معرفی
Asja Fischer is a Professor at the Faculty of Computer Science, Ruhr-University Bochum. Her research focuses on machine learning, adversarial robustness, deepfake detection, and generative models.
- Assistant Professor at RUB (previous)
- Akademische Rätin at Bonn University (previous)
- Post-doctoral researcher at MILA
Her work explores uncertainty quantification, stochastic neural networks, and federated learning. Recent studies analyze adversarial attacks on diffusion models, semantic watermarks, and robustness in AI-generated image detectors.
Key trends in her publications include:
- Adversarial robustness in computer vision and speech recognition
- Deepfake detection using autoencoder reconstruction and frequency analysis
- Uncertainty estimation for improving model reliability
- Security challenges in diffusion and autoregressive models
She has no publicly listed scientific awards or student advising records in the provided texts.
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