جست‌وجوی استاد و پژوهشگر

Hamzah Syedمشاهده پروفایل

استادیار

• Statistical Genetics
• Bioinformatics
• Multi-Omics Studies
• +۳ مورد دیگر

Dr. Hamzah Syed is an Assistant Professor of Statistical Genetics and Bioinformatics at Koç University's School of Medicine. He leads research integrating statistical methods and machine learning into multi-omics studies, particularly targeting cancer and neurodegenerative diseases like ALS. His work focuses on overcoming drug resistance mechanisms in cancers such as prostate cancer and triple-negative breast cancer through epigenetic and genomic approaches. Dr. Syed holds a PhD in Biostatistics from the University of Liverpool and conducted postdoctoral research at University College London (UCL), specializing in rare disease datasets and bioinformatics tools. He is the principal investigator on a CIHR-funded project exploring microbiomic biomarkers for ALS and has secured over ten TÜBİTAK grants. His research portfolio includes developing computational platforms like EPIKOL for epigenetic vulnerability screening and MOPower for multi-omics power analysis. He manages clinical and multi-omic data for Koç University's high-performance computing infrastructure, ensuring robust data integration across medical research projects. Key research themes include drug resistance in solid tumors, epigenetic regulation in glioblastoma, and applying phenome-wide association studies (PheWAS) to understand disease mechanisms. His work bridges statistical rigor with translational applications, aiming to advance precision medicine strategies.

Barış Sürücüمشاهده پروفایل

استاد

• Robust Statistics and Inference
• Statistical Distributions and Applications
• Goodness-of-Fit Tests
• +۱۱ مورد دیگر

Barış Sürücü is a Professor in the Department of Statistics at Middle East Technical University (METU), where he has held academic roles since 2004. He previously served as Deputy Rector at METU (2012-2016) and as a Visiting Professor in the Department of Business at Boğaziçi University (2016-2017). His research spans robust statistics, statistical distributions, goodness-of-fit tests, and applications in reliability engineering, environmental statistics, and big data analytics. PhD in Statistics, METU (2003) MSc in Statistics, METU (1999) BSc in Statistics, METU (1996) His work focuses on developing statistical methods for reliability and survival models, outlier detection, ranked set sampling, and environmental data analysis. His publications address theoretical and applied challenges in goodness-of-fit testing, parameter estimation, and graphical reliability analysis tools. Dr. Sürücü's scientific contributions include 15+ publications in journals such as IEEE Transactions in Reliability and Environmental and Ecological Statistics, with recurring themes in multivariate distribution validation, computational efficiency, and applications to engineering and environmental sciences. Academic Achievement Award, METU (2010) Young Researcher Award, METU Development Foundation (2009) NATO Science Scholarship, TÜBİTAK (2003)

İbrahim Arıkمشاهده پروفایل

مدرس

• Statistical Analysis
• Wind Energy
• Renewable Energy
• +۳ مورد دیگر

Dr. İbrahim Arık is a Lecturer in the Department of Business Administration at the Faculty of Economics and Administrative Sciences, Anadolu Üniversitesi. His research focuses on statistical analysis, wind energy modeling, and advanced distribution theory with applications in renewable energy systems. Educational Background: Bachelor's (Lisans) in Statistics and Computer Science from Kadir Has Üniversitesi (2004-2009) Master's (Tezli Yüksek Lisans) in Statistics from Fen Bilimleri Enstitüsü, Anadolu Üniversitesi (2011-2014) Doctorate (Doktora) in Statistics from Fen Bilimleri Enstitüsü, Anadolu Üniversitesi (2014-2018) Research Interests: İbrahim Arık specializes in statistical distributions (e.g., Weibull, Lindley, Log Logistic) applied to wind energy analysis. His work addresses challenges like non-normal error distributions, heteroscedasticity, and robust estimation techniques in censored data scenarios. He has developed novel methods for wind speed modeling and parameter estimation in renewable energy contexts. Key Projects: Principal researcher in 3 Higher Education Institution-funded projects: 'Sansürlü Regresyon Modelleri: Hata Dağılımının Normal Olmaması ve Değişen Varyans Problemi' (2017–ongoing) 'Yaşam Modelleri ve Uygulamaları' (2016-2010) 'RÜZGAR HIZINI MODELLEMEDE ÖNERİLEN İSTATİSTİKSEL DAĞILIM AİLELERİ...' (2015-2009) Publications: With 22 peer-reviewed articles, his work bridges statistical theory and practical energy applications. Key contributions include new distribution models (e.g., Odd-Burr Rayleigh) and robust estimation frameworks for wind energy systems.

