Teodor Rotaru is a PhD-trained numerical optimization specialist with about a decade of experience bridging rigorous mathematical analysis and high-performance scientific software development. His doctoral work at KU Leuven and UCLouvain resolved longstanding worst-case performance questions for gradient descent and produced exact analyses for several first-order methods, combining theory with implementations in C++, Python, and MATLAB. He has a strong background in numerical linear algebra, simulation and control, and a track record of turning analytical insights into reliable, performance-oriented code useful for engineering and data-driven R&D. Comfortable in both academic and applied settings, he seeks industry research roles where algorithm design and production-quality scientific software meet challenging real-world problems. An uncommonly practical theorist, he focuses on deliverable results—provable bounds that inform implementable methods.
10 years of coding experience
5 years of employment as a software developer
Doctor of Engineering, Numerical Optimization Methods, Doctor of Engineering, Numerical Optimization Methods at KU Leuven
Doctor of Philosophy - PhD, Numerical Optimization Methods, Doctor of Philosophy - PhD, Numerical Optimization Methods at Université catholique de Louvain
Master of Science - MS, Computational Science and Engineering, Master of Science - MS, Computational Science and Engineering at Technical University of Munich
POLITEHNICA București National University for Science and Technology
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