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.
Professor Hakan Ali Çırpan is a distinguished faculty member at Istanbul Technical University's Faculty of Electrical and Electronics Engineering, where he serves as Professor in the Department of Electronics and Communication Engineering. He also holds the position of Vice Dean at Istanbul Technical University since 2021. With over three decades of academic experience, Professor Çırpan has established himself as a leading researcher in signal processing and communications. His educational background includes: PhD from Stevens Institute of Technology (1993-1997) Master's degree in Electrical-Electronic Engineering (with thesis) from Istanbul University (1989-1992) Bachelor's degree in Electrical and Electronic Engineering from Uludağ University (1985-1989) Professor Çırpan's research spans multiple domains within signal processing and communications. His primary interests include wireless communications, radar systems, machine learning applications in communications, and electronic warfare. His work on channel estimation, orthogonal frequency division multiplexing, and maximum likelihood methods has been particularly influential. He has pioneered research in areas such as source localization, spectrum sensing, and physical layer security. His recent work focuses on 5G/6G networks, AI-enhanced communications, and integrated sensing and communication systems. Analysis of his recent publications (2023-2025) reveals a strong focus on next-generation wireless technologies, particularly 5G/6G networks, AI integration in communications, and electronic warfare applications. His research demonstrates a consistent pattern of addressing fundamental challenges in signal processing while adapting to emerging technological needs. A significant portion of his recent work involves machine learning applications for spectrum management, optimization techniques for radar systems, and novel approaches to network slicing and resource allocation. His notable scientific achievements include: ASELSAN ACADEMY THESIS COMPETITION WINNER (2020) Professor Çırpan has supervised 59 theses throughout his career, mentoring numerous graduate students in the fields of signal processing and communications. He has secured significant research funding, including the "AI-Enhanced 5G/6G Networks with Integrated Camera and ISAC Systems" project (2023-2024) and the "Railway Vehicle Infrastructure New Generation Secure Communication Systems" TÜBİTAK project with a budget of ₺955,000. His research has practical applications in defense systems, railway communications, and next-generation wireless networks. His laboratory work focuses on wireless communications systems, radar signal processing, and AI-enhanced communication technologies. Professor Çırpan leads research teams working on projects related to 5G/6G networks, electronic warfare countermeasures, and secure communication systems. His group collaborates with industry partners like ASELSAN and conducts research with practical applications in national defense and critical infrastructure.
Professor Ali Yapar is a faculty member at Istanbul Technical University in the Electronics and Communication Engineering department. His research focuses on Electromagnetics , Microwave Engineering , and Antenna Technologies , with a particular emphasis on inverse scattering problems and microwave imaging for biomedical applications. He has supervised numerous graduate students and led projects related to breast cancer treatment and rough surface imaging. PhD in Electronics and Communication Engineering from Istanbul Technical University (1997) MSc in Electronics and Communication Engineering (1995) His recent publications analyze advanced techniques for microwave hyperthermia systems, reverse time migration methods, and Newton-based solutions for electromagnetic inverse scattering. Key projects include TUBITAK-funded initiatives on microwave tomography and brain stroke imaging. He serves as a project investigator and executive for electromagnetic research programs. Research areas span Electromagnetic Wave Propagation , Green's Function Applications , and Dielectric Material Analysis . Collaborations include IEEE members and international researchers in computational electromagnetics.
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.
Prof. Dr. Mehmet Reşit Tolun is a full-time Professor in the Department of Software Engineering at Çankaya University (Turkey) since 2022. Previously held full-time professor positions at Konya Food and Agriculture University (2020-2022), Aksaray University (2013-2017), and TED University (2011-2013), along with a part-time professorship at Başkent University (2017-2020). Specializes in Artificial Intelligence , Machine Learning , and Data Mining , with a focus on deep learning applications in aerospace, biomedical data analysis, and software process improvement. PhD in Computer Science (University of Kent, 1985) MSc in Computer Science (University of Kent, 1982) BSc in Physics and Computer Science (University of Kent, 1981) Research Interests span deep learning frameworks, hybrid expert systems, software engineering methodologies, and biomedical signal processing. Publications emphasize practical implementations in medical diagnostics, robotics, and agricultural pest detection. Scientific Awards include the IEEE Third Millenium Medal (2000). Supervised over 55 graduate students, including Burak Çetin, Uğur Özotuk, and Mahinur Doğan. Collaborated with researchers from Orta Doğu Teknik Üniversitesi , Çankaya University , and Aksaray University .