Müjdat Çetinمشاهده پروفایل

استاد

• Signal Processing
• Image Processing
• Data Science
• +۱۲ مورد دیگر

Müjdat Çetin is a Professor of Electrical and Computer Engineering and serves as the Robin and Tim Wentworth Director of the Goergen Institute for Data Science and Director of the New York State Center of Excellence in Data Science at the University of Rochester. He previously held faculty positions at Sabancı University and was a Research Scientist at MIT, with visiting roles at Boston University, Northeastern University, and MIT. Education: PhD in Electrical Engineering, Boston University, 2001 MS in Electrical Engineering, University of Salford, 1995 BS in Electrical Engineering, Boğaziçi University, 1993 His research lies at the intersection of signal processing, machine learning, and data science, with applications in biomedical imaging, radar, and brain-computer interfaces. He develops probabilistic and deep learning models for robust information extraction from noisy and complex data. His work emphasizes computational imaging, sparse representations, and multimodal data fusion. The recent publications reflect a strong trend toward integrating Bayesian methods and deep learning in imaging sciences, particularly in medical image reconstruction, neuroimaging analysis, and radar systems. His group actively explores transformer architectures, federated learning, and model-based deep learning for solving inverse problems in imaging. Scientific Awards and Honors: IEEE Fellow IEEE Signal Processing Society Best Paper Award IET Radar, Sonar and Navigation Premium Award Elsevier Signal Processing Best Paper Award Turkish Academy of Sciences Distinguished Young Scientist Award (GEBİP) ODTÜ Mustafa Parlar Foundation Research Incentive Award TÜBİTAK Career Award Boston University Best Engineering Research Award Professor Cetin has advised numerous PhD and Master’s students and led significant research grants in data science and imaging. He has served as a Senior Area Editor for IEEE Transactions on Image Processing and IEEE Transactions on Computational Imaging, and held editorial roles in several top journals. He has chaired major conferences including ICASSP, ICIP, and IVMSP workshops. He leads a multidisciplinary research group focused on data science and imaging, collaborating with neuroscientists and medical researchers. The team develops novel algorithms for brain-computer interfaces, medical image analysis, and remote sensing systems, often integrating machine learning with physical models of data acquisition.

• Statistics
• Nonlinear Models
• Regression Analysis
• +۷ مورد دیگر

Prof. Müjgan Tez is a distinguished academic in the field of Statistics, currently serving as a Professor at Marmara University, Faculty of Arts and Sciences, Department of Statistics , and concurrently at Işık University, Faculty of Arts and Sciences, Department of Mathematics . Her career spans decades with significant contributions to statistical methodology and applications. Doctorate: Çukurova University, Mathematics (1985) Postgraduate: Ankara University, Mathematics (1982) Undergraduate: Selçuk University, Mathematics (1980) Her research interests include nonlinear models, regression analysis with measurement error, meta-analysis, survival analysis, robust statistics, and time series forecasting. She applies advanced statistical techniques to interdisciplinary problems in medicine, engineering, and public health. The recent publications reflect a strong trend in methodological statistics, particularly in nonlinear and semiparametric modeling, robust regression, and optimization techniques. Her work bridges theoretical statistics with real-world applications, including medical studies on neurosurgery career choices and pandemic forecasting. Scientific awards: Nato Bursları TUBITAK (1990–1991) Advising and grants: She has supervised over 20 graduate theses and led funded research projects such as "Genetic Algorithm and Jackknife Method Combined for Estimating Compartment Model Parameters" (BAP, 2016). Her academic leadership includes multiple terms as Head of Department in both Mathematics and Statistics at Marmara University. She has served on PhD thesis monitoring committees and contributed to numerous international conferences. Labs and teams: While no specific lab name is mentioned, her collaborative work with researchers like Taylan, Yerlikaya-Özkurt, İnan, and Türkşen suggests active participation in statistical research groups focusing on optimization, fuzzy systems, and functional data analysis.

