Software and AI engineer with a background in computational mechanics and scientific computing, experienced in developing machine learning workflows and data-driven engineering solutions.
Passionate about applied AI, optimization, and scalable computational technologies.
The curriculum focuses on solving complex engineering and scientific problems using numerical methods, data-driven modeling, and computational algorithms.
Core areas include machine learning, scientific programming, software development, and physics-based simulation.
MathWorks March 2020 – January 2021 Aim: The use of autonomous vehicles is increasing, and driverless races are starting to take form. …
BMW November 2022 – February 2023 The final report can be found on TUM wiki: https://wiki.tum.de/display/modsim/Error+Estimators+for+pMOR
Machine Learning Module June 2021 – July 2021 Aim: A comparison between closed-form results vs Iterative approaches like EM algorithm for: Final …
Publisher: Elsevier B.V. URL: https://doi.org/10.1016/j.procir.2023.01.016 8 July 2023 Abstract: Future vehicles are connected, autonomous and shared platforms that render a multitude of …