Publications

For additional information and material about our publications,
visit https://bib.sebastianstober.de

 

2026

• Phy-VC: Physics-Informed Voice Conversion for Privacy-Preserving Pathological Speech
  Suhita Ghosh, Yamini Sinha, Melanie Jouaiti, Tim Wansiedler, Kim Patrick Hakenberg, Julian Karcher, Ingo Siegert and Sebastian Stober
  In: Interspeech 2026 - Sydney, Australia, 27 September-02 October 2026
  [ URL ]
  
• Temporal Feature Extractors in EEG Foundation Models: A Controlled Comparison Including a Pretrained Time-Series Model
  Ayşe Betül Yüce, Chris Joey Leffler, Sarun Varghese, Myra Spiliopoulou and Sebastian Stober
  In: Proceedings of the 2nd ICML Workshop on Foundation Models for Structured Data, 2026
  [ URL ]
  
• Benchmarking Positional Encoding Strategies for Transformer-Based EEG Foundation Models
  Ayse Betul Yuce and Sebastian Stober
  In: 10th Graz Brain-Computer Interface Conference 2026 
  [ URL ]
  
  

2025

• Investigating Inclusivity of Whisper for Dysfluent Speech
  Evelyn Starzew, Suhita Ghosh, Valerie Krug In: 12th edition of the Disfluency in Spontaneous Speech Workshop (DiSS 2025) [ URL ]
  

• StutterCut: Uncertainty-Guided Normalized Cut for Dysfluency Segmentation

  
  Suhita Ghosh,   Melanie Jouaiti, 

  Jan-Ole Perschewski

   and Sebastian Stober. In: Interspeech 2025 - Rotterdam, The Netherlands, August 17-21, 2025 [URL ] [ Github ]
  
• Efficient Deep Equilibrium Models: Denoising Regularization and Average Fixed-Point Initialization to Reduce Function Evaluations
  

  Jan-Ole Perschewski

   and Sebastian Stober. In: International Neural Network Society Workshop on Deep Learning Innovations and Applications 2025 [URL]
  
• Intersectional Bias Quantification in Facial Image Processing with Pre-Trained ImageNet Classifiers
  Valerie Krug, Florian Röhrbein, Sebastian Stober. In: 2025 International Joint Conference on Neural Networks (IJCNN) [ URL ]
  
• Assessing Intersectional Bias in Representations of Pre-Trained Image Recognition Models
  Valerie Krug, Sebastian Stober. In: 3rd TRR 318 Conference: Contextualizing Explanations [ URL ] [ extended Version ]
  
• Relation of Activity and Confidence When Training Deep Neural Networks
  Valerie Krug, Christopher Olson, Sebastian Stober. In: Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD 2023. Communications in Computer and Information Science, vol 2134 [ URL ]
  
  
• TransferLight: Zero-Shot Traffic Signal Control on any Road Network.
  Johann Schmidt,  Frank Dreyer ,  Sayed Abid Hashimi & Sebastian Stober.
  In: Multi-Agent reinforcement Learning for Transportation Autonomy (MALTA) Workshop AAAI, 2025.
  [ URL ]
  
  

2024

• Integrating AI Education in Disciplinary Engineering Fields: Towards a System and Change Perspective
  Johannes Schleiss, Aditya Johri , Sebastian Stober.
  In: Proceedings of Society for Engineering Education (SEFI) Annual Conference 2024, pp. 2126-2137[DOI]
  
  
• A Roles-based Competency Framework for Integrating Artificial Intelligence (AI) in Engineering Courses
  Johannes Schleiss, Aditya Johri.
  In: Proceedings of Society for Engineering Education (SEFI) Annual Conference 2024, pp. 2116-2125[DOI]
  
  
• Towards Responsible AI Competencies for Engineers: An Explorative Literature Review on Existing Frameworks
  

  Marie Decker, Johannes Schleiss, Ben Schultz, Sarah Moreno, Sebastian Stober, and Carmen Leicht-Scholten 
  In:  Proceedings of Society for Engineering Education (SEFI) Annual Conference 2024, pp. 1372-1384
  [ DOI ]
  
  

• Misconceptions, Pragmatism, and Value Tensions: Evaluating Students' Understanding and Perception of Generative AI for Education
  Aditya Johri, Ashish Hingle, Johannes Schleiss
  In:Proceedings of 2024 IEEE Frontiers in Education (FIE) Conference
  

• Mastery Learning in Higher Education: A Classification from Theory to Practice.
  Johannes Schleiss, Mathias Magdowski.
  In: Digital Examination Scenarios in Higher Education, 65-79[DOI]
  
