Serkan Kir is an Assistant Professor in the Department of Molecular Biology and Genetics at Koc University. His research focuses on cancer cachexia, metabolism in oncology, and the physiological interactions between adipose tissue and skeletal muscle. He obtained his PhD from UT Southwestern Medical Center (2011) and a Bachelor's degree from Bilkent University (2006). Education: PhD, UT Southwestern Medical Center, 2011 Bachelor's Degree, Bilkent University, 2006 Research Interests: Cancer cachexia, metabolism, and tissue physiology are central themes in his work. He investigates: Mechanisms of tumor-induced muscle wasting Adipose tissue thermogenesis and browning Cytokine signaling (e.g., interleukin-6 family, Oncostatin M) Role of EDA2R-NIK and PTHrP pathways in cachexia Epigenetic and transcriptional regulation in metabolic disorders Therapeutic targeting of HDACs and receptor signaling Recent Publication Trends: His work spans translational cancer biology, metabolic reprogramming during cachexia, and receptor-ligand interactions driving tissue wasting. Key areas include fibroblast growth factor signaling, bile acid metabolism, and interventions for Duchenne muscular dystrophy.
Associate Professor RECEP BİNDAK is a faculty member at Gaziantep University's Faculty of Education, Department of Mathematics and Science Education. With a Doctorate in Mathematics from Dicle University (2004), he has built an extensive academic career spanning over two decades, including positions at Mardin Artuklu University and Gaziantep University's Technical Sciences Vocational School. His educational background includes a Doctorate (2000-2004) from Dicle University's Institute of Sciences in Mathematics, a Master's degree (1994-1997) from Yuzuncuyil University's Institute of Sciences in Mathematics, and a Bachelor's degree (1987-1991) in Mathematics Teaching from Dicle University's Faculty of Education. BINDAK's research focuses on mathematics education, statistics, and educational psychology, with particular emphasis on mathematical self-efficacy, problem-solving attitudes, measurement techniques, and quantitative research methods. His work bridges theoretical statistical concepts with practical educational applications, making significant contributions to both fields. He has published extensively on topics ranging from mathematical justification skills in middle school students to psychometric properties of Likert scales and teacher burnout predictors. His recent publications (2018-2024) reveal a strong trend toward interdisciplinary research combining mathematics education with psychological factors affecting student performance. The majority of his work centers on middle school mathematics education, examining variables like self-efficacy, problem-solving attitudes, and mathematical justification skills. He also maintains active research in statistical methodology, particularly in bootstrap methods and nonparametric techniques, demonstrating his dual expertise in both educational theory and quantitative analysis. TUBITAK Publication Incentive Award (2011) TUBITAK Publication Incentive Award (2012) Professor BINDAK has supervised 22 graduate theses (1 doctoral and 21 master's), reflecting his commitment to mentoring the next generation of researchers. His students have explored diverse topics within mathematics education, including mathematical connection self-efficacy, geometric justification skills, and the relationship between school climate and teacher burnout. His teaching portfolio spans doctoral, master's, undergraduate, and associate degree levels, with courses focused on statistics, probability, data analysis, and mathematical research methods. As evidenced by his extensive publication record and thesis supervision, Professor BINDAK maintains an active research laboratory focused on quantitative educational research, with particular attention to measurement theory, statistical methodology in education, and mathematics learning processes. His work continues to influence both educational practice and research methodology in Turkey's academic community.