Ali Taylan Cemgilمشاهده پروفایل

دانشیار

• Bayesian Statistics
• Machine Learning
• Time Series Analysis
• +۴ مورد دیگر

Ali Taylan Cemgil is an Associate Professor at Bogazici University's Department of Computer Engineering, College of Engineering. His research focuses on Bayesian statistics, machine learning, and audio/music processing within the Perceptual Intelligence Laboratory (PILAB). PhD in Computer Science from Radboud University Nijmegen (2004) Postdoctoral research at University of Amsterdam (Intelligent Autonomous Systems Lab) and University of Cambridge (Signal Processing and Communications Lab) Research Interests: Bayesian modeling and time series analysis Audio signal processing and source separation Human-AI collaboration frameworks Probabilistic methods in AI reliability and fairness Scientific Contributions: Recent work explores conformal prediction for model calibration, adversarial robustness in deep learning, and fairness-aware medical AI systems. His research spans theoretical foundations in Bayesian statistics and practical applications in indoor localization and capsule robotics. Academic Service: Current faculty member with extensive publications in AI/ML, signal processing, and probabilistic modeling.

Ali Osman ERمشاهده پروفایل

استادیار

• Machining
• Hard-to-Machining Materials
• Metal Matrix Composites
• +۴ مورد دیگر

Dr. Ali Osman ER serves as an Assistant Professor in the Department of Mechanical Engineering at Kırıkkale University's Faculty of Engineering and Natural Sciences, specializing in advanced machining technologies and hard-to-machine materials. His academic journey began with third-place graduation from Kırıkkale University's Mechanical Engineering Department in 1999, followed by research assistantship and subsequent academic promotions. His educational background includes: B.S. in Mechanical Engineering (1999), Kırıkkale University (3rd rank) M.S. in Mechanical Engineering (2003), Kırıkkale University Ph.D. in Mechanical Engineering (2008), Kırıkkale University Postdoctoral Research (2014-2015), Purdue University Dr. ER's research focuses on cutting-edge manufacturing processes including laser-assisted turning of titanium composites, high-speed machining of hardened materials, and sustainable manufacturing techniques. His work bridges theoretical innovation with industrial applications, particularly in domestic manufacturing development. Current research trends show increasing emphasis on machine learning applications for machining optimization, hybrid composite material processing, and environmentally conscious manufacturing methods like Minimum Quantity Lubrication. His scientific recognition includes: TÜBİTAK Postdoctoral Research Scholarship (2014) As an academic leader, Dr. ER has served as Deputy Department Head (2012), Director of Kırıkkale University Hacılar Hüseyin Aytemiz Vocational School (2019-2024), and University Senator. He actively contributes to national manufacturing initiatives through consultancy for İmalET Community, technical expertise for Vocational Qualifications Authority, and evaluation roles for TÜBİTAK and Ministry of Industry. His science communication efforts include TÜBİTAK-organized school talks on National Technology Move. Dr. ER maintains active engagement with student communities through Mechanical Engineering Club and previously co-founded Kırıkkale University Mountaineering Club. His patent applications in Smart Kitchen Systems and Toy Production demonstrate practical technology transfer.

