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

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.

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.

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.

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.

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.

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.

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.

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 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.

Streamlined Training of GCN for Node Classification with Automatic Loss Function and Optimizer Selection
S. Sanaullah, S. Koravuna, U. Rückert, T. Jungeblut, in: L. Iliadis, I. Maglogiannis, S. Alonso, C. Jayne, E. Pimenidis (Eds.), Engineering Applications of Neural Networks. 24th International Conference, EAAAI/EANN 2023