Prof. Dr. Ahmet Tutar is a faculty member in the Department of Chemistry at Sakarya University . His academic activities include teaching courses such as Organic Chemistry I/II , Organic Synthesis Design , and Stereochemistry , alongside supervising numerous master's theses in organic synthesis and humic substance applications. Research Interests: Focus on bromination reactions , BODIPY dye synthesis , humic/fulvic acid characterization , computational chemistry , and pharmaceutical applications of organic compounds. Key Article Trends: Recent publications emphasize photobromination methods , metal-organic frameworks , and biological activity of brominated derivatives , with keywords spanning organic synthesis , biochemistry , and environmental chemistry . Thesis Supervision: Guided 35+ master's theses (2007-2013) on topics like synthesis of brominated indan derivatives , humic acid extraction , and photobromination of terpenes .
Mustafa Taha Koçyiğit is a Full-time Assistant Professor at Bogazici University. His research focuses on Deep Learning, Self-supervised learning, Efficient training of deep learning methods, Computer vision, Efficient training of large language models, and Language grounded vision models. His recent work addresses computational efficiency in training methods and novel applications of deep learning across domains like aerospace defect detection and computer vision. His publications span advancements in self-supervised learning strategies (2023), efficient training for computer vision tasks (2023), and theoretical contributions like unsupervised batch normalization (2020). The 2025 work demonstrates cross-disciplinary impact in aerospace engineering through AI-driven defect detection via X-ray tomography. Notable Contributions: Bridging efficiency and accuracy in deep learning pipelines Technical Strengths: Neural architecture design, optimization strategies, and domain-specific model adaptation
Cem Say is a Professor in the Department of Computer Engineering at Boğaziçi University's Faculty of Engineering, where he has established himself as a leading researcher in theoretical computer science and artificial intelligence. His academic journey began with the completion of his doctoral dissertation titled Qualitative System Identification in 1992, which was the first thesis of Boğaziçi University's Computer Engineering PhD program. Professor Say's research interests span multiple domains of computer science, with significant contributions to quantum computing, artificial intelligence, and theoretical computer science. His early work focused on qualitative reasoning and simulation, particularly through the QSIM algorithm, where he made significant improvements to filtering techniques and addressed challenges in representing physical systems. Over time, his research evolved toward quantum computation, where he has made substantial contributions to quantum finite automata theory, space-bounded quantum computation, and quantum complexity classes. His recent work explores the energy complexity of computation, bridging theoretical computer science with thermodynamics. His publication record shows a clear evolution from classical AI and qualitative reasoning toward quantum computation. The most recent articles demonstrate his focus on space-bounded quantum computation, energy complexity of regular languages, and interactive proof systems with minimal resources. His work consistently addresses fundamental questions about computational limits, particularly in quantum and sublogarithmic-space models. Professor Say has also made significant contributions to science communication through several books written for general audiences, including 50 Soruda Yapay Zekâ (2018), Yeni Dünya, Yeni Ağ (2020), and En Hakiki Mürşit (2021), which explain complex concepts in artificial intelligence and scientific methodology in accessible terms. Throughout his career, Professor Say has been actively involved in the Turkish academic community, editing proceedings for multiple Turkish symposia on artificial intelligence and neural networks. His doctoral dissertation established foundational work in qualitative system identification, and his subsequent research has consistently pushed boundaries in theoretical computer science, particularly in quantum computation where he has collaborated extensively with Abuzer Yakaryılmaz and other researchers.
Dr. Aykut Koç is an Associate Professor at the Department of Electrical and Electronics Engineering and a faculty member of the National Magnetic Resonance Research Center (UMRAM) at Bilkent University, Turkey. He leads the AykutKoc Lab, focusing on interdisciplinary research at the intersection of machine learning, signal processing, natural language processing, and graph signal processing. Education: B.S. in Electrical and Electronics Engineering (2005, Bilkent University); M.S. in Electrical Engineering (2007), M.S. in Management Science and Engineering (2009), and Ph.D. in Electrical Engineering (2011) under Professor Lambertus Hesselink at Stanford University; LL.B. in Law (Ankara University). His research integrates mathematical signal processing techniques (e.g., fractional Fourier and linear canonical transforms) with modern machine learning architectures like transformers and graph neural networks. Recent work explores semantic communication systems, bias mitigation in legal language models, and cross-modal applications in biomedical imaging and radar technology. Dr. Koç has published extensively in IEEE and Springer journals, with recent articles analyzing Fourier-enhanced transformers, graph-based NLP methods, and time-vertex signal analysis. His work addresses both theoretical innovations and practical applications, including schizophrenia diagnosis, legal outcome prediction, and maritime surveillance. Scientific Awards: Science Academy Young Scientists Award (BAGEP), 2023. He has supervised numerous graduate and undergraduate researchers, many of whom have transitioned to top-tier institutions such as MIT, UCLA, and TU Darmstadt. Dr. Koç actively serves as Associate Editor for multiple IEEE journals and participates in conference program committees, including EMNLP's Natural Legal Language Processing (NLLP) workshop.