  

• Artificial intelligence in the context of competencies, assessments, and teaching and learning methods: Old and new design issues.
  Maria Klar, Johannes Schleiss.
  In: Media Education: Journal for Theory and Practice of Media Education 58, 41-57 [ DOI ]
  
  

• Artificial Intelligence and Education in Germany: Insights from the AI ​​Education Workshop 2024
  Johannes Schleiss, Marc Egloffstein, Dana-Kristin Mah
  In: Proceedings of DELFI Workshops 2024
  [DOI]
  

• Use of open educational resources on artificial intelligence.
  Marc Egloffstein, Johannes Schleiss, Raffael Ruppert, Florian Rampelt.
  In:5th EdTech Research Forum 2024, 1st Conference of the Media Didactics Working Group of the German Society for Educational Science (DGfE).
  
  
• Improving Voice Quality in Speech Anonymization With Just Perception-Informed Losses
  Suhita Ghosh, Tim Thiele, Frederick Lorbeer, Frank Dreyer and Sebastian Stober.
  In: NeurIPS Workshop 2024 (Audio Imagination: Workshop on AI-Driven Speech, Music, and Sound Generation) - Vancouver, Canada, December 10-15, 2024
  [ URL ]
  
  
• Anonymizing Elderly and Pathological Speech: Voice Conversion Using DDSP and Query-by-Example
  Suhita Ghosh, Melanie Jouaiti, Arnab Das, Yamini Sinha, Tim Polzehl, Ingo Siegert and Sebastian Stober.
  In: Interspeech 2024 - Kos, Greece, September 1-5, 2024
  [URL] [Github]
  
  
• Speecher: Towards Privacy Ensuring Decoder Only Speech Reconstruction Through Disentanglement for German Speech Anonymization Using Any-to-Many Voice Conversion
  

  Arnab Das, Carlos Franzreb, Suhita Ghosh, Tim Polzehl, Sebastian Möller.

  In: SPSC Workshop, Interspeech 2024 - Kos, Greece, September 6, 2024
  [ URL ]
  
  
• Exploration of interpretability techniques for deep COVID-19 classification using chest X-ray images.
  Soumick Chatterjee, Fatima Saad, Chompunuch Sarasaen, Suhita Ghosh, Valerie Krug, Rupali Khatun, Rahul Mishra, Nirja Desai, Petia Radeva, Georg Rose, Sebastian Stober, Oliver Speck, Andreas Nürnberger.
  In: Journal of Imaging (AI in Imaging), 2024.
  [ URL ]
  

• Neuroscience-Inspired Analysis and Visualization of Deep Neural Networks.
  Valerie Krug.
  Dissertation/PhD thesis, Otto-von-Guericke University Magdeburg, Faculty of Computer Science
  [ URL ]
  
  

• Reviving Simulated Annealing: Lifting its Degeneracies for Real-Time Job Scheduling.
  Johann Schmidt, Benjamin Köhler & Hagen Borstell.
  In: The Hawaii International Conference on System Sciences (HICSS), 2024.
  [ URL ]
  

• Pursuing the Perfect Projection: A Projection Pursuit Framework for Deep Learning. 
  Jan-Ole Perschewski, Johann Schmidt & Sebastian Stober.
  In: International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM+), 2024.
  [ URL ]
  

• T-DVAE: A Transformer-Based Dynamical Variational Autoencoder for Speech
  Jan-Ole Perschewski & Sebastian Stober
  In:  Artificial Neural Networks and Machine Learning – ICANN 2024
  [ URL ]
  
  

• Tilt your Head: Activating the Hidden Spatial-Invariance of Classifiers.
  Johann Schmidt & Sebastian Stober.
  In: International Conference on Machine Learning (ICML), 2024.
  [ URL ]
  

• Hybrid Symbolic-Waveform Modeling of Music–Opportunities and Challenges
  Jens Johannsmeier & Sebastian Stober
  In: Third Workshop on Artificial Intelligence and Creativity (CREAI), 2024
  [ URL ]
  
  

2023

• Visualizing Bias in Activations of Deep Neural Networks as Topographic Maps Valerie Krug, Christopher Olson and Sebastian Stober.
  In: Proceedings of the 1st Workshop on Fairness and Bias in AI (AEQUITAS 2023), co-located with 26th European Conference on Artificial Intelligence (ECAI 2023) Kraków, Poland. CEUR-WS, 2023
  [ URL ]
  
  