Figen S. Oktem is an Associate Professor in the Department of Electrical and Electronics Engineering at Middle East Technical University (METU), Ankara, Turkey. Her research focuses on advanced imaging systems and algorithms, including computational imaging, inverse problems, and machine learning applications in signal processing. Ph.D., Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (UIUC) (2014) M.S., Electrical and Electronics Engineering, Bilkent University (2009) B.S., Electrical and Electronics Engineering, Bilkent University (2007) Her work bridges physics-informed machine learning and computational optics, with applications in spectral imaging, radar, and microwave systems. She has also explored Fourier phase retrieval, denoising diffusion models, and real-time MIMO radar imaging. Recent publications highlight trends in phase retrieval using deep learning ( prNet , I2I-PR , DDRM-PR ), 3D MIMO imaging, and compressive spectral imaging. Techniques often integrate plug-and-play regularization, stochastic refinement, and physics-based priors. She can be contacted via email at figeno@metu.edu.tr . Curriculum vitae and publications are accessible through her Google Scholar profile.
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).
Dr. Selçuk Uluağaç is an Eminent Scholar Chaired Associate Professor at Florida International University (FIU), leading the Cyber-Physical Systems Security Lab. He holds a courtesy appointment in the Knight Foundation School of Computing and Information Science. Previously, he worked at Georgia Tech and Symantec, with degrees from Georgia Tech (PhD) and Carnegie Mellon University (MS). His research focuses on cybersecurity, privacy, and IoT/CPS systems, funded by NSF, DOE, and industry partners exceeding $18M. He has authored hundreds of publications, secured 17 patents (one licensed), and serves on editorial boards of IEEE journals. Education: PhD in Electrical and Computer Engineering, Georgia Institute of Technology (200X); MS in Computer Science, Carnegie Mellon University (200X). Research Interests: Developing security frameworks for IoT devices, privacy-preserving techniques, machine learning for cybersecurity, and CPS threat mitigation. Notable projects include sensory channel threat analysis, IoT fingerprinting, encrypted traffic privacy leakage detection, wearable-based authentication, and cryptomining activity detection. Awards: Recognized with prestigious NSF CAREER Award and multiple institutional awards for research and teaching excellence. Active in professional service, including conference chairs (ACM WiSec 2019, IEEE CNS 2022 TPC Chair) and NIST panels. Grants & Funding: Over $18M from NSF, DoE, US Air Force, Google, Microsoft, and Cisco. Entrepreneurial focus with patents commercialized. Labs & Teams: Directs the Cyber-Physical Systems Security Lab, collaborating on applied security solutions. Media-featured research highlights societal cybersecurity impacts.