• Applied Statistics
• Operations Research
• Statistical Analysis
• +۳ مورد دیگر

Kamile Şanlı Kula is a Professor at the Department of Mathematics , Faculty of Arts and Sciences , Ahi Evran University , Turkey. She holds a PhD in Statistics (2005) and MSc in Statistics (1999) from Ankara University , and a BSc in Statistics (1997) from Eskişehir Osmangazi University . Her academic career spans institutions including Ankara University (1999-2005) and Eskişehir Osmangazi University (2007). Academic Ranks: Professor (2016–), Associate Professor (2011–), Assistant Professor (2007–2011) Professional Roles: Head of Department (2017–), Faculty Board Member (2016–), Project Evaluation Committee (2015–2019) Her research focuses on Applied Statistics , Operations Research , and Statistical Analysis , with a notable emphasis on Type-2 Fuzzy Logic and Robust Regression techniques. Recent publications address student anxiety, burnout, and life satisfaction, often applying fuzzy logic to handle outliers in datasets. Key projects include studies on cerebrovascular patient anxiety (2017–2019), exam anxiety in 8th-grade students (2017), and vocational school math anxiety (2015–2017). She has supervised 10 master's theses on topics like geometric software impact and educational psychology metrics, collaborating with researchers such as Türkan Erbay Dalkılıç and Ayşen Apaydın. She serves on editorial boards for journals like Journal of Biometry Studies and Mathematical Sciences and Applications E-Notes , and is a member of the Turkish Statistical Association (since 2005) and Statisticians Association (since 1997). Her work integrates statistical methods with psychological and educational applications, particularly in fuzzy logic and outlier-resistant models.

ÖZGÜR GÖLGEمشاهده پروفایل

استاد

• Food Safety
• Food Microbiology
• Milk and Dairy Products Technology
• +۶ مورد دیگر

Özgür Gölge is a Professor at the Department of Gastronomy and Culinary Arts, Faculty of Tourism, Alanya Alaaddin Keykubat University. With a career spanning over two decades, he has held academic positions including Associate Professor (2019–2024) and Doctor Lecturer (2017–2019) at the same institution. Education includes a Doctorate in Food Engineering from Çukurova University (2009–2003), Master's in Food Engineering (2002–1998), and Bachelor's in Food Engineering (1997–1993). His research focuses on Pesticide residue analysis in fruits, vegetables, and dairy Mycotoxin monitoring in cereals and traditional foods Development of QuEChERS and chromatographic methods Food safety in tourism businesses Hygiene practices in culinary operations Recent publications highlight trends in Pesticide contamination in baby foods (2025) Multi-residue detection in apples and mandarins (2023–2024) Mycotoxin exposure through bread and rice (2016) Non-thermal treatment effects on juice safety (2020) Scientific achievements include Second Place in 2023 Social Sciences Academic Achievement Award Leadership in national projects on maximum residue limits (2006–2011) TÜBİTAK and DPT-funded research Administrative roles encompass Erasmus Coordinator (2022–present) Head of Department (2019–2022) Vocational School Director (2019–2022)

Tuğrul TAŞCIمشاهده پروفایل

استادیار

• Artificial Intelligence
• Natural Language Processing
• Computer Vision
• +۳ مورد دیگر

Tuğrul TAŞCI serves as an Assistant Professor in the Department of Information Systems Engineering at Sakarya University's Faculty of Computer and Information Sciences, where he has maintained continuous academic service since 2001. His career progression includes Research Assistant positions across multiple university units before advancing to his current faculty role in 2016. His academic credentials include: Doctorate in Computer and Information Engineering (2014) from Sakarya University Institute of Science, thesis: Real-Time Motion Tracking with Particle Filtering Based on Data Fusing Master's degree in Computer and Information Engineering (2004) with thesis: Design of an Integrated Web-Based Distance Education System Bachelor's degree in Computer Engineering (2001) with thesis: Course Scheduling with Genetic Algorithms Dr. TAŞCI's research centers on Artificial Intelligence applications, particularly Natural Language Processing for Arabic text and Computer Vision . His work integrates particle filtering , data fusion , and optimization algorithms (e.g., Artificial Bee Colony, Firefly) to solve problems in text summarization, motion tracking, and image processing. Recent publications demonstrate expansion into deep learning for industrial defect detection and time series analysis. Analysis of his 2019-2024 publications reveals three dominant research trajectories: (1) Arabic NLP with focus on extractive summarization using PageRank and word embeddings, (2) Computer vision systems for motion tracking and text detection leveraging particle filters and curvature features, and (3) Hybrid optimization techniques applied to diverse domains from emergency management to customer churn prediction. Current academic advising activities and research grant details are not publicly documented in available sources. Similarly, no institutional laboratories or research teams are explicitly associated with his profile in the provided materials.

