* F-INR: Functional Tensor Decomposition for Implicit Neural Representations. Accepted at WACV 2026.
Research Experience
- Project: MELODI - Machine-learning-based analysis of fan noise source dependencies on aerodynamic inlet disturbances. Development and testing of machine learning methods to investigate dependencies of fan noise sources on aerodynamic inflow disturbances.
Education
- Since 2022, PhD Student, Computer Vision Group, Friedrich Schiller University Jena, Data Analysis and Intelligence Group, German Aerospace Center (DLR), Institute for Data Science, Jena
- 2019 – 2022, Masters in Computational Materials Sciences, TU Bergakademie Freiberg. Master Thesis: 'Machine Learning assisted understanding of RVE size dependent uncertainties and corresponding hierarchy of properties'
- 2015 – 2019, Bachelors in Mechanical Engineering, Osmania University, Hyderabad, India
Background
Research interests include: Applied DL/ML in Physics and Engineering, Knowledge Integration, Causality.