Canan ATILGAN is a Professor at the Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey. She has held leadership roles including Dean (2018-2020), Director of the Graduate School (2018-2020), and President of the Science Academy (2021-present). Her research focuses on computational tools for protein conformational transitions, allosteric communication, and antibiotic resistance mechanisms. Ph.D. (1996) and B.S. (1991) in Chemical Engineering from Boğaziçi University A pioneer in perturbation-response scanning and network-based protein modeling, her work bridges biophysics, structural biology, and molecular evolution. She has supervised 15 PhD and 17 MS students, emphasizing accessible computational biophysics education through workshops and seminars. Her recent publications highlight allosteric mechanisms in biosensors, β-lactam resistance via TolC dynamics, and evolutionary fitness landscapes. Awards include EMBO and Academia Europaea membership, L’Oréal Turkey Young Women Scientist Fellowship, and TÜBA-GEBİP Distinguished Young Scientist Award. President, Science Academy (2021) EMBO Elected Member (2023) TÜBA-GEBİP Distinguished Young Scientist (2004) She leads the MIDST Lab, contributes to Turkish science communication via sarkac.org, and organizes 'Dialogues in the MIDST' workshops for graduate students. Her work integrates theoretical models with experimental validation in iron transport proteins and resistance mechanisms.
Tuğba Dalyan is an Associate Professor in the Department of Computer Engineering at Istanbul Bilgi University, Faculty of Engineering and Natural Sciences. She holds a Ph.D. in Computer Engineering from Yıldız Technical University (2014), an MSc from Kocaeli University (2007), and dual BSc degrees in Mathematics and Computer Science and Business Administration (Minor) from Istanbul Bilgi University (2003). She has been a faculty member since 2016 and previously served as a Teaching Staff member and Research Assistant at the same institution. Her research focuses on Natural Language Processing , Machine Learning , Deep Learning , Text Mining , Data Science , and Big Data Analytics . Her work spans computational linguistics, sentiment analysis, author profiling, machine translation, and smart systems. She has led and contributed to numerous research projects, particularly in AI-driven urban solutions and health technologies. The most recent publications show a strong trend in Turkish NLP, zero-shot classification, multimodal AI (image captioning), emotional robotics, and decision support systems using fuzzy logic. Her work combines theoretical rigor with practical applications in smart cities, education, and healthcare. Best Paper Award , CICLing 2012 TÜBİTAK 2209-A student project awards (2022–2024) Horizon2020 Eşik Üstü Ödülü , MIMOSCSA 2024 TÜBİTAK 2242 competition: 2nd and 3rd place (2016, 2018) She has advised numerous student research projects, many of which have received national recognition. She has directed multiple TÜBİTAK and institutional research grants, including projects on smart homes, blockchain crowdfunding, mental health, and AI for social polarization. Her leadership roles include Head of Department, Vice Dean, and Director of Graduate Programs. Tuğba Dalyan leads research in AI and NLP with a strong emphasis on Turkish language technologies. She is involved in interdisciplinary teams working on emotional robots, smart city platforms, and citizen science ecosystems. Her lab activities focus on neural networks, text analysis, and intelligent systems development.
Professor Vakur B. Erturk is a distinguished faculty member in the Department of Electrical and Electronics Engineering at Bilkent University's Faculty of Engineering. With a PhD from The Ohio-State University (2000), his academic journey spans over two decades of impactful research and teaching. His research focuses on advanced computational electromagnetics, specializing in closed-form Green's function representations, conformal antenna design, structural health monitoring systems, and metamaterial applications. His work bridges theoretical electromagnetics with practical engineering solutions, particularly in wireless sensing and high-frequency electromagnetic analysis. Professor Erturk's publication record demonstrates consistent innovation, with recent work emphasizing efficient computational methods like the multilevel fast multipole algorithm (MLFMA) for multiscale electromagnetic problems. His research shows strong continuity in antenna theory while expanding into metamaterial-inspired sensors and structural monitoring systems. Best master thesis award (1996) He actively mentors graduate students, with over 30 PhD and MSc graduates who have contributed significantly to fields including computational electromagnetics, antenna design, and wireless sensor development. His research group maintains strong collaborations with institutions like Middle East Technical University and researchers in metamaterials and structural health monitoring. Professor Erturk teaches core courses including Microwave Engineering, Antenna Engineering, and Computational Methods in Electromagnetics, shaping the next generation of electrical engineers through rigorous theoretical and practical instruction.
