DNA: detecting early signs of neurodegenerative diseases through activity and sleep analysis
H. Attaullah, S. Sanaullah, A. Peters, Q.A. Ahmed, J. Baudisch, T. Jungeblut, Frontiers in Neuroscience 19 (2025).

Design-Space Exploration of Biologically-Inspired SNN Models for Application-Specific Many-Core Systems
S. Sanaullah, Design-Space Exploration of Biologically-Inspired SNN Models for Application-Specific Many-Core Systems, Universität Bielefeld, 2025.

Automating Neural Model Selection in Spiking Neural Networks Using AutoML Techniques*
S. Sanaullah, H. Honda, K. Roy, A. Schneider, J. Waßmuth, T. Jungeblut, in: 2025 22nd International Learning and Technology Conference (L&;T), IEEE, 2025, pp. 274–279.

RAVSim .0: Enhanced visualization and comparative analysis for neural network models
S. Sanaullah, A. Schneider, J. Waßmuth, U. Rückert, T. Jungeblut, SoftwareX 29 (2025).

Spiking Neural Network Models Analysis on Field Programmable Gate Arrays
S. Koravuna, S. Sanaullah, T. Jungeblut, U. Rückert, in: S. Pudaruth, K. Ogudo (Eds.), International Conference on Intelligent and Innovative Computing Applications, Society of Information Technologists and Engineers Ltd, 2024, pp. 259–270.

FL-DL: Fuzzy Logic with Deep Learning, Hybrid Anomaly Detection and Activity Prediction in Smart Homes Data-Sets
H. Attaullah, S. Sanaullah, T. Jungeblut, in: 2024 IEEE 24th International Symposium on Computational Intelligence and Informatics (CINTI), IEEE, Budapest, Hungary, 2024, pp. 43–48.

Trade-offs Between Privacy and Performance in Encrypted Dataset using Machine Learning Models
S. Sanaullah, H. Attaullah, T. Jungeblut, in: U. Kuhl, DataNinja.nrw (Eds.), Proceedings of the SAIOnARA Conference, DataNinja sAIOnARA Conference, 2024.

Advancements in Neural Network Generations
S. Sanaullah, S. Koravuna, U. Rückert, T. Jungeblut, in: U. Kuhl, DataNinja.nrw (Eds.), Proceedings of the SAIOnARA Conference, DataNinja sAIOnARA Conference, 2024.

Encryption Techniques for Privacy-Preserving CNN Models: Performance and Practicality in Urban AI Applications
S. Sanaullah, H. Attaullah, T. Jungeblut, in: O.A. Omitaomu, A. Mostafavi, S. Randhawa, H. Niu (Eds.), Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances in Urban-AI, ACM, New York, NY, USA, 2024, pp. 50–53.

Analyzing Machine Learning Models for Activity Recognition Using Homomorphically Encrypted Real-World Smart Home Datasets: A Case Study
H. Attaullah, S. Sanaullah, T. Jungeblut, Applied Sciences 14 (2024).

Selection of Optimal Neural Model using Spiking Neural Network for Edge Computing   
S. Sanaullah, K. Roy, U. Ruckert, T. Jungeblut, in: IEEE (Ed.), 2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS), IEEE, 2024, pp. 1452–1453.

A Spike Vision Approach for Multi-object Detection and Generating Dataset Using Multi-core Architecture on Edge Device
S. Sanaullah, S. Koravuna, U. Rückert, T. Jungeblut, in: L. Iliadis, I. Maglogiannis, A. Papaleonidas, E. Pimenidis, C. Jayne (Eds.), Engineering Applications of Neural Networks. 25th International Conference, EANN 2024, Corfu, Greece, June 27–30, 2024, Proceedings, Springer Nature Switzerland, Cham, 2024, pp. 317–328.

A Hybrid Spiking-Convolutional Neural Network Approach for Advancing Machine Learning Models
S. Sanaullah, K. Roy, U. Rückert, T. Jungeblut, in: T. Lutchyn, A. Ramírez Rivera, B. Ricaud (Eds.), Proceedings of the 5th Northern Lights Deep Learning Conference, Proceedings of Machine Learning Research (PMLR), UiT The Arctic University, Tromsø, Norway, 2024.

The Next-Gen Interactive Runtime Simulator for Neural Network Programming
S. Sanaullah, H. Attaullah, T. Jungeblut, in: E. Söderberg, L. Church (Eds.), Companion Proceedings of the 8th International Conference on the Art, Science, and Engineering of Programming, ACM, New York, NY, USA, 2024, pp. 8–10.

A Novel Spike Vision Approach for Robust Multi-Object Detection using SNNs
S. Sanaullah, S. Koravuna, U. Rückert, T. Jungeblut, in: 2023.

A Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality Image Inpainting
S. Sanaullah, A. Amanullah, K. Roy, J.-A. Lee, S. Chul-Jun, T. Jungeblut, in: 2023.

Analysis of MR Images for Early and Accurate Detection of Brain Tumor using Resource Efficient Simulator Brain Analysis
S. Sanaullah, T. Jungeblut, in: New York USA, 2023.

Digit Recognition Using Spiking Neural Networks on FPGA
S. Koravuna, S. Sanaullah, T. Jungeblut, U. Rückert, in: I. Rojas, G. Joya, A. Catala (Eds.), Advances in Computational Intelligence. 17th International Work-Conference on Artificial Neural Networks, IWANN 2023, Ponta Delgada, Portugal, June 19–21, 2023, Proceedings, Part I, Springer Nature Switzerland, Cham, 2023, pp. 406–417.

Transforming Event-Based into Spike-Rate Datasets for Enhancing Neuronal Behavior Simulation to Bridging the Gap for SNNs
S. Sanaullah, S. Koravuna, U. Rückert, T. Jungeblut, in: Paris France , 2023.

Design-Space Exploration of SNN Models using Application-Specific Multi-Core Architectures
S. Sanaullah, S. Koravuna, U. Ruckert, T. Jungeblut, Preprint (2023).