Ruhr-University Bochum
Faculty of Computer Science
Machine Learning
Universitätsstr. 150

44801 Bochum

 

Room:  MC 5.124

Tel:      +49 (0)234 32-23207

E-Mail: asja.fischer@rub.de

Office hours: By Arrangement

About Me

Before becoming a professor in Bochum I was an assistant professor at RUB, Akademische Rätin (assistant professor) at Bonn University, and a post-doctoral researcher at the Montreal Institute for Learning Algorithms (MILA). Between 2010 and 2015, I was employed both at the Institute for Neural Computation at the Ruhr-University Bochum and the Department of Computer Science at the University of Copenhagen working on my PhD, which I defended in Copenhagen in 2014. Before, I studied Biology, Bioinformatics, Mathematics and Cognitive Science at the Ruhr-University Bochum, the Universidade de Lisboa, and the University of Osnabrück.

Publications

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2026

Simon Damm, Jonas Ricker, Henning Petzka, Asja Fischer

PRADA: Probability-Ratio-Based Attribution and Detection of Autoregressive-Generated Images Proceedings Article

In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Findings, 2026.

Links

Sandra Höltervennhoff, Jonas Ricker, Maike M. Raphael, Charlotte Schwedes, Rebecca Weil, Asja Fischer, Thorsten Holz, Lea Schönherr, Sascha Fahl

"That's another doom I haven't thought about": A User Study on AI Labels as a Safeguard Against Image-Based Misinformation Proceedings Article

In: CHI Conference on Human Factors in Computing Systems (CHI), 2026.

Links

Denis Lukovnikov, Andreas Müller, Erwin Quiring, Asja Fischer

ClusterMark: Towards Robust Watermarking for Autoregressive Image Generators with Visual Token Clustering Proceedings Article

In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.

Links

Sina Mavali, Jonas Ricker, David Pape, Asja Fischer, Lea Schönherr

Adversarial Robustness of AI-Generated Image Detectors in the Real World Artikel

In: International Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 2026.

Links

Karla Pizzi, Matías Pizarro, Asja Fischer

Comparative Study on Noise-Augmented Training and its Effect on Adversarial Robustness in ASR Systems Artikel

In: Computer Speech & Language, 2026.

Links

2025

Simon Damm, Asja Fischer, Alexander May, Soundes Marzougui, Leander Schwarz, Henning Seidler, Jean-Pierre Seifert, Jonas Thietke, Vincent Quentin Ulitzsch

Solving Concealed ILWE and its Application for Breaking Masked Dilithium Proceedings Article

In: Advances in Cryptology (ASIACRYPT 25), 2025.

Links

Simon Damm, Asja Fischer, Alexander May, Soundes Marzougui, Leander Schwarz, Henning Seidler, Jean-Pierre Seifert, Jonas Thietke, Vincent Quentin Ulitzsch

Solving Concealed ILWE and Its Application for Breaking Masked Dilithium Proceedings Article

In: International Conference on the Theory and Application of Cryptology and Information Security (ASIACRYPT), 2025.

Links

Simon Damm, Mike Laszkiewicz, Johannes Lederer, Asja Fischer

AnomalyDINO: Boosting Patch-based Few-shot Anomaly Detection with DINOv2 Proceedings Article

In: IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025.

Links

Zahra Dehghanighobadi, Asja Fischer, Muhammad Bilal Zafar

Can LLMs Explain Themselves Counterfactually? Proceedings Article

In: Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025.

Links

Sina Däubener, Simon Damm, Asja Fischer

ELBO, Regularized Maximum Likelihood, and Their Common One-Sample Approximation for Training Stochastic Neural Networks Proceedings Article

In: Conference on Uncertainty in Artificial Intelligence (UAI), 2025.

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Hicham Eddoubi, Jonas Ricker, Federico Cocchi, Lorenzo Baraldi, Angelo Sotgiu, Maura Pintor, Marcella Cornia, Lorenzo Baraldi, Asja Fischer, Rita Cucchiara, Battista Biggio

RAID: A Dataset for Testing the Adversarial Robustness of AI-Generated Image Detectors Artikel

In: arXiv Preprint, 2025.

Links

Florian Lam, Simon Damm, Asja Fischer, Thomas Heinze

Exploring the Potential and Limitations of Machine Learning for Forecasting Groundwater Recharge from Meteorological Time Series Proceedings Article

In: AGU Annual Meeting, 2025.