Prof. Dr. Ahmet ÖZMEN is a Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Software Engineering. He has held various administrative positions including Head of the Software Engineering Department (2019-2028) and Director of the Computer Research and Application Center (2019-2022). With extensive experience in academia since 1991, he has made significant contributions to computer vision, traffic monitoring systems, and sensor technologies. Sakarya University: Professor (2019-present), Associate Professor (2011-2019) Dumlupınar University: Assistant Professor (2001-2011), Research Assistant (2000-2001, 1993-1998) Istanbul Technical University: Research Assistant (1991-1993) Prof. ÖZMEN's research spans computer vision applications for traffic monitoring, indoor air quality systems, parallel computing, and sensor technologies. His work bridges theoretical computer science with practical engineering applications, particularly in developing vision-based systems for nighttime vehicle detection, traffic flow monitoring, and environmental sensing. His interdisciplinary approach combines machine learning, image processing, and embedded systems to solve real-world problems in transportation and environmental monitoring. His publication record shows a clear evolution from parallel and distributed systems in his early career to computer vision and sensor applications in recent years. The majority of his recent work focuses on traffic monitoring systems using computer vision techniques, particularly for nighttime conditions, and indoor air quality monitoring systems using sensor networks. His research demonstrates strong industry and societal relevance, with applications in smart transportation, environmental protection, and educational technology. TÜBİTAK Publication Awards (2006, 2008, 2009, 2010) Physical implementation award from TÜBİDER (2008) Microsoft Certified Professional Certificate (2005) YÖK overseas study scholarships (1993, 1998) Elginkan graduate scholarships (1990, 1991) Prof. ÖZMEN has supervised numerous graduate students across multiple institutions, with a focus on practical engineering problems. His research has been supported by various projects including TÜBİTAK projects, institutional research grants, and industry collaborations. He has led significant research initiatives in traffic monitoring systems, indoor air quality monitoring, and educational technology platforms. His administrative leadership has included directing research centers and shaping curriculum development in software engineering. His work has involved establishing research teams focused on computer vision applications, sensor network development, and educational technology. These teams have produced numerous publications, developed practical systems, and trained the next generation of computer engineers. Current research directions include advanced traffic monitoring systems using deep learning and multi-camera setups for urban planning applications.
Assoc. Prof. Dr. Ayhan Gün is an Associate Professor in the Department of Electrical and Electronics Engineering at Kütahya Dumlupınar University's Faculty of Engineering. With a career spanning over two decades, he has held various academic positions including Research Assistant, Assistant Professor, and currently Associate Professor since 2024. His extensive administrative experience includes serving as Head of the Control and Command Systems Department (2007-2021) and various leadership roles in university-industry collaboration initiatives. Dr. Gün completed his Bachelor's degree at Near East University (1991-1996), Master's at Dumlupınar University (1998-2001), and PhD at Eskişehir Osmangazi University (2001-2007). His research focuses on control systems, mathematical modeling, artificial neural networks, robotics, SCADA, PLC programming, electromechanical systems, nonlinear control, fuzzy logic, optimization techniques, automation, biomechanics, and mechatronics. His recent publications demonstrate a consistent research trajectory in control engineering, with particular emphasis on optimization algorithms applied to quadrotor control, inverted pendulum systems, and electrical motor design. His work bridges theoretical control concepts with practical implementations in robotics and power systems. A significant portion of his research involves applying swarm intelligence and evolutionary algorithms to solve complex control problems. Bilim, Sanayi ve Teknoloji Bakanlığı Kurumsal Kapasitenin Arttırılması (2016) BİLİM SANAYİ VE TEKNOLOJİ BAKANLIĞI Çift Beslemeli İndüksiyon Generatörü Tasarımı ve İmalatı (2016) Dr. Gün has supervised multiple graduate students and managed numerous research projects, including the current 'Robotic Arm Design and Implementation for Patients with Hemiparetic Arms' project. His external roles include serving as an expert witness for judicial institutions, project referee for TÜBİTAK, and publication reviewer for IEEE Transactions. He has also contributed to regional development through his work with Kütahya Governorship's Planning and Development Board.
Dr. Veysel Gümüş is an Associate Professor at Harran University's Faculty of Engineering, Department of Civil Engineering, where he has been since 2014. His research focuses on turbulence modeling, computational fluid dynamics, hydrological drought analysis, and time-series trend analysis. Licence (2003), Master's (2006), and Doctorate (2014) in Civil Engineering from Harran and Çukurova Universities. His research interests span hydrological drought , computational fluid dynamics , climate trend analysis , and GIS applications in hydrology . His recent work emphasizes drought risk assessment, wind speed trends, and fluid flow simulations using AI techniques. Publications since 2023 highlight his expertise in Mann-Kendall tests , copula-based drought analysis , and CMIP6 climate projections across Turkey and Morocco. He has supervised over 15 graduate theses and served as an editor/hakem for 10+ journals, including ASCE and Theoretical and Applied Climatology.
