Sai Karthikeya Vemuri, M.Sc.
| Address: | Computer Vision Group |
| Department of Mathematics and Computer Science | |
| Friedrich Schiller University of Jena | |
| Ernst-Abbe-Platz 2 | |
| 07743 Jena | |
| Germany | |
| Phone: | +49 (0) 3641 9 46416 |
| E-mail: | sai (dot) karthikeya (dot) vemuri (at) uni-jena (dot) de |
| Room: | 1212 |
| Links: |
Curriculum Vitae
| 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 | |
| Research topic: “MELODI: Machine-learning-based analysis of fan noise source dependencies on aerodynamic | |
| inlet disturbances” | |
| 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 |
Research Interests
- Applied DL/ML in Physics and Engineering
- Knowledge Integration
- Causality
Projects
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. These physical relationships have not yet been investigated using the modern methods that have been developed in the field of artificial intelligence and machine learning. Existing methods for the integration of prior knowledge into machine learning procedures, as well as causality investigations are tested and extended for this specific application domain.