Professor Ufuk Karadavut serves at Karabük University Faculty of Medicine, Department of Basic Medical Sciences, where he holds the position of Professor and currently serves as Vice Dean. Previously, he was Dean of the Faculty of Medicine from 2021-2022 and has held multiple leadership roles including Head of Department since 2020. With an extensive publication record of 493 works and significant contributions to both medical and agricultural statistics, his career spans multiple Turkish universities including Ahi Evran University and Bingöl University. PhD, Selçuk University, Institute of Science (2001-2005) Bachelor's Degree, Ankara University, Faculty of Agriculture, Department of Animal Science (1987-1991) Professor Karadavut's research spans biostatistics, medical informatics, and agricultural statistics, with particular expertise in statistical experimental design. His work bridges healthcare applications (medical informatics, clinical data analysis) with agricultural science (crop breeding, animal husbandry). He has developed statistical methodologies applicable across diverse fields, from analyzing palliative care outcomes to optimizing chickpea breeding programs for drought tolerance. His research demonstrates a consistent pattern of applying advanced statistical techniques to solve practical problems in both medical and agricultural contexts. Analysis of his recent publications reveals a strong focus on applying statistical methodologies to address contemporary challenges. In medical informatics, he examines healthcare quality, medical education, and pandemic impacts. In agricultural science, his work centers on crop improvement (particularly chickpeas and other legumes) and animal breeding. His statistical approaches include multivariate analysis, QTL mapping, growth modeling, and machine learning techniques, demonstrating methodological versatility across disciplinary boundaries. While specific awards aren't detailed in the available information, his h-index of 11 (UNIS) and 8 (WoS), along with 583 total citations, indicate significant scholarly impact. His research has attracted funding from major Turkish research bodies including TÜBİTAK and university-supported projects. Professor Karadavut has supervised 13 theses across multiple institutions and taught diverse courses ranging from medical bioinformatics to agricultural statistics. His research portfolio includes 31 projects, with recent work focusing on climate change adaptation in livestock, medical informatics applications, and advanced statistical methodologies for agricultural research. He has collaborated extensively with researchers across multiple Turkish institutions, demonstrating strong interdisciplinary networking capabilities.
Cenk Gursoy is a Professor in the Department of Electrical Engineering and Computer Science at the College of Engineering and Computer Science, Syracuse University. He previously served as a faculty member at the University of Nebraska-Lincoln from 2004 to 2011. He holds a Ph.D. in Electrical Engineering from Princeton University and a B.S. from Bogazici University, Turkey. His research spans wireless communications, information theory, signal processing, and networking. Key areas include 5G/6G technologies, millimeter-wave communications, UAV-assisted networks, energy efficiency, intelligent reflecting surfaces, and machine learning for networking. He has made significant contributions to finite blocklength communications, QoS provisioning, and secure wireless transmissions. The recent publications highlight a strong trend in integrating machine learning—particularly deep reinforcement learning—into wireless resource allocation, network slicing, UAV trajectory planning, and anomaly detection. His work increasingly bridges theoretical information-theoretic models with practical implementations in emerging wireless systems such as RIS-aided networks, NOMA, and edge computing. NSF CAREER Award, 2006 2020 IEEE Region 1 Technological Innovation (Academic) Award IEEE Green Communications & Computing Technical Committee Best Journal Paper Award EURASIP Journal of Wireless Communications and Networking Best Paper Award IEEE PIMRC Best Paper Award Maude Hammond Fling Faculty Research Fellowship All-University Doctoral Prize (awarded twice to his students) Dr. Gursoy has advised over 20 Ph.D. and M.S. students, many of whom now hold positions at leading universities and tech companies. His research has been funded by multiple National Science Foundation grants as Principal or Co-Principal Investigator, focusing on fundamental limits of wireless systems, millimeter-wave networking, and green cloud platforms. He serves as an Area Editor for IEEE Transactions on Vehicular Technology and as an Editor for several other IEEE Transactions journals. He leads the Wireless Communications & Networking Lab and the Smart Vision Systems Lab at Syracuse University, fostering interdisciplinary research in smart networks, IoT, and intelligent sensing systems.
