Assoc. Prof. Dr. Sema Alaçam Doğan has been affiliated with Istanbul Technical University since 2014, serving as an Associate Professor in the Department of Architecture . She has held administrative roles including Deputy Head of Department and Erasmus Coordinator. Education : PhD in Informatics in Architectural Design (2008-2014), MS in Informatics in Architectural Design (2005-2008), and BS in Architecture (1999-2005) from Istanbul Technical University. Her research explores Computational Design , Artificial Intelligence in Architecture , and Sustainable Material Innovation . She investigates digital tools for heritage preservation, daylight optimization in BIM, and cognitive development in architecture students. Recent publications analyze AI-assisted design literacy , machine learning for Sinan mosques , and environmental comfort in Harran houses . Her work integrates algorithmic frameworks with sustainable practices. Scientific awards include multiple ITU Publication and Performance Awards (2021-2024), FABFEST Prizes , and the 2024 Artemis Educator Award from NASA. Active projects like "Physical Computation in Architectural Drawing" and "Robotic Fabrication with Recycled Wind Turbine Blades" demonstrate her leadership in computational and sustainable research.
Dr. İsmail ÖZTEL serves as an Assistant Professor in the Department of Computer Engineering at Sakarya University's Faculty of Computer and Information Sciences. He has been a faculty member since 2019, following his tenure as a Research Assistant from 2012-2019 at the same institution. His educational background includes: Doctorate in Computer and Information Engineering (2014-2018) from Sakarya University with thesis on "Facial expression detection on partial and full face images using machine learning methods" Master's Degree in Computer and Information Engineering (2012-2014) from Sakarya University with thesis on "Driver simulator for educational purposes" Bachelor's Degree in Computer Engineering (2007-2011) from Sakarya University Dr. ÖZTEL's research focuses on artificial intelligence, deep learning, and computer vision with significant applications in healthcare, mobile technology, and public safety. His work has evolved from foundational facial expression recognition to sophisticated medical applications including skin disease classification using smartphones, monkeypox detection from skin lesions, and pandemic response systems for face mask detection. His research demonstrates strong interdisciplinary connections between computer science and healthcare. An analysis of his publication trends reveals a clear progression toward increasingly complex deep learning architectures applied to real-world problems, with recent work emphasizing medical applications using mobile technology and public health safety systems. His 2023-2025 publications show particular focus on skin disease classification, intelligent vehicle systems, and hybrid feature extraction methods for pandemic response. Dr. ÖZTEL has served as a reviewer for numerous prestigious journals including Expert Systems With Applications (multiple years), World Wide Web, Multimedia Tools and Applications, and Journal of King Saud University - Computer and Information Sciences, demonstrating his recognition in the academic community across multiple domains. His research projects include work on facial expression detection in open scientific databases (2020), performance evaluation of transfer learning approaches (2019), and current projects on brain tumor classification systems and earthquake safety education for individuals with developmental disabilities. His international research experience includes collaboration with Filiz Bunyak in 2017, indicating global engagement in his field.
Mustafa Asım Kazancıgil is an Assistant Professor at Yeditepe University's Faculty of Computer and Information Sciences, Department of Information Security Technology. He has also served in the Department of Information Systems and Technologies at Yeditepe University since 2014. His academic journey includes a PhD in Informatics-Computer Science from Universita degli Studi di Milano (2013) and a Master's in Interactive Digital Television from the same institution (2006). PhD: Universita degli Studi di Milano (2013) Master's: Universita Degli Studi di Milano (2006) Bachelor's: Yeditepe University, Faculty of Communication, Department of Radio, Television and Cinema (2004) His research focuses on web design , information systems security , big data analytics , and emergency services technology . His publications include works on disaster resilience and interactive digital television applications. He has taught courses on Web Design, Information Systems Security, and Advanced Web Programming at both undergraduate and graduate levels. Administrative roles include Head of Department (2021) and multiple Erasmus Coordinator positions (2016-2019). He supervises theses in digital marketing and CRM trends, as well as CRM/SCM applications in management information systems. His teaching portfolio spans 2013-2025 across Yeditepe University's academic calendar.
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.
