Seyhan Sahin Claeys

Seyhan Sahin Claeys is a mathematics instructor and AI researcher with a PhD in Mathematics from Gebze Technical University, Turkey (2011), specializing in matrix analysis and convex geometry. She conducted postdoctoral research at LAAS-CNRS, France (September 2012 - November 2013), on semidefinite programming duality and facial reduction algorithms in conic optimization, supported by a TÜBİTAK International Postdoctoral Research Fellowship. Her doctoral research focused on the geometric characterization of feasibility regions in Linear Matrix Inequalities (LMIs) for systems and control theory. She currently extends this work to machine learning by integrating LMI-based structural constraints into neural network training to enhance the reliability and robustness of AI models while avoiding the computational burden of traditional semidefinite programming solvers. Alongside her research, she has extensive teaching and mentoring experience in mathematics, including university-level instruction. https://github.com/SeyhanSahin