İlkay Doğanمشاهده پروفایل

دانشیار

• Biostatistics
• Medical Informatics
• Structural Equation Modeling
• +۳ مورد دیگر

Associate Professor İlkay Doğan is affiliated with Gaziantep University, Faculty of Medicine as an Associate Professor in the Department of Basic Medical Sciences . His academic journey includes a PhD in Biostatistics from Eskişehir Osmangazi University (2015), an MSc in Statistics from Afyon Kocatepe University (2012), and a Licence in Mathematics from Balıkesir University (2010). Current Position: Associate Professor, Gaziantep University Academic Rank: Associate Professor Research Interests span biostatistical methodology, medical informatics, structural equation modeling, and sports analytics. He investigates: Statistical models in clinical research Artificial intelligence applications in healthcare Game statistics in professional sports Public health data analysis Bioinformatics in disease diagnosis Sports science and athlete performance Recent Article Trends reflect his expertise in medical AI literacy, structural modeling comparisons, and sports/health data analysis. His work appears in journals like Journal of Medical Screening and European Journal of Therapeutics . Scientific Awards include a TÜBİTAK Domestic Doctoral Scholarship (2015) . He has contributed to 16 funded projects and served as editor for European Journal of Therapeutics .

Mehmet Can Yavuzمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Human-Computer Interaction
• +۳ مورد دیگر

Mehmet Can Yavuz is an Assistant Professor at Işık University's Faculty of Engineering and Natural Sciences, Department of Computer Engineering. As Principal Investigator of the Multimedia Lab, he bridges machine learning with artistic expression through projects like Arky Multimedia, ConvergedMachine, and Duyukoru. His research spans biomedical imaging, human-computer interaction, and cross-modal analysis of multimedia storytelling. 2019-2023: PhD in Computer Science & Engineering, Sabancı University 2010-2016: MS in Physics, Boğaziçi University 2006-2010: BS in Physics, Işık University 2004-2010: BS in Electrical-Electronics Engineering, Işık University Current research explores: Advanced machine learning architectures (Variational Contrastive Learning, Cross-D Convolution) Biomedical imaging applications for disease detection Computational analysis of dramatic/literary works through graph theory and sentiment analysis AI-driven threat detection systems using sensor fusion Creative technology intersections in multimedia production His lab develops frameworks for: Noisy data processing in semi-supervised learning Cross-dimensional knowledge transfer Ensemble approaches in 2D/3D medical imaging Temporal-sentiment analysis of urban events Document embedding-based character analysis Projects include: ARKY MULTIMEDIA - Combining creative exploration with ML DUYUKORU - Machine learning-enhanced sensor threat detection CONVERGEDMACHINE - Multimodal ML research repository He oversees the Işık University Multimedia Lab , which integrates medical image computing with animation production, pushing boundaries in both scientific and artistic domains.

• Natural Language Processing
• Generative AI
• Social Computing
• +۵ مورد دیگر

Cagri Toraman is an Assistant Professor at Middle East Technical University's Computer Engineering Department, leading the Applied NLP Group. He holds a PhD in Computer Science from Bilkent University (2017) and has industry experience as Software Engineer (Havelsan 2017-2018), Postdoctoral Research Scientist (University of Central Florida 2018-2019), and NLP Team Lead (Aselsan 2020-2023). PhD in Computer Science (Bilkent University, 2017) Postdoctoral Research Scientist (University of Central Florida, 2018-2019) NLP Team Lead (Aselsan, 2020-2023) His research focuses on Natural Language Processing , Generative AI , and Social Computing , with particular emphasis on low-resource language adaptation, hate speech detection, multimodal analysis, and misinformation identification. Recent work examines dataset quality evaluation, transformer optimization with tweet-specific elements, and pejorative language disambiguation for misogyny detection. Notable achievements include receiving the Google Gemma Academic Research Award 2024 . He teaches core courses in Data Structures and Applied Natural Language Processing , emphasizing both theoretical foundations and practical implementation. Research trends show expertise across: Multilingual dataset creation (MiDe22, JL-Hate) Transformer-based hate speech detection Generative AI adaptation for Turkish Ensemble learning in socio-political event extraction Contextual word embeddings analysis Conversational system robustness