Ozgur S. Oguz is an Assistant Professor at Bilkent University , Faculty of Computer Engineering, and the lead of the Learning for Intelligent Robotic Agents (LiRA) Lab . His research focuses on enhancing autonomous agents' capabilities in learning, reasoning, and planning, particularly for robotics applications. Education : PhD in Computer Science from TU Munich , studies at University of British Columbia (UBC) and Koç University , postdoctoral work at University of Stuttgart and Max Planck Institute for Intelligent Systems . His research explores algorithms for autonomous decision-making, with emphasis on deep learning , reinforcement learning , and robotics . Recent work includes diffusion-based reinforcement learning , hindsight experience prioritization , and hybrid manipulation planning , often addressing challenges in sequential task execution and tactile-based control. Key trends in his publications revolve around robotic manipulation , motion planning , and human-robot interaction . He has contributed to conferences like NeurIPS , ICRA , IROS , and journals such as IEEE TRO and Scientific Reports .
Ceren Saran Doğan is an Assistant Professor at the Faculty of Communication , Uskudar University , specializing in Radio, Television and Cinema . Her academic background includes a PhD (2022), MA (2015), and BA (2009) in Media and Communication Studies from Galatasaray University and Journalism from Istanbul University. Education: BSc in Journalism (Istanbul University, 2009) MSc in Media and Communication Studies (Galatasaray University, 2015) PhD in Media and Communication Studies (Galatasaray University, 2022) Her research focuses on the political economy of media , critical digital media studies , algorithms in journalism , and digital platform dynamics . She has published extensively on topics like algorithmic bias, media ownership, and digital inequalities, with notable works including the 2024 book chapter Reasons for News Avoidance on Mobile News Consumption and the 2022 book chapter Algorithms and Audience Monitoring in Newsrooms . Her recent 2023-2025 publications analyze digital platform trust , AI integration in newsrooms , and platform capitalism , reflecting her expertise in algorithmic systems and media sociology. She also serves as Vice Dean and chairs multiple committees at Uskudar University, including Social Media Commission and Curriculum Development Commission . She teaches courses like Digital Content Production and Graduation Project II .
Mehmet Uğur KAHRAMAN is an Assistant Professor at the Department of Interior Architecture and Environmental Design at Antalya Bilim University, where he has served since 2017. Previously, he held a faculty position at Kayseri Nuh Naci Yazgan University (2015–2017). His academic journey includes a Doctorate from Hacettepe University (Interior Architecture and Environmental Design), a Master of Design (Interior Design) from Swinburne University of Technology (Australia), and a Bachelor’s degree from Hacettepe University’s Department of Interior Architecture and Environmental Design. Before academia, he worked as a construction site manager at KG Architecture in Istanbul, co-founded the food and beverage brand 'Shot&Bite' in Ankara, and later served as a designer at QUBİ Design Office. His research focuses on integrating artificial intelligence into design education, neurocognitive aspects of spatial design, sustainable materials, and pedagogical innovations in interior architecture education. He has authored over 20 peer-reviewed articles on topics ranging from AI-driven furniture design to multisensory hospitality spaces. His work bridges theoretical research with practical applications, such as developing curriculum models for design studios and exploring waste-to-art construction techniques. KAHRAMAN’s studies also address health impacts of building materials and the psychological dimensions of housing during crises like the COVID-19 pandemic. He maintains active research collaborations, particularly in Turkey and Australia, and has contributed to public infrastructure projects involving material conservation and adaptive reuse. His educational philosophy emphasizes student-centered learning, interdisciplinary approaches, and leveraging digital tools for contemporary design challenges.
Dr. Emre PINAR is an active Researcher at Çukurova University's Faculty of Architecture, Department of Interior Architecture. His work bridges innovative design with critical safety and sustainability considerations. Faculty Affiliation: Faculty of Architecture, Çukurova University Academic Rank: Researcher Research interests span biomimetic design principles, earthquake-resistant furniture solutions, and the integration of artificial intelligence in interior architecture. His recent work explores: Biomimetic furniture design systems (LOT-US, 2025) Non-structural seismic safety elements (2022) AI collaboration in design workflows (2019) Historical structural analysis of Eastern Black Sea rural buildings (2018) Design methodologies emphasize space optimization in constrained environments and preservation of traditional architectural knowledge through modern analytical frameworks.