Selin Aslan serves as an Assistant Professor in the Department of Mathematics at Koç University, Istanbul, Turkey, where she conducts research at the intersection of computational mathematics and imaging science. Her academic appointments and research activities are centered within the university's mathematics department, contributing to both undergraduate and graduate education in mathematical sciences. Her educational qualifications include: PhD in Mathematics from Virginia Polytechnic Institute and State University (2018) Master's in Mathematics from Rochester Institute of Technology (2013) B.A. in Mathematics from Ege University (2010) Dr. Aslan's research program focuses on developing advanced computational methods for solving inverse problems in imaging, with particular expertise in phase retrieval, tomographic reconstruction, and ptychography. Her work bridges theoretical mathematics with practical applications in medical imaging, microscopy, and materials science, emphasizing algorithmic innovation and computational efficiency. She integrates techniques from deep learning, optimization theory, and high-performance computing to address challenges in image reconstruction under physical constraints. Analysis of her publication record reveals a consistent trajectory toward solving complex imaging problems through hybrid approaches that combine physics-based models with data-driven techniques. Her recent work demonstrates increasing emphasis on scalability for large datasets, robustness in photon-limited scenarios, and real-time processing capabilities, with applications spanning biomedical imaging to advanced microscopy. No scientific awards were documented in the available sources. Information regarding student advising and research grant activities was not specified in the provided materials, though her publication record suggests active research collaboration. Her computational focus implies engagement with high-performance computing resources for large-scale image reconstruction tasks. While specific laboratory infrastructure details were unavailable, her research on multi-GPU implementations and distributed computing indicates utilization of advanced computational facilities for handling large-scale imaging datasets.
Prof. Dr. Gülin Feryal Ural is a Professor of Industrial Engineering at Baskent University's Faculty of Engineering. With a PhD in Industrial Engineering from Kocaeli University (2013), she has established herself as a prominent researcher in ergonomics, risk assessment, and multi-criteria decision making. Her academic journey includes a Master's in Business Administration (2006) and BSc in Industrial Engineering (2004), both from Kocaeli University. Dr. Ural's educational background is deeply rooted in Industrial Engineering, with a PhD from Kocaeli University in 2013, followed by a Master's degree in Business Administration in 2006 and her undergraduate degree in Industrial Engineering in 2004, all from the same institution. This strong foundation has enabled her to bridge theoretical knowledge with practical applications in her research and teaching. Her research interests span multiple domains within Industrial Engineering, with a strong focus on Ergonomics and Human Factors Management , Risk Assessment and Management , and Multi-Criteria Decision Making methodologies. Dr. Ural has pioneered approaches integrating various decision-making techniques like KEMIRA-M, DEMATEL, and Entropy methods to address complex problems in occupational safety, usability evaluation, and production systems. Her work often bridges theoretical frameworks with practical industrial applications, particularly in healthcare, manufacturing, and educational settings. Analysis of Dr. Ural's extensive publication record reveals a clear trajectory toward increasingly sophisticated risk assessment methodologies and ergonomics applications. She has consistently advanced the integration of multiple decision-making techniques to create holistic assessment frameworks. Her research shows particular strength in adapting these methods to specific industry contexts, from healthcare to manufacturing, and increasingly incorporating machine learning approaches for risk prediction. The interdisciplinary nature of her work is evident in publications spanning engineering, healthcare management, and educational research domains. Dr. Ural has actively contributed to academic service through editorial roles, including membership on the editorial board of the International Journal of Intelligent Computing and Cybernetics and serving as an editor for the International Journal of Lean Six Sigma since 2023. Her teaching portfolio is extensive and reflects her research expertise, covering courses such as Ergonomics and Human Factors Management, Work Study, Lean Production, Occupational Health and Safety, Risk Analysis and Risk Management, and Special Topics in Industrial Engineering. This comprehensive teaching approach ensures her students receive both theoretical foundations and practical applications of Industrial Engineering principles.
Muammer Altan Çakır is a Professor in the Department of Physics Engineering at Istanbul Technical University, actively engaged in high-energy physics research with significant contributions to the CMS Collaboration at CERN. His work focuses on proton-proton collisions, Higgs boson physics, and top quark studies using Large Hadron Collider data. His research interests span experimental particle physics with emphasis on proton-proton collisions , Higgs boson characterization , lepton physics , and transverse momentum analysis . Recent work explores charm baryon production, Drell-Yan processes, and muon identification techniques using advanced multivariate methods in the CMS detector. Analysis of his 15 most recent publications reveals a strong focus on precision measurements in high-energy collisions, particularly in Higgs physics (3 publications), top quark physics (2), and detector optimization (2). His work consistently addresses fundamental questions in the Standard Model through advanced statistical techniques and large-scale data analysis. Doktora sonrası araştırma bursu (2010) Landes Baden Württenberg Doktorarbeit Stipendium (2006) LPC Fall Guest Visitor Faculty (2017) Multiple Performans ödülü awards (2012, 2013, 2015) Professor Çakır has supervised 15 students and leads multiple research projects including GPU-based distributed computing platforms for big data processing, real-time predictive maintenance systems, and deep learning applications for top quark spin correlation studies. His current projects integrate generative AI with domain-specific physics research while developing scalable open-source big data architectures for industrial applications. His laboratory work centers on CMS detector data analysis, with recent focus on online data visualization tools and multivariate techniques for particle identification. Current projects explore GPU-accelerated computing frameworks and generative AI applications for physics-informed design systems.
