Seyhan Sahin Claeys

Seyhan Sahin Claeys is a mathematics instructor and AI researcher with a PhD in Mathematics from Gebze Technical University, Turkey (2011). Her doctoral research focused on the geometric and structural properties of the feasibility regions of linear matrix inequalities (LMIs), including their partial characterization through conic constructions. 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.

Recently, she developed an energy forecasting project at CETIC ICT in Belgium using deep learning architectures to predict household energy consumption. The project link is: https://github.com/SeyhanSahin. She currently extends this work 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.