Sevil Yazıcı is an Associate Professor at the Department of Architecture , Istanbul Technical University , with a focus on computational design, material efficiency, and structural performance in architecture. She previously served as a Doctor Lecturer at Ozyegin University (2013–2020). Educational background: PhD in Building Sciences (2009–2013), Istanbul Technical University Degree in Architecture from Architectural Association School of Architecture (2004–2006) Research interests span computational design, bio-inspired material organization, and sustainable construction. Her recent work explores VR-driven spatial performance analysis, demolition waste reuse, and microstructure-informed shell topologies. Selected trends in publications include: Integrating environmental/structural data in early design Material-efficient generative models Biomimetic computational analysis AI-assisted architectural creativity Scientific awards highlight her achievements: 2024 Best Article Award (Frontiers of Architectural Research) 2018 Gold Medal (Istanbul International Invention Fair) 2016 UK Graduate Professional Achievement Award 2014 ITU Most Successful Doctoral Thesis Award Advising includes theses on reversible structures, sustainable façades, AI-driven design, and material-efficient fabrication. She served on the Executive Board of the Informatics in Architectural Design Graduate Program (2021–present) and was Deputy Head of Department (2022).
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
Sanem Kabadayı is an Assistant Professor at the Department of Computer Engineering, Istanbul Technical University. Her research focuses on sensor networks, middleware frameworks, and pervasive computing. Research Interests Sensor Networks (Wireless, Ad-hoc, Heterogeneous) Pervasive and Ubiquitous Computing Middleware Design for Smart Environments Data Abstraction and Communication Paradigms Advisory Role Advisor for Yakup Kayatas' thesis on AI-assisted IoT agents for smart spaces (2025). Recent Research Trends Her 15 most recent publications (2006–2024) emphasize sensor network architectures, middleware innovations for programmable environments, and abstractions for heterogeneous sensor integration. Key themes include AI-driven IoT agents, positioning techniques in wireless networks, and virtual sensor frameworks.
Tamer Ölmez is a Professor in the Department of Electronics and Communication Engineering at Istanbul Technical University (ITU), College of Engineering, where he conducts cutting-edge research in biomedical signal processing, brain-computer interfaces (BCI), and deep learning applications in medical systems. His work bridges engineering and neuroscience, with a strong focus on EEG-based motor imagery classification, medical image analysis, and embedded deep learning systems. His research interests include motor imagery EEG signal processing , brain-computer interfaces , feature extraction , deep neural networks , classification algorithms , and medical image analysis . He applies machine learning and signal processing techniques to improve diagnostic accuracy and system performance in neuroengineering and healthcare technologies. The recent publications highlight a consistent trend in leveraging divergence-based deep neural networks , convolutional neural networks , and small-sized models for efficient and accurate classification in BCI and medical imaging. His work emphasizes performance improvement with reduced channel counts, noise elimination, and real-time applicability in embedded systems. Scientific Awards: Excellent Oral Presentation Certificate, June 1, 2015 Advising and Grants: He is actively supervising 26 theses in progress, indicating a strong mentoring role. He has led multiple funded research projects, including those funded by ITU’s Technology Transfer Office (TTO) and Scientific Research Projects (BAP), such as 'Classification of Medical Images with Deep Learning Method in Embedded Systems' and 'New Approaches to Finding Optimal Protein Folding'. Labs and Research Teams: While specific lab names are not mentioned, his collaborative fingerprint and project leadership suggest he leads or is a key member of a research group focused on biomedical signal processing, neural networks, and intelligent systems at ITU.