Links

Denis Lukovnikov, Asja Fischer

Enabling ControlNet to follow Localized Descriptions Using Cross-Attention Control Proceedings Article

In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2025.

Links

Denis Lukovnikov, Andreas Müller, Jonas Thietke, Erwin Quiring, Asja Fischer

Are Semantic Watermarks for Diffusion Models Resilient to Layout Control? Proceedings Article

In: International Conference on Learning Representations (ICLR) Workshops, 2025.

Links

Laura Manduchi, Clara Meister, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard Melo, Eric Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van Broeck, Julia E Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin

On the Challenges and Opportunities in Generative AI Artikel

In: arXiv Preprint, 2025.

Links

Andreas Müller, Denis Lukovnikov, Jonas Thietke, Asja Fischer, Erwin Quiring

Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models Proceedings Article

In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.

Links

Matías Pizarro, Mike Laszkiewicz, Dorothea Kolossa, Asja Fischer

Lightweight Model Attribution and Detection of Synthetic Speech via Audio Residual Fingerprints Artikel

In: arXiv Preprint, 2025.

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Jens Püttschneider, Simon Heilig, Asja Fischer, Timm Faulwasser

Towards the Optimal Control Perspective of ResNet Training Proceedings Article

In: International Conference on Machine Learning (ICML) Workshops, 2025.

Links

Jonas Thietke, Andreas Müller, Denis Lukovnikov, Asja Fischer, Erwin Quiring

Towards a Correct Usage of Cryptography in Semantic Watermarks for Diffusion Models Proceedings Article

In: International Conference on Learning Representations (ICLR) Workshops, 2025.

Links

2024

Linara Adilova, Bernhard C. Geiger, Asja Fischer

Information Plane Analysis for Dropout Neural Networks Proceedings Article

In: International Conference on Learning Representations (ICLR), 2024.

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Sina Mavali, Jonas Ricker, David Pape, Asja Fischer, Lea Schönherr

Adversarial Robustness of AI-Generated Image Detectors in the Real World Artikel

In: arXiv Preprint, 2024.

Links

Sina Däubener, Kira Maag, David Krueger, Asja Fischer

Integrating uncertainty quantification into randomized smoothing based robustness guarantees Artikel

In: arXiv Preprint, 2024.

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Joel Frank, Franziska Herbert, Jonas Ricker, Lea Schönherr, Thorsten Eisenhofer, Asja Fischer, Markus Dürmuth, Thorsten Holz

A Representative Study on Human Detection of Artificially Generated Media Across Countries Proceedings Article

In: IEEE Symposium on Security and Privacy (SP), 2024.

Links

Mike Laszkiewicz, Imant Daunhawer, Julia E. Vogt, Asja Fischer, Johannes Lederer

Benchmarking the Fairness of Image Upsampling Methods Proceedings Article

In: ACM Conference on Fairness, Accountability, and Transparency (FaccT), 2024.

Links

Mike Laszkiewicz, Jonas Ricker, Johannes Lederer, Asja Fischer

Single-Model Attribution of Generative Models Through Final-Layer Inversion Proceedings Article

In: International Conference on Machine Learning (ICML), 2024.

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Kira Maag, Asja Fischer

Uncertainty-Weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation Proceedings Article

In: IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024.

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Kira Maag, Asja Fischer

Uncertainty-Based Detection of Adversarial Attacks in Semantic Segmentation Proceedings Article

In: International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP), 2024.

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Kira Maag, Roman Resner, Asja Fischer

Detecting Adversarial Attacks in Semantic Segmentation via Uncertainty Estimation: A Deep Analysis Proceedings Article

In: International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP), 2024.

Links

Matías Pizarro, Dorothea Kolossa, Asja Fischer

DistriBlock: Identifying Adversarial Audio Samples by Leveraging Characteristics of the Output Distribution Proceedings Article

In: Conference on Uncertainty in Artificial Intelligence (UAI), 2024.

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Matías Pizarro, Mike Laszkiewicz, Dorothea Kolossa, Asja Fischer

Single-Model Attribution for Spoofed Speech via Vocoder Fingerprints in an Open-World Setting Artikel

In: arXiv Preprint, 2024.

Links

Karla Pizzi, Matías Pizarro, Asja Fischer

Reassessing Noise Augmentation Methods in the Context of Adversarial Speech Proceedings Article

In: Symposium on Security and Privacy in Speech Communication (SPSC), 2024.

Links

Jonas Ricker, Dennis Assenmacher, Thorsten Holz, Asja Fischer, Erwin Quiring

AI-Generated Faces in the Real World: A Large-Scale Case Study of Twitter Profile Images Proceedings Article

In: International Symposium on Research in Attacks, Intrusions and Defenses (RAID), 2024.

Links

Jonas Ricker, Simon Damm, Thorsten Holz, Asja Fischer

Towards the Detection of Diffusion Model Deepfakes Proceedings Article

In: International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP), 2024.

Links

Jonas Ricker, Denis Lukovnikov, Asja Fischer

AEROBLADE: Training-Free Detection of Latent Diffusion Images Using Autoencoder Reconstruction Error Proceedings Article

In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.

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Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Stefan Wrobel, Asja Fischer

Wasserstein dropout Artikel

In: Machine Learning, 2024.

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Sidak Pal Singh, Linara Adilova, Michael Kamp, Asja Fischer, Bernhard Schölkopf, Thomas Hofmann

Landscaping Linear Mode Connectivity Artikel

In: International Conference on Machine Learning (ICML) Workshops, 2024.

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Yulian Sun, Li Duan, Ricardo Mendes, Derui Zhu, Yue Xia, Yong Li, Asja Fischer

Exploiting Internal Randomness for Privacy in Vertical Federated Learning Proceedings Article

In: European Symposium on Research in Computer Security (ESORICS), 2024.

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Dmytro Velychko, Simon Damm, Asja Fischer, Jörg Lücke

Learning sparse codes with entropy-based ELBOs Proceedings Article

In: International Conference on Artificial Intelligence and Statistics (AISTATS), 2024.

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Jan Warnken, Dmytro Velychko, Simon Damm, Asja Fischer, Jörg Lücke

Generative Models with ELBOs Converging to Entropy Sums Artikel

In: arXiv Preprint, 2024.

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2023

Linara Adilova, Maksym Andriushchenko, Michael Kamp, Asja Fischer, Martin Jaggi

Layer-wise Linear Mode Connectivity Proceedings Article

In: International Conference on Learning Representations (ICLR), 2023.

Links

Linara Adilova, Bernhard C. Geiger, Asja Fischer

Information Plane Analysis for Dropout Neural Networks Proceedings Article

In: International Conference on Learning Representations (ICLR), 2023.

Links

Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke

The ELBO of Variational Autoencoders Converges to a Sum of Entropies Proceedings Article

In: International Conference on Artificial Intelligence and Statistics (AISTATS), 2023.

Links

Mike Laszkiewicz, Denis Lukovnikov, Johannes Lederer, Asja Fischer

Set-Membership Inference Attacks using Data Watermarking Artikel

In: arXiv Preprint, 2023.

Links

2022

Sina Däubener, Asja Fischer

How Sampling Impacts the Robustness of Stochastic Neural Networks Proceedings Article

In: Advances in Neural Information Processing Systems (NeurIPS), 2022.

Links

Mike Laszkiewicz, Johannes Lederer, Asja Fischer

Marginal Tail-Adaptive Normalizing Flows Proceedings Article

In: International Conference on Machine Learning (ICML), 2022.

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2021

Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Mikhail Galkin, Sahand Sharifzadeh, Asja Fischer, Volker Tresp, Jens Lehmann

Bringing Light Into the Dark: A Large-Scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework Artikel

In: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021.

Links

Kai Brügge, Asja Fischer, Christian Igel

On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions Proceedings Article

In: International Conference on Artificial Intelligence and Statistics (AISTATS), 2021.

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Nilesh Chakraborty, Denis Lukovnikov, Gaurav Maheshwari, Priyansh Trivedi, Jens Lehmann, Asja Fischer

Introduction to Neural Network-Based Question Answering over Knowledge Graphs Artikel

In: WIREs Data Mining and Knowledge Discovery, 2021.

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Diego Esteves, José Marcelino, Piyush Chawla, Asja Fischer, Jens Lehmann

HORUS-NER: A Multimodal Named Entity Recognition Framework for Noisy Data Proceedings Article

In: Advances in Intelligent Data Analysis (IDA), 2021.

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Mike Laszkiewicz, Asja Fischer, Johannes Lederer

Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery Proceedings Article

In: International Conference on Artificial Intelligence and Statistics (AISTATS), 2021.

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