Mélisande Albert is an Associate Professor in Mathematics at INSA Toulouse, working in the Department of Mathematical Engineering and Modeling (GMM). She is also a member of the Toulouse Institute of Mathematics (IMT) at Paul Sabatier University (UPS). Her educational background includes: PhD in Mathematics from University of Nice Sophia Antipolis (2015), with thesis titled "Tests of independence by bootstrap and permutation: an asymptotic and non-asymptotic study. Application to Neurosciences" Master's degree in Mathematics, specialization Research (2012) Admission to the External Agrégation of Mathematics (2011, rank: 47/288) Bachelor's degree in Mathematics from University of Nice Sophia Antipolis (2009) Dr. Albert's research focuses on developing and analyzing statistical methods for independence testing and resampling techniques. Her work bridges theoretical statistics with practical applications, particularly in neuroscience. She investigates non-parametric tests of independence using bootstrap and permutation approaches, studies concentration inequalities for randomly permuted sums, and applies these methods to analyze spike train data in neuroscience to detect neural synchrony. Her research spans from theoretical foundations to practical implementations, with contributions to both statistical theory and neuroscience applications. Her scientific achievements include: Marie-Jeanne Laurent-Duhamel Award from the French Society of Statistics (SFdS) for her doctoral thesis Dr. Albert serves as a reviewer for the Journal of Machine Learning Research and Computation Statistics and Data Analysis. She has supervised student projects at INSA Toulouse and has been involved in the ANR Project SansSouci (2018-2020). She is an elected member of the French Statistical Society Mathematical Statistics group committee. She is an active member of the Statistics and Optimization team and the Mathematics and Biology research group at the Institute of Mathematics of Toulouse (IMT). She has co-organized several scientific events including the weekly Statistical Seminar at IMT (2018-2022), the Journées de Statistique Mathématique at the Henri Poincaré Institute in Paris (2018), and the "Post-selection inference and multiple testing" Workshop in Toulouse (2018).
Prof. Dr. İbrahim Halil GÜMÜŞ is a distinguished faculty member at Adıyaman University, Faculty of Arts and Sciences, Department of Mathematics, where he currently holds the position of Professor (since 2023). Previously, he served as Associate Professor (2017-2023) and Assistant Professor (2011-2017) at the same institution. Before his academic career, he worked as a Teacher at Public Schools under the Ministry of National Education from 2002 to 2011. He earned his educational qualifications from Selçuk University: B.Sc. in Mathematics (1998-2002), M.Sc. in Mathematics (2002-2005), and PhD in Mathematics (2005-2011). His Master's Thesis focused on 'On the Hadamard Product of Matrices' (2005), while his PhD Thesis examined 'Bounds on arithmetic, geometric and Heinz means of positive definite matrices' (2011). Prof. GÜMÜŞ's research primarily centers on Matrix Theory and Operator Inequalities, with significant contributions to Positive Operators, Matrix Analysis, and Optimization. His work demonstrates a strong theoretical foundation in mathematical inequalities with increasing applications in data science and medical informatics. He has published extensively in high-impact journals such as Linear and Multilinear Algebra, Journal of Mathematical Analysis and Applications, and Operators and Matrices. His publication record shows a clear evolution from theoretical matrix inequalities toward practical applications in data analysis, particularly evident in his recent work on synthetic data generation for imbalanced datasets using geometric means and Heinz averages. This interdisciplinary approach bridges pure mathematics with machine learning applications, especially in medical data analysis. TÜBİTAK Publication Incentive Award, 2012 TÜBİTAK Publication Incentive Award, 2015 TÜBİTAK Publication Incentive Award, 2017 TÜBİTAK Publication Incentive Award, 2018 TÜBİTAK Publication Incentive Award, 2019 TÜBİTAK Publication Incentive Award, 2021 Prof. GÜMÜŞ has successfully supervised multiple Master's theses on topics including inequalities for positive multilinear mappings, geometric inequalities via majorization methods, determinants of positive semi-definite matrices, and mathematical approaches to synthetic data sampling. He serves as a referee for prestigious journals including Journal of Inequalities and Applications and Mathematical Reviews/MathSciNet. His administrative roles include Farabi Coordinator, Erasmus Coordinator, Bologna Coordinator for both the Faculty of Arts and Sciences and Institute of Science, and Mevlana Exchange Program Institutional Coordinator. His work bridges theoretical mathematics with practical applications in data science, particularly in addressing challenges related to imbalanced datasets in medical informatics through innovative mathematical approaches.
Alper Kürşat Uysal is an Associate Professor of Computer Engineering at Alanya Alaaddin Keykubat University. His research develops advanced text classification algorithms and feature selection methods, with applications ranging from spam detection to educational analytics. Research foci: Novel feature selection metrics for text data Imbalanced text classification techniques Short text analysis methodologies Multilingual spam detection systems Affective computing in educational contexts Uysal's publications introduce innovative approaches to feature selection, including the Extensive Feature Selector method and specialized metrics for short text datasets. His work addresses practical challenges in Turkish-language social media content moderation and develops automatic classification systems for educational applications. Recent research examines how feature selection impacts classifier performance on imbalanced text corpora.