Semih Doğu is an Assistant Professor at the Department of Electronics and Communication Engineering , Faculty of Electrical and Electronics Engineering , Istanbul Technical University . His research focuses on Electromagnetic Theory , Microwave Imaging , Inverse Scattering Problems , and Antenna Design . Doctorate: Istanbul Technical University (2023) Master's: Istanbul Technical University (2017) Bachelor's: Yıldız Technical University (2015) His research interests emphasize microwave-based diagnostics, including: Microwave imaging for breast cancer detection Antenna optimization for medical and security applications Inverse problem solving in electromagnetic systems Through-the-wall imaging for surveillance Semih Doğu's recent publications demonstrate his expertise in: Neural networks for temperature monitoring in hyperthermia Ku/Ka-band antenna designs for satellite systems Microwave salinity sensing Algorithm development for improved imaging accuracy He contributes to the ITU Electromagnetics Research Group , participating in projects like: Microwave Brain and Breast Imaging Device Development Compressed Sensing for Energy-Efficient Communication Microwave Tissue Analysis
Assoc. Prof. Dr. Umut Asan is an active faculty member in the Department of Industrial Engineering at Istanbul Technical University (ITU), Faculty of Management. He holds the academic rank of Associate Professor and has been affiliated with ITU since 1999, progressing from Research Assistant to his current role. He earned his PhD from Technische Universität Berlin and holds a Master’s and Bachelor’s from ITU in Engineering Management and Industrial Engineering, respectively. PhD: Technische Universität Berlin (2003–2009) MSc: Istanbul Technical University, Engineering Management (1999–2001) BSc: Istanbul Technical University, Industrial Engineering (1995–1999) Dr. Asan's research lies at the intersection of decision science and industrial systems, with a strong emphasis on Multi-Criteria Decision Making (MCDM) , Fuzzy Cognitive Mapping , Scenario Planning , and Digital Twins . His work applies advanced modeling techniques such as Bayesian networks and fuzzy logic to solve complex problems in supply chain resilience, urban mobility, technology adoption, and organizational behavior. His recent publications (2023–2025) reveal a consistent trend toward integrating artificial intelligence and data-driven methods into decision support systems. Topics include electric vehicle adoption in urban logistics, digital twin frameworks for manufacturing, risk analysis in forestry and rail systems, and consumer behavior in digital platforms. These works demonstrate interdisciplinary applications across engineering, business, and social sciences, often using fuzzy and probabilistic models to handle uncertainty. Dr. Asan is actively involved in research leadership, having served as Vice Dean (2018–2023) and currently supervising numerous graduate theses. He is the principal investigator of funded projects, including BAP grants on qualitative cross-impact analysis and consumer cognitive models. Principal Investigator, "A New Approach to Qualitative Cross-Impact Analysis" (BAP Project, 2016–2020) Principal Investigator, "A New Approach to Consumer Causal Chain Models" (BAP Project, 2022–2024) He is a member of several international academic societies, including the International Society on MCDM, ENBIS, and EURO, reflecting his active engagement in the global operations research community. His research has been published in journals such as IEEE Access, European Journal of Forest Engineering, and Decision Science Letters, with a growing citation impact (Scopus h-index: 13). Dr. Asan advises a large cohort of graduate students, both at the Master’s and PhD levels, in areas ranging from risk modeling to digital transformation. His lab or research group focuses on decision support systems and cognitive modeling, supervising theses on FMEA, Bayesian networks, and digital twins. Future work appears to be directed toward enhancing predictive capabilities in industrial and societal systems through hybrid AI models.
Selda Güney is an Assistant Professor in the Department of Electrical and Electronics Engineering at Başkent University's Faculty of Engineering. She holds a PhD (2013), Master's (2007), and Bachelor's (2004) in Electrical-Electronics Engineering from Karadeniz Technical University. Her professional experience includes roles as an R&D Engineer at DEKA Digital (2004-2005), Research Assistant at Karadeniz Technical University (2005-2013), and Assistant Professor at Başkent University (2013-present). Her research spans: Machine Learning : Applications in medical imaging, radar, and industrial systems Signal/Image Processing : Focus on real-time classification and fault detection Pattern Recognition : Electronic nose systems and biometric analysis Her recent publications demonstrate strong emphasis on deep learning applications in healthcare (chest X-ray classification, fracture detection) and industrial automation (real-time fault detection systems). Over 70% of her last 15 articles involve medical/industrial AI implementations using convolutional networks. Awards & Honors: TÜBİTAK Domestic PhD Scholarship IBEC ERASMUS Scholarship Research Leadership: Supervised 20+ graduate theses (e.g., radar data classification, medical image steganography) and led 9 R&D projects including: AI-based pathology classification in lung X-rays VR glove development Smart parking systems She is a member of IEEE and ISOCS, and teaches courses including Pattern Recognition, Signals and Systems.
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