Mehmet Gönenمشاهده پروفایل

استاد

• Machine Learning
• Computational Biology
• Cancer Biology
• +۳ مورد دیگر

Mehmet Gönen is a Professor in the Department of Industrial Engineering at Koç University's College of Engineering. His academic career spans multiple disciplines at the intersection of engineering, computer science, and biomedical research. He maintains an active research program with significant contributions to machine learning applications in biological and medical contexts. Education: PhD, Boğaziçi University (2010) MSc, Boğaziçi University (2005) BS, Boğaziçi University (2003) Professor Gönen's research primarily focuses on developing and applying machine learning methodologies, particularly multiple kernel learning techniques, to solve complex problems in computational biology and medicine. His work bridges theoretical algorithm development with practical applications in cancer biology, infectious disease modeling, and drug discovery. He has made significant contributions to single-cell multiomics analysis, antibiotic resistance research, and cancer genomics. His methodological innovations in kernel-based machine learning have found applications across diverse biological domains, demonstrating the versatility and power of his computational approaches. Analysis of his recent publications (2022-2025) reveals a consistent research trajectory centered on applying advanced machine learning techniques to pressing biomedical challenges. His work demonstrates strong interdisciplinary collaboration, spanning computational methods development, clinical applications, and biological discovery. Key thematic areas include cancer genomics (particularly pathway analysis and biomarker discovery), infectious disease modeling (with emphasis on antibiotic resistance mechanisms), and methodological innovations in kernel learning for biological data integration. His research has practical implications for precision medicine, drug discovery, and healthcare analytics. Professor Gönen has maintained a robust publication record with significant contributions to both methodology development and domain-specific applications. His work on scMKL for single-cell multiomics analysis represents cutting-edge integration of computational techniques with modern biological data. The consistent focus on interpretable machine learning methods suggests an emphasis on creating tools that provide biological insights rather than just predictive accuracy. His research group appears to collaborate extensively with domain experts in microbiology, oncology, and clinical medicine, ensuring that computational approaches address real-world biomedical challenges.

• Water Quality Assessment
• Environmental Impact Assessment
• Heavy Metal Pollution
• +۴ مورد دیگر

Dr. Ayla BİLGİN is an Associate Professor at Artvin Coruh University, College of Engineering, Department of Environmental Engineering, where she serves as Vice Dean and Department Head. Her academic career spans over two decades with significant contributions to environmental engineering research and education. Education: PhD in Environmental Engineering, Hacettepe University (2004-2011) Masters in Environmental Sciences, Gazi University (2001-2003) Bachelors in Environmental Engineering, Ondokuz Mayıs University (1995-1999) Postdoctoral Research, Princeton University (2016-2017) Dr. BİLGİN's research focuses on water quality assessment, environmental impact analysis, heavy metal pollution, and soil remediation techniques. Her work combines field studies with advanced statistical methods to evaluate environmental systems and develop sustainable solutions. She has pioneered research on phytostabilization techniques for contaminated soils and developed innovative approaches for water quality monitoring in river basins, particularly the Coruh River Basin in Turkey. Her recent publications demonstrate a strong trend toward interdisciplinary environmental research, combining chemical analysis with ecological assessment and statistical modeling. She has made significant contributions to understanding water quality dynamics in coastal and groundwater systems of the Eastern Black Sea Basin and has developed robust methodologies for environmental impact assessment regulation analysis. Scientific Awards: EWRI Visiting International Fellow Award, ASCE (2024) Best Poster Award, BRICS Urbanization Green Innovation Conference (2022) Multiple Publication Incentive Awards from Artvin Coruh University and TÜBİTAK (2014-2018) Young Scientist Paper Award, American Academy of Sciences (2014) Overseas Postdoctoral Research Scholarship, TÜBİTAK (2016) Dr. BİLGİN has supervised multiple graduate theses on environmental impact assessment and water resource management. She has led numerous research projects funded by universities and government agencies, including studies on heavy metal pollution in the Murgul Copper Mine area and water quality assessment in the Coruh River Basin. Her administrative roles include serving on academic promotion committees and faculty management boards, reflecting her leadership in the academic community.