateş has supervised numerous graduate students through their research journeys. His lab, Deep-VIP, has successfully guided students like İ. Can Yağmur (MS thesis on "Self-Supervised Deep Learning for Multispectral Image Matching") and Gökçe Güven (PhD thesis on "DEEP LEARNING TECHNIQUES FOR 3D VOLUME RECONSTRUCTION FROM PLANAR X-RAY IMAGES"). The lab maintains active collaborations with industry partners including Vestel, Tübitak Bilgem, and Obase, securing research funding for cutting-edge projects in computer vision and deep learning. The Deep-VIP Laboratory is at the forefront of deep learning based computer vision research, with current projects focusing on Image Registration, Tiny Object Detection in Aerial Imagery, Building Height Estimation from Satellite Images, 3D Reconstruction, and Super-Resolution Imaging. The lab's recent work has been presented at major conferences including SIU, IGARSS, and ECAI, demonstrating their commitment to advancing both theoretical understanding and practical applications of visual intelligence systems.
Prof. Dr. Seden Acun Özgünler is a faculty member at the Faculty of Architecture, Istanbul Technical University , where she has served as Professor since 2021. Her research spans material science in architecture, focusing on durability, maintenance, and sustainable building technologies . She has supervised numerous theses and led projects on natural binders, thermal insulation, and historical preservation . Education: PhD in Building Science (Dr), Istanbul Technical University. Academic Roles: Department Head (2023), Associate Professor (2013-2021), Research Assistant (1999-2003). Research Trends include: Material Innovation: Mycelium-based composites, natural hydraulic binders, and geopolymer concrete. Sustainability: LCIA models, waste material utilization, and energy-efficient designs. Historical Preservation: Volcanic tuff conservation, grouting methods for masonry repair, and adaptive reuse of structures. Scientific Awards: 2nd Young Türkiye Summit Academy Award (2017) for Mimar Sinan Cultural Wealth Preservation. Publication-based Academic Performance Awards (2022, 2025) from Istanbul Technical University. Key Projects involve biocomposite materials, natural cement reproduction, and chromic glass applications in facades. Her work bridges traditional building techniques with modern sustainability through experimental and computational approaches.
Engin Erzin is a Professor at Koç University's College of Engineering, leading the KUIS AI Lab and Multimedia, Vision and Graphics Lab . His research focuses on AI-driven human-centric systems, affective computing, and multimodal interaction analysis. He has contributed extensively to robotics, speech processing, and human-robot interaction through over 70 peer-reviewed publications since 2008. Research interests include: Affective computing and emotion recognition from speech/gestures Human-robot interaction and socially engaging agents Speech-driven animation and gesture synthesis Multimodal data fusion for interaction analysis Deep learning applications in robotics and biomedical engineering Recent work emphasizes: Developing adaptive pHRI controllers for manufacturing tasks Creating engagement measurement frameworks for human-machine interfaces Advancing Turkish speech recognition through self-supervised learning Designing multimodal databases for interaction studies Labs: KUIS AI Lab : Focuses on AI applications in robotics and human-computer interaction Multimedia Lab : Specializes in vision, graphics, and audiovisual analysis
Elif Ak is a Researcher at Istanbul Technical University's Department of Computer Engineering, College of Engineering. Her work focuses on cutting-edge network technologies and digital twin systems. Current research in 6G communication frameworks Active in AI-enabled network management Digital twin methodology specialist Her research interests span Digital Twin , 6G Networks , and Machine Learning applications in telecommunications. Recent publications highlight advancements in backbone network security , UWB localization , and semantic communication systems. Key publication trends show 7 Scopus citations with 33 Mendeley readers, featuring collaborations with international experts in IEEE Transactions and Communications Magazine . Research outputs (21 total) demonstrate consistent annual contributions since 2019.