Sinan Yıldırım is a Researcher in the Faculty of Engineering and Natural Sciences at Sabancı University, Turkey. His primary research focuses on Bayesian Statistics, Monte Carlo methods, and data privacy, with interdisciplinary applications in machine learning and signal processing. He holds a BSc and MSc in Electrical and Electronics Engineering from Boğaziçi University, followed by a PhD in Mathematical Statistics from the University of Cambridge. Postdoctoral research (2013-2015) at the University of Bristol’s School of Mathematics involved the EPSRC-funded project 'Intractable Likelihood: New Challenges from Modern Applications (i-like).' His work bridges theoretical statistics with practical problems in privacy, control systems, and energy optimization. Research interests emphasize Bayesian methodologies for privacy-preserving data analysis, dynamic modeling of complex systems, and stochastic optimization algorithms. Recent publications explore differential privacy in machine learning, Monte Carlo techniques for high-dimensional inference, and applications of Bayesian methods in robotics and energy systems. Advising and grants include contributions to multi-party resource sharing frameworks and privacy-aware algorithms. His work integrates computational methods with real-world challenges in engineering and policy modeling.
Prof. Dr. Gökhan Kiper is a faculty member in the Department of Mechanical Engineering at Izmir Institute of Technology , Turkey. His research focuses on Mechanism Science , Machine Design , and Deployable Structures , with particular emphasis on Polyhedral Geometry applications. Teaches courses: ME332 (Mechanisms), ME402 (Machine Design), ME577 (Advanced Mechanism Design) Active in IFToMM (International Federation for the Promotion of Mechanism and Machine Science), including roles in the Technical Committee for Computational Kinematics and the Turkey Branch (MakTeD) Co-organized the IFToMM Summer School on Mechanism Design for Medical Applications (2018) Research interests span kinematic synthesis of mechanisms, deployable architectural structures, and medical robotics. Key projects include a rollable ramp for temporary use, finger exoskeletons for rehabilitation, and remote-center-of-motion manipulators for minimally invasive surgery. His work integrates theoretical analysis with practical prototyping, reflected in publications across robotics, structural mechanics, and geometric design. Affiliates with the Rasim Alizade Mechatronics Laboratory (RAML) and the IzTech Kinetic Designs in Architecture Group . Presented at international conferences like International Symposium of Mechanism and Machine Science (ISMMS-2017) in Baku, Azerbaijan, where he chaired sessions on mechanism kinematics.
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.
Asst. Prof. Hilal Öztürk Baydere serves in the Department of Western Languages and Literatures at Karadeniz Technical University's Faculty of Arts and Humanities since 2021, advancing to Assistant Professor in 2024 after beginning her academic career at the university's School of Foreign Languages in 2013. Her institutional trajectory reflects deep integration within Turkey's translation studies community. Her academic foundation includes: Doctorate in Translation Studies (2016-2022) from Istanbul University's Institute of Social Sciences Postgraduate degree in English Translation and Interpretation (2011-2015) from Hacettepe University Undergraduate degree in English Language and Literature (2007-2011) from Hacettepe University Her research centers on Translation Studies with acute focus on machine translation's disruption of literary translation practices. She investigates translator competence evolution in AI-driven environments, creativity preservation in machine-assisted workflows, and historical/cultural dimensions of translation. Her work bridges theoretical linguistics with practical technological applications, particularly examining lexical diversity and stylistic integrity in neural machine translation outputs. Publication analysis reveals three dominant research vectors: (1) Machine translation evaluation frameworks for literary texts (25% of output), (2) Historical/cultural memory representation through translation (33%), and (3) Translator identity and competence in digital ecosystems (42%). Recent work increasingly incorporates large language models while maintaining strong philological grounding in English-Turkish translation contexts. She actively supervises student research on AI translation applications including subtitle translation effectiveness and e-commerce review sentiment analysis. Her TUBITAK-funded doctoral scholarship (2017-2022) and current membership in the European 'Language in the Human-Machine Era' research consortium demonstrate significant grant acquisition and international collaboration. Conference participation spans 8+ annual international symposia since 2017, primarily KTUDELL and NALANS events. Her ongoing projects with the European Cooperation in Science and Technology group indicate future research directions exploring human-AI symbiosis in translation pedagogy and professional practice, particularly regarding creativity metrics and cultural adaptation in neural machine translation systems.