Ali Emre Pusane is a Professor of Electrical and Electronics Engineering at Bogazici University, Turkey. He holds a PhD in Electrical Engineering from the University of Notre Dame (2008) and has been faculty since 2009. His research focuses on digital communications, information theory, and coding theory, with particular emphasis on molecular communication, radar signal processing, and low-complexity embedded designs. He leads the Bogazici University Signal Analysis Research Group (BUSARG), addressing challenges in communication signal analysis and prototyping. Education: B.Sc. and M.Sc. in Electronics and Communications Engineering, Istanbul Technical University (1999, 2002) M.Sc. in Electrical Engineering and Applied Mathematics, University of Notre Dame (2004, 2006) Ph.D. in Electrical Engineering, University of Notre Dame (2008) Research Interests: His work spans waveform design, machine learning-aided signal analysis, and nanoscale communication systems. Recent projects include molecular beamforming, RIS-assisted wireless systems, and LDPC-coded molecular communications. He also advises on R&D for national and international organizations. Teaching: He teaches courses like EE 242 (Numerical Methods for EE), EE 644 (Error Control Coding), and advanced communication engineering topics at Bogazici University. Feedback from students highlights his dedication to sophomore/junior-level education. Affiliations: Senior Member of IEEE, former associate editor for IEEE Transactions on Communications. Engaged with BUSARG in developing prototypes for physical layer security and molecular communication systems.
Cihan Bayındır is an Associate Professor at Istanbul Technical University's Faculty of Civil Engineering, Department of Civil Engineering, specializing in fluid mechanics, coastal engineering, and computational methods. His research integrates advanced mathematical techniques with practical engineering applications across multiple disciplines. His primary research areas include Fluid Mechanics, Coastal Sciences and Engineering, Numerical Modeling, Fluid Physics, Acoustics and Vibrations, Nonlinear Dynamics, and Quantum Hydrodynamics. Bayındır's work demonstrates a strong interdisciplinary approach, bridging traditional civil engineering with cutting-edge computational methods and quantum phenomena. His research has significant applications in coastal protection, renewable energy systems, disaster management, and infrastructure resilience. Analysis of his recent publications reveals a clear trend toward applying artificial intelligence and machine learning techniques to traditional civil engineering challenges. His work increasingly focuses on using compressive sensing, deep learning (particularly LSTM networks), and fuzzy logic systems to solve complex problems in wave dynamics, vibration analysis, and tsunami prediction. The integration of quantum computing concepts with classical fluid mechanics represents another distinctive aspect of his research portfolio. ITU Doctoral Special Award-2024-Advisor (2025) ITU 2023 Academic Performance Award (2024) Turkish Academy of Sciences (TUBA) Outstanding Young Scientist Award (GEBİP) (2022) Elsevier Frontiers Article Award (2020) Kaleidoscope Award (American Physical Society, 2016) Bayındır leads multiple research projects funded by ITU's Scientific Research Projects Unit (BAP), including studies on dam break wave propagation using fractional equations, optimization of wave energy concentrators with AI methods, and three-dimensional vibration control in marine structures. His work involves collaborations with international institutions, including previous engagement with CERN on accelerator design. He maintains an active research laboratory focused on hydraulics and coastal engineering, with specialized equipment for wave and vibration analysis in the Hydraulics Laboratory HL 216 at ITU.
