İnci Batmaz

Professor İnci Batmaz, affiliated with the Department of Statistics at Middle East Technical University (METU), has held her current academic rank since 2012. She is also an affiliated faculty member of METU's Institute of Applied Mathematics (Financial Mathematics Program) and has served in administrative roles such as Chair of the Department of Statistics and Administrative Coordinator for institutional development initiatives.

• Ph.D. in Computer Engineering, Ege University (1993)
• Ph.D. Dissertation at Carnegie-Mellon University (Fulbright Scholar, 1988-1991)
• M.S. in Computer Engineering, Ege University (1986)
• B.S. in Statistics, METU (1984)

Her research spans Data Science, Machine Learning, and Computational Statistics with applications in Environmental Statistics, Quality Improvement, and Financial Analytics. Key methodologies include Response Surface Methodology, Design of Experiments, and advanced regression splines (MARS, CMARS, RCMARS). She has made significant contributions to statistical modeling of climate patterns, financial systems, and industrial quality control.

Recent publications focus on regression splines for predictive modeling (2021), climate change analysis (2016), robust statistical methods under uncertainty (2011), and machine learning applications in finance and environmental science. Her work emphasizes both theoretical developments and real-world implementations across diverse domains.

Scientific Awards
• TÜBİTAK International Post-Doctoral Fellowship (2016-2017)
• Multiple METU Faculty Performance Awards (2003-2013)
• Best MSc Thesis Awards (2009, 2012) as co-advisor
• Fulbright Doctoral Scholarship (1988-1991)
• Seven TÜBİTAK research grants and publication supports

She has advised two MSc students to award-winning theses and collaborated with international researchers including Prof. Gerhard W. Weber. Her professional experience includes visiting positions at Imperial College London and Tilburg University, along with board memberships in academic institutions like the Graduate School of Natural and Applied Sciences.