Adversarially Robust Speech Recognition
ISCA SIGML Seminar Series 2021
My research includes all kinds of attacks against machine learning models, including adversarial examples and poisoning attacks with a focus on signal-driven input data like audio and speech by utilizing approaches based on signal processing. I aim to develop domain-adaptive detection mechanisms and countermeasures, e.g., for Deepfakes and adversarial examples.
During my Ph.D., I focused on the robustness of neural networks and the security of speech-based systems. I received my Ph.D. in 2021 from Ruhr University Bochum, where I was advised by Prof. Dr.-Ing. Dorothea Kolossa at the Cognitive Signal Processing group at Ruhr University Bochum (RUB), Germany. I received two scholarships from UbiCrypt (DFG Research Training Group) and CASA (DFG Cluster of Excellence).
I obtained my Master's degree in Electrical Engineering and Information Technology at RUB in 2015 after graduating from the University of Applied Science in Mannheim in Biomedical Engineering.