• Emo-StarGAN: A Semi-Supervised Any-to-Many Non-Parallel Emotion-Preserving Voice Conversion Suhita Ghosh, Arnab Das, Yamini Sinha, Ingo Siegert, Tim Polzehl and Sebastian Stober.
  In: Interspeech 2023 - Dublin, Ireland, August 20-24, 2023
  [ URL ]  [Github]
  
  
• StarGAN-VC++: Towards Emotion Preserving Voice Conversion Using Deep Embeddings. Arnab Das, Suhita Ghosh, Tim Polzehl and Sebastian Stober. In: 12th Speech Synthesis Workshop (SSW) 2023 - Grenoble, France, August 26-30, 2023 [ URL ] [Github]
  
  
• Anonymization of Stuttered Speech – Removing Speaker Information while  Preserving the Utterance.
  Jan Hintz ,  Sebastian Bayerl , Yamini Sinha , Suhita Ghosh , Martha Schubert,  Sebastian  Stober , Korbinian Riedhammer and  Ingo Siegert. In: 3rd Symposium on Security and Privacy in Speech Communication - Dublin, Ireland, August 19, 2023[URL]
  
  
• Visualizing Deep Neural Networks with Topographic Activation Maps.
  Valerie Krug, Raihan Kabir Ratul, Christopher Olson and Sebastian Stober.
  In: HHAI 2023: Augmenting Human Intellect. IOS Press, 2023. 138-152.
  [ URL ] [G ithub ]
  
  
• AI Course Design Planning Framework: Developing Domain-Specific AI Education Courses.
  Johannes Schleiss, Matthias Carl Laupichler, Tobias Raupach and Sebastian Stober.
  
  Educ. Sci. 2023, 13 (9), 954; [ https://doi.org/10.3390/educsci13090954 ]
  
  

• Better ready than just aware: Data and AI literacy as an enabler for informed decision making in the data age.
  Katharina Schüller, Florian Rampelt, Henning Koch and Johannes Schleiss.
  In: INFORMATIK 2023. [ 10.18420/inf2023_49 ]
  
  
• Planning Interdisciplinary Artificial Intelligence Courses.
  Johannes Schleiss and Sebastian Stober.
  In: Proceedings of Society for Engineering Education (SEFI) Annual Conference 2023. [ https://doi.org/10.21427/V4ZV-HR52 ]
  
  

• Curriculum Workshop as Method of Interdisciplinary Curriculum Development: A Case Study of Artificial Intelligence in Engineering.
  Johannes Schleiss, Anke Manukjan, Michelle Ines Bieber, Philipp Pohlenz, Sebastian Stober.
  In: Proceedings of Society for Engineering Education (SEFI) Annual Conference 2023. [ https://doi.org/10.21427/XTAE-AS48 ]
  
  

2022

• Voice Privacy Leveraging Multi-Scale Blocks with ECAPA-TDNN SE-Res2NeXT Extension for Speaker Anonymization.
  Razieh Khamsehashari, Yamini Sinha, Jan Hintz, Suhita Ghosh, Tim Polzehl, Carlos Franzreb, Sebastian Stober and Ingo Siegert.
  In: 2nd Symposium on Security and Privacy in Speech Communication - Incheon, Korea, September 23-24, 2022 - International Speech Communication Association.  https://doi.org/10.21437/spsc.2022-8
• Project seminar “Artificial Intelligence in Neuroscience – Implementing Interdisciplinary and Application-Oriented Teaching.”
  Johannes Schleiss, Robert Brockhoff, and Sebastian Stober.
  In: Mah, D.-K., & Torner, C. (Eds.) (2022): Application-Oriented Higher Education Teaching in Artificial Intelligence. Impulses from the Fellowship Program for the Integration of AI Campus Learning Opportunities. Berlin: AI Campus. https://doi.org/10.5281/zenodo.7319832
  
  

• An Interdisciplinary Competence Profile for AI in Engineering.
  Johannes Schleiss, Michelle Ines Bieber, Anke Manukjan, Lars Kellner and Sebastian Stober.
  In: Proceedings of the 50thEuropean Society for Engineering Education (SEFI)Annual Conference, 2022.
  [URL]
  
  
• Teaching AI Competencies in Engineering using Projects and Open Educational Resources.
  Johannes Schleiss, Julia Hense, Andreas Kist, Jörn Schlingensiepen and Sebastian Stober
  In: Proceedings of the 50thEuropean Society for Engineering Education (SEFI)Anual Conference, 2022.
  [URL]
  
  

• Neural-Gas UAE
  Jan-Ole Perschewski and Sebastian Stober
  In:  Artificial Neural Networks and Machine Learning – ICANN 2022
  [ URL ]
  
  

• Towards Patient Specific Reconstruction Using Perception-Aware CNN and Planning CT as Prior.
  Suhita Ghosh, Philipp Ernst, Georg Rose, Andreas Nürnberger and Sebastian Stober.
  In: IEEE 19th International Symposium on Biomedical Imaging (ISBI). IEEE, 2022.
  [URL]
  
  
• Dual Branch Prior-SegNet: CNN for Interventional CBCT using Planning Scan and Auxiliary Segmentation Loss.
  Philipp Ernst, Suhita Ghosh, Georg Rose, Andreas Nürnberger .
  Medical Imaging with Deep Learning, MIDL 2022, Zurich, Switzerland, July 06, 2022, Medical Imaging with Deep Learning
  [URL]
  
  
• Protecting Student Data in ML Pipelines: An Overview of Privacy-Preserving ML.
  Johannes Schleiss, Kolja Günther and Sebastian Stober.
  In: Proceedings of the International Conference on Artificial Intelligence in Education, 532-536, 2022.
  [ URL ]
  
  
• BiTe-REx: An Explainable Bilingual Text Retrieval System in the Automotive Domain.
  Viju Sudhi; Sabine Wehnert, Norbert Michael Homner, Sebastian Ernst, Mark Gonter, Andreas Krug and Ernesto William De Luca.
  In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Pages 3251–3255, 2022.
  [ URL ]
  
  

• Visualizing Deep Neural Networks with Topographic Activation Maps.
  Andreas Krug, Raihan Kabir Ratul and Sebastian Stober.
  In: arXiv preprint arXiv:2204.03528, 2022.
  [ PDF ] [ github ]
  
  

2021

• Hierarchical Predictive Coding and Interpretable Audio Analysis-Synthesis.
  André Ofner; Johannes Schleiss & Sebastian Stober. In: Proc. of the 15th International Symposium on CMMR , 2021. [ PDF ]
  
  
• Uncertainty-aware temporal self-learning (UATS) - semi-supervised learning for segmentation of prostate zones and beyond.
  Anneke Meyer; Suhita Ghosh; Daniel Schindele; Martin Shostak; Sebastian Stober; Christian Hansen & Marko Rak.
  In:  Artificial intelligence in medicine: AIM - Amsterdam [ua]: Elsevier Science - AIM, Vol. 116, 2021.
  [ PDF ]
  
  
• Analyzing and Visualizing Deep Neural Networks for Speech Recognition with Saliency-Adjusted Neuron Activation Profiles.
  Andreas Krug; Maral Ebrahimzadeh; Jost Aleman; Jens Johannsmeier & Sebastian Stober.
  In: Electronics 10 (11), 1350, 2021.
  [ URL ]
  
  
• Perceptual Losses Facilitate CT Denoising and Artifact Removal.
  Suhita Ghosh; Andreas Krug; Georg Rose & Sebastian Stober.
  In: 2021 IEEE 2nd International Conference on Human-Machine Systems (ICHMS) . IEEE, 2021.
  [ URL ]
  
  

• Distributed Planning with Active Inference.
  André Ofner; Johannes Schleiss & Sebastian Stober .
  In: Bernstein Conference , 2021.
  [ URL ]
  
  
• Visualizing Artificial Neural Network Activations as Topographic Maps.
  Andreas Krug;  Raihan Kabir Ratul &  Sebastian Stober .
  In: Bernstein Conference , 2021.
  [ URL ]
  
  
• NeuroEvolution of Augmenting Topologies for Solving a Two-Stage Hybrid Flow Shop.
  Sebastian Lang, Tobias Reggelin, Johann Schmidt, Marcel Müller & Abdulrahman Nahhas.
  In: Expert Systems with Applications, 2021.
  [ URL ]
  
  
• Human Action Recognition as part of a Natural Machine Operation Framework.
  Simone Bexten, Johann Schmidt, Christoph Walter & Norbert Elkmann.
  In: IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2021.
  [URL]
  
  

• Approaching Scheduling Problems via a Deep Hybrid Greedy Model and Supervised Learning .
  Johann Schmidt & Sebastian Stobe r .
  In:  IFAC-PapersOnline 54 (1), 805-810, 2021 .
  [ URL ]
  
  

• Few-Shot Bioacoustic Event Detection via Segmentation using Prototypical Networks.
  Jens Johannsmeier & Sebastian Stobe r .
  In: Detection and Classification of Acoustic Scenes and Events (DCASE), 2021.
  [ PDF ]
  
  

2020

• Automatic prostate and prostate zones segmentation of magnetic resonance images using DenseNet-like U-net.
  Nader Aldoj; Federico Biavati; Florian Michallek; Sebastian Stober & Marc Dewey.
  In: Scientific Reports, Volume 10, Number 1, Springer Science and Business Media LLC, 2020.
  [ DOI ] [ PDF ]
  
  
• Balancing Active Inference and Active Learning with Deep Variational Predictive Coding for EEG.
  André Ofner & Sebastian Stober.
  In: IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020), 2020.
  [ URL ]
  
  
• Modeling perception with hierarchical prediction: Auditory segmentation with deep predictive coding locates candidate evoked potentials in EEG.
  André Ofner & Sebastian Stober.
  In: ResearchGATE: scientific network ; the leading professional network for scientists - Cambridge, Mass.: ResearchGATE Corp., 2010, 2020.
  [ URL ] [ PDF ]
  
  
• Applying deep learning to single-trial EEG data provides evidence for complementary theories on action control. Amirali Vahid; Moritz Mückschel; Sebastian Stober: Ann-Kathrin Stock & Christian Beste. In:  Communications biology - London: Springer Nature, Vol. 3.2020, Art.-No. 112, 11, 2020. [ DOI ] [ PDF ]
  
• Analyzing regions of safety for handling shared data in cooperative systems.
  Georg Jäger; Johannes Schleiss; Sasiporn Usanavasin; Sebastian Stober & Sebastian Zug.
  In:  2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2020.
  [ URL ]
  
  
• PredNet and Predictive Coding: A Critical Review.
  Roshan Prakash Rane; Edit Szügyi; Vageesh Saxena; André Ofner & Sebastian Stober.
  In: Proceedings of the 2020 International Conference on Multimedia Retrieval, ICMR '20, Pages 233–241, Association for Computing Machinery, New York, NY, USA, 2020.
  [ DOI ] [ PDF ]
  
  

• Gradient-adjusted neuron activation profiles for comprehensive introspection of convolutional speech recognition models.
  Andreas Krug & Sebastian Stober.
  In: arXiv preprint arXiv:2002.08125, 2020.
  [ PDF ]
  
  

2019

• Window-Based Neural Tagging for Shallow Discourse Argument Labeling.
  René Knaebel; Manfred Stede & Sebastian Stober.
  In: Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL), Pages 768-777, 2019.
  [ DOI ] [ PDF ]
  
  
• The ISMIR Explorer – A Visual Interface for Exploring 20 Years of ISMIR Publications.
  Thomas Low; Christian Hentschel; Sayantan Polley; Anustup Das; Harald Sack; Andreas Nürnberger & Sebastian Stober.
  In: 20th International Society for Music Information Retrieval Conference (ISMIR'19), Pages 392-399, 2019.
  [ PDF ]
  
  
• Predictive Coding Based Vision For Autonomous Cars.
  Roshan Prakash Rane; André Ofner; Shreyas Gite​ & Sebastian Stober.
  In: Computational Cognition 2019 Workshop, 2019.
  [ URL ]
  
  
• Knowledge transfer in coupled predictive coding networks.
  André Ofner & Sebastian Stober.
  In: Bernstein Conference, 2019.
  [ DOI ]
  
  
• Visualizing Deep Neural Networks for Speech Recognition with Learned Topographic Filter Maps.
  Andreas Krug & Sebastian Stober.
  In: Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 2019.
  [ PDF ]
  
  
• Siri visualized.
  Andreas Krug & Sebastian Stober.
  In: Proceedings of the 2019 NaWik Symposium Karlsruhe, Pages 24-25, 2019.
  
  
• Deep Learning Based on Event-Related EEG Differentiates Children with ADHD from Healthy Controls.
  Amirali Vahid; Annet Bluschke; Veit Roessner; Sebastian Stober & Christian Best.
  In: Journal of Clinical Medicine, Volume 8, Number 7, 2019.
  [ DOI ] [ PDF ]
  
  
• Hybrid Variational Predictive Coding as a Bridge between Human and Artificial Cognition.
  André Ofner & Sebastian Stober.
  In: The 2019 Conference on Artificial Life, Number 31, Pages 68-69, 2019.
  [ URL ] [ PDF ]
  
  
• Automatic prostate and prostate zones segmentation of magnetic resonance images using convolutional neural networks.
  Nader Aldoj; Federico Biavati; Miriam Rutz; Florian Michallek; Sebastian Stober & Marc Dewey.
  In: Proceedings of International Conference on Medical Imaging with Deep Learning (MIDL'19), 2019.
  [ DOI ] [ PDF ]