Find Academic Supervisors

• Signal Processing
• Detection Theory
• Modulation Classification
• +4 more

Berkan Dulek is a Professor at the Department of Electrical and Electronics Engineering at Hacettepe University since December 2021. His research focuses on Signal Processing , Detection Theory , and Communication Systems , with applications in Wireless Sensor Networks and Machine Learning . PhD, Electrical and Electronics Engineering, Bilkent University (2012) MS, Electrical and Electronics Engineering, Bilkent University (2006) BS, Electrical and Electronics Engineering, Bilkent University (2003) His work explores optimal signal design, modulation classification, and distributed detection under various constraints (power, secrecy, noise uncertainty). Recent publications address behavioral utility in detection systems, Fano-type bounds in hypothesis testing, and mutual information-based quantizer design . He also investigates power adaptation strategies and stochastic signaling in non-Gaussian noise environments . Key trends in his research include: Optimization of detection and estimation systems under prior uncertainty Machine Learning applications for modulation classification Communication Security via secrecy constraints Information Theory fundamentals in quantizer design Berkan has received multiple awards including the METU Prof. Dr. Mustafa N. Parlar Research Encouragement Award (2020) and TUBITAK Grant No: 215E118 (2019) . He holds a U.S. Patent (9,491,716) in communication control systems.

• Software Testing
• Model-Based Testing
• Software Product Lines
• +7 more

Assoc. Prof. Tugkan Tuglular is affiliated with the Department of Computer Engineering at Izmir Institute of Technology, leading the Safety, Security and Reliability of Software Systems (S2RS2) Laboratory. His research focuses on software testing methodologies, model-based systems, and security applications across software product lines. His work spans formal methods for testing (e.g., event sequence graphs, feature modeling), blockchain-enhanced data sharing, and empirical software engineering. He has extensively studied automated test case generation, change impact analysis, and robustness measurement using Bayesian networks. Notable contributions include domain-specific languages for business applications and frameworks for incremental testing in evolving systems. Recent efforts explore federated platforms for source code quality analysis and AI-driven methods for completing graphical software models. His research integrates theoretical foundations with practical tools, emphasizing security and reliability across diverse software domains. Awards: No specific awards listed. Advising/Grants: No student advising records or grant details provided in the text. His lab (S2RS2) focuses on advancing software safety and security through rigorous testing and modeling approaches. Labs/Teams: Leads the S2RS2 Lab, which investigates software systems' reliability through advanced testing techniques and formal modeling.

Michal ValkoView profile

Researcher

• Reinforcement Learning
• Machine Learning
• Artificial Intelligence
• +3 more

Roles & Affiliations: Michal Valko is the Chief Models Officer at a stealth startup, a tenured researcher at Inria (Inria Lille - Nord Europe), and a lecturer in the MVA Master program at École Normale Supérieure Paris-Saclay. He previously held roles including Principal Llama Engineer at Meta and Senior Staff Research Scientist at Google DeepMind. Education: Ph.D. in Machine Learning from the University of Pittsburgh (2011), Habilitation à Diriger des Recherches (HdR) from École Normale Supérieure Paris-Saclay (2016). Research Interests: Michal focuses on minimizing human supervision in AI systems, including deep reinforcement learning, bandit algorithms, self-supervised learning, and large language models (LLMs). His work emphasizes scalable test-time inference, fine-tuning, and alignment of LLMs. He also explores theoretical foundations of reinforcement learning and representation learning. Awards: Recipient of the Outstanding Paper Award at ICML 2023, Inria's Prime d'Excellence Scientifique (2014–2017 and 2018–2021), Homer Warner Best Paper Award (2010), and Google Best Paper Award (2010). Advising & Grants: Advised over 20 PhD and postdoctoral students, including notable alumni like Daniele Calandriello and Jean Tarbouriech. His research has been supported by grants from ANR (Extra-Learn, BOLD), Intel, and collaborative projects like EduBand with Carnegie Mellon. Labs & Teams: Co-founder of the SequeL team at Inria and a key contributor to the DeepMind Paris and Meta GenAI research groups. Active in organizing conferences like ICML, NeurIPS, and workshops on Graphs in Machine Learning.

• Robust Statistics
• Statistical Modeling
• Multivariate Analysis
• +5 more

Prof. Olçay Arslan is a Professor of Statistics at the Department of Statistics, Faculty of Science, Ankara University. He holds a Doctorate from the University of Leeds (1993) and has held academic positions including Associate Professor at Saint Cloud State University (2001-2003). His research focuses on robust statistical methods, multivariate analysis, and distribution theory with emphasis on heavy-tailed and skewed distributions. He has supervised 23 theses and published over 170 articles in peer-reviewed journals like Journal of Multivariate Analysis and Computational Statistics & Data Analysis . Education: PhD: University of Leeds, UK (1993) MSc: Ankara University (1986) BSc: Ankara University (1983) Key Roles: Head of Department (2014-2023) Member of University Academic Incentive Evaluation Commission (2016-present) Editorial Board member for multiple journals Research Interests: His work centers on robust statistical methodologies addressing outliers and non-normality in data. Notable areas include: Robust estimation techniques Mixture models and clustering Heavy-tailed distributions Regression analysis with autoregressive errors Computational statistics Recent Contributions: Recent studies emphasize: Variable selection in joint mean-covariance models Nonparametric tests for serial independence Robust methods for asymmetric/heteroscedastic data Applications of skew Laplace distributions Grants & Teams: Lead researcher on 4 funded projects. Active member of the Robust Statistics Research Group at Ankara University, collaborating on multidisciplinary data science initiatives.

• Blind Signal Processing
• Bayesian Estimation
• Particle Filters
• +3 more

Ayşın Baytan Ertüzün is a Professor at Boğaziçi University, specializing in signal processing and statistical methodologies. Their research focuses on blind signal processing, Bayesian estimation techniques, particle filters, and seismological applications. They have contributed extensively to defect detection in textiles using advanced signal processing methods like wavelet transforms and independent component analysis, as well as geophysical signal analysis through Bayesian deconvolution approaches. Over 25 years of academic work includes pioneering work in non-Gaussian processes, time-varying autoregressive models, and particle filtering algorithms for complex signal environments. Their research bridges theoretical advancements with practical applications in manufacturing quality control and seismic data analysis. Key technical contributions include hybrid deconvolution methods for Bernoulli-Gaussian processes, subband domain subspace analysis for texture defects, and entropy-based 2D lattice filter structures. Their work often emphasizes robust statistical frameworks for non-stationary and non-Gaussian signal environments, with applications spanning from environmental forecasting (wind speed modeling) to medical signal analysis (respiratory sound coherence). Publications span from foundational 1990s lattice filter innovations to modern Bayesian approaches. Their methodologies are characterized by interdisciplinary fusion of signal processing theory with real-world industrial and geophysical challenges. No specific awards are listed in the provided materials, though their extensive publication record indicates sustained academic impact.

• Biostatistics
• Animal Breeding and Genetics
• Computational Biology
• +5 more

Prof. Mehmet Ziya Firat is a faculty member at Akdeniz University , serving in the Faculty of Agriculture within the Department of Zootechnics and Biometry and Genetics . He holds a doctorate in Statistics from the University of Edinburgh and has held academic positions since 1995, including Professor (2003–present) and Associate Professor (1999–2003) at Akdeniz University. Doctorate: University of Edinburgh (1995), Statistics Postgraduate: University of Reading (1991), Biometry Associate Degree: University of Reading (1990), Biometry Undergraduate: Çukurova University (1986), Zootechnics His research spans Biostatistics , Animal Breeding , and Computational Methods , with over 172 WoS-indexed publications. Key areas include: Bayesian statistical modeling in agriculture Genetic parameter estimation Drying process analysis Clinical and health science applications Multivariate analysis of livestock data Covariance structure modeling Recent articles focus on Bayesian hierarchical models, covariance structures in repeated measures, and applications to Japanese quail growth and agricultural product drying. Collaborations span veterinary sciences, medical informatics, and food technology. He has supervised multiple graduate theses, including PhD projects on genomic evaluation and postgraduate works on milk yield modeling. No scientific awards are explicitly mentioned in the provided text.

Frank ZenkerView profile

Assistant Professor

• Philosophy of Science
• Social Epistemology
• Cognitive Science
• +7 more

Frank Zenker is an Assistant Professor with a Ph.D. from the University of Hamburg. His academic work centers on the philosophy of science, social epistemology, and cognitive science, with strong interdisciplinary engagement in legal reasoning, argumentation theory, and conceptual modeling. He has led research projects funded by TUBITAK and BAP, focusing on models, theories, and theory construction in the behavioral sciences. Research Interests: Philosophy of Science Social Epistemology Cognitive Science Argumentation and Reasoning Conceptual Spaces Bayesian and Legal Reasoning His recent publications reveal a consistent focus on argument structure, debiasing in legal contexts, and the epistemology of scientific practice. He frequently collaborates with scholars like E.H. Witte, Peter Gärdenfors, and C. Dahlman. His work appears in top journals such as Synthese , Argumentation , and Frontiers in Psychology , often addressing methodological issues in empirical psychology and the structure of reasoning. Scientific Contributions: Editor of multiple volumes in the Synthese Library series Guest editor for special issues in Argumentation , Topoi , Synthese , and Erkenntnis Author of books on ceteris paribus conditions and Bayesian argumentation He has taught courses such as Logic I, Philosophy of Science, and Meta-Analysis. While his current institutional affiliation is not explicitly stated, his TUBITAK project suggests a position in Turkey. He maintains an active research profile with a strong publication output and editorial leadership in his field.

Ceylan Talu YozgatlıgilView profile

Professor

• Time Series Analysis
• Machine Learning
• Data Science
• +4 more

Dr. Ceylan Talu Yozgatlıgil is a Professor at the Department of Statistics, Middle East Technical University (METU), where she has served since 2007. She earned her Ph.D. in Statistics from Temple University (2007), M.S. (1999) and B.S. (1996) from METU. Her roles include Vice Chairperson of the Department (2020–present) and former Associate Director of the Institute of Applied Mathematics (2017–2020). Education: Ph.D. in Statistics, Temple University (2007) M.S. in Statistics, METU (1999) B.S. in Statistics, METU (1996) Her research spans Time Series Analysis , Machine Learning , and Applied Statistics , with recent work on drought forecasting, comorbidity modeling, and Industry 4.0 production efficiency. Her 15 most recent articles reflect expertise in hybrid forecasting methods, copula modeling, and spatio-temporal analysis. Scientific Awards include the THD Clinical Hematology Paper Award (2007), TÜBİTAK Publication Support (2004, 2009), and a Full Time Doctorate Scholarship (2001–2006). She has developed advanced courses in time series and statistical computing, and her collaborations span actuarial science, climate research, and biomedical studies.

Pelin AtahanView profile

Assistant Professor

• Online Personalization
• E-commerce
• Recommendation Systems
• +2 more

Pelin Atahan is an Assistant Professor in the Department of Management Information Systems at Özyeğin University. She holds a PhD in Management from the University of Texas at Dallas (2009) and an MBA from the University of Georgia (2003), with a Bachelor's degree in Management from Boğaziçi University (1998). PhD: University of Texas at Dallas, Management (2009) MBA: University of Georgia (2003) BA: Boğaziçi University, Management (1998) Her research focuses on online personalization, e-commerce recommendation systems, and user profile learning , with a particular emphasis on optimizing offer sets and improving website interactions for faster profile acquisition. Her work bridges theoretical advancements in machine learning with practical applications in digital marketing and consumer behavior. Notable research trends include algorithmic optimization for personalized recommendations , probabilistic modeling of user behavior, and strategic learning frameworks for recommendation systems. Key methodologies span data science, behavioral economics, and human-computer interaction. She teaches courses such as Introduction to Information Systems and Technologies (MIS101) , Database Management (MIS102) , and Enterprise Resource Planning Systems with SAP (OPER412) , integrating her expertise in MIS into both undergraduate and graduate curricula.

• Bayesian Statistics
• Signal Processing
• Mathematical Modeling
• +6 more

Dr. Mehmet Cevri is an Assistant Professor at Istanbul University's Faculty of Science, Department of Mathematics, where he has been serving since 2011. He specializes in Bayesian statistical methods, signal processing, and mathematical modeling with applications spanning from genetics to engineering. Education: 2003-2009: Doctorate in Mathematics/Applied Mathematics, Marmara University Institute for Graduate Studies in Pure and Applied Sciences 1999-2002: Postgraduate in Mathematics/Applied Mathematics, Marmara University 1995-1999: Undergraduate in Mathematics Education, Marmara University Ataturk Faculty of Education Research Focus: Dr. Cevri's research encompasses a broad spectrum of mathematical and computational methods, with particular emphasis on Bayesian inference and signal processing . His work includes developing sophisticated algorithms for extracting sinusoidal signals from noisy data, analyzing genetic traits using Bayesian methods, and applying mathematical clustering techniques to biological data. His expertise extends to optimization techniques, stochastic processes, and numerical analysis. His recent publications demonstrate a consistent focus on Bayesian approaches to signal processing problems , particularly in recovering sinusoids from noisy environments. He has also applied his mathematical expertise to biological problems, including the analysis of ostracoda habitat preferences and genetic trait transmission probabilities. Research Projects: 2015: "Bayesian Estimates of Genetic Characters" (Project Executive) 2012-2014: "Family Tree Analysis with Bayesian Logical Inference Method" (Project Executive) 2013: "Performance Analysis of Gibbs Sampling in Bayesian Inference of Sinusoids" (Project Executive) 2010-2013: "Positron Lifetime Spectrum Analysis with Bayesian Statistical Inference" 2007-2010: "Bayesian Spectrum Estimation of Harmonic Signals" 2007-2010: "Bayesian Model Selection and Parameter Estimation" Teaching and Supervision: Dr. Cevri teaches a variety of mathematics courses ranging from foundational mathematics to specialized topics like integral transforms and Bayesian data analysis. He has supervised multiple thesis students including F. Fırat and E. Serhan, contributing to the development of future researchers in mathematical sciences.

• Structural Engineering
• Seismic Response Analysis
• Structural Control Systems
• +4 more

Gürsoy Turan is an Assistant Professor in the Department of Civil Engineering at Izmir Institute of Technology (IYTE). His research focuses on structural dynamics, seismic response control, and vibration damping technologies. He completed his B.S. and M.S. at Orta Doğu Teknik Üniversitesi and his PhD at the University of Illinois at Urbana-Champaign. Key research areas include seismic mitigation using tuned mass dampers, Bayesian-based structural model updating, and structural health monitoring. His work addresses challenges in tall building design, cable-stayed bridges, and soil-structure interaction effects. He has contributed to advancing methodologies for modal parameter identification and active/passive control strategies. Publications highlight innovations in damping systems, data merging algorithms, and benchmark control problems for infrastructure resilience. His research bridges theoretical advancements with practical engineering solutions for earthquake-resistant structures.

• Philosophy of Science
• Early Modern Philosophy
• Scientific Explanation
• +3 more

Alireza Fatollahi is an Assistant Professor at Bilkent University's Department of Philosophy. He holds a Ph.D. in Philosophy from Princeton University. His research focuses on Philosophy of Science and Early Modern Philosophy, particularly Leibniz and Newton. He applies statistical methods to address questions about scientific explanation and epistemology. He co-organized the inaugural Princeton-Bilkent Workshop on the History and Philosophy of Science with Dan Garber. Education: Ph.D. in Philosophy, Princeton University Research Interests: Statistical approaches to philosophy of science Leibniz's modal metaphysics and theories of free action Newton's epistemological framework Model selection criteria (e.g., AIC/BIC) Scientific realism and the No Miracle Argument Publications: Focus on journals like Canadian Journal of Philosophy , Episteme , and Philosophy of Science , addressing topics ranging from Bayesian methods to historical figures like Leibniz and Newton. Awards/Grants: No awards explicitly mentioned. Active in academic events like the Princeton-Bilkent Workshop. Labs/Teams: Organized interdisciplinary workshops and participates in reading groups (e.g., Natural Philosophy).

• First and second language acquisition
• Childhood bilingualism
• Reading acquisition
• +2 more

Belma Haznedar is a full Professor at Boğaziçi University's Faculty of Education, Department of Applied Linguistics. She holds a Ph.D. in Linguistics from Durham University and specializes in childhood bilingualism, language acquisition, and literacy development. Her research examines cognitive and linguistic aspects of bilingual education, particularly in Turkish-speaking populations. Education includes: Ph.D. in Linguistics, University of Durham (1997) M.A. in Applied Linguistics, University of Durham (1992) B.A. in English Language Education, Hacettepe University (1989) Her research explores morphosyntactic development in bilingual children, reading acquisition in transparent orthographies, and teacher training for migrant populations. Recent work focuses on developing digital tools for heritage language preservation and literacy assessment frameworks. Publications demonstrate sustained focus on bilingual cognition, with recent trends emphasizing technology-mediated language learning and cross-cultural educational strategies. She has advised 12+ graduate students on topics spanning reading acquisition, spelling development, and bilingual literacy. Active in EU-funded projects including EU-SPEAK-3 (migrant teacher training) and COST Action ELN (European Literacy Network). Collaborates with international researchers on multilingual education policy.

• Speech Processing
• Natural Language Processing
• Machine Learning
• +3 more

Murat Saraçlar is a full professor at the Electrical and Electronic Engineering Department of Boğaziçi University. He holds a B.S. from Bilkent University (1994), and M.S.E. and Ph.D. degrees from Johns Hopkins University (1997, 2001). Before joining Boğaziçi in 2005, he worked at AT&T Labs Research (2000–2005). He has held visiting positions at Google (2011–2012) and IBM T.J. Watson Research Center (2012–2013). Affiliations: Editorial roles include IEEE Transactions on Audio, Speech, and Language Processing (Senior Area Editor), and Computer Speech & Language (Editorial Board). Research Interests: Speech Processing, Natural Language Processing, Machine Learning, and Artificial Intelligence. His work focuses on speech recognition, keyword search, and medical signal analysis. Over 100 publications span journals like IEEE/ACM Transactions on Audio, Speech, and Language Processing. Awards include TÜBA-GEBİP Young Scientist Award (2009) and IBM Faculty Award (2010). Recent articles emphasize multimodal systems, unsupervised learning, and medical diagnostics. His contributions bridge theoretical advancements with practical applications in healthcare and communication systems.

Vilda PurutçuoğluView profile

Professor

• Bioinformatics
• Systems Biology
• High Dimensional Data
• +2 more

Prof. Vilda Purutçuoğlu is a Professor in the Department of Statistics at Middle East Technical University (METU). Her academic career includes roles as Assistant Professor (2010–2012), Associate Professor (2012–2018), and Professor since 2018. She holds a Ph.D. from Lancaster University (2007) and has affiliations with the Department of Biomedical Engineering, Institute of Applied Mathematics, and Informatics Institute at METU. Her research focuses on bioinformatics, systems biology, high-dimensional data analysis, neuroscience, and social statistics . Key professional roles include Head of the Department of Statistics (since 2025), Chair of the Award Fund Committee at the International Biometric Society (since 2022), and Editorial roles in journals like BMC Bioinformatics. She has led projects on topics ranging from family dynamics to outlier detection in biomedical data, funded by TÜBİTAK and METU. Prof. Purutçuoğlu has been recognized with multiple Academic Performance Awards (2011–2022 excluding 2020) and was a finalist for the Sabri Ülker Science Award (2015). She collaborates internationally, including a Global Engagement Fellowship (2024–2025) at University College London and research at Università Della Svizzera Italiana (2024). Her publications span books on operations research and bioinformatics, and she actively supervises projects and students in interdisciplinary areas like biomedical engineering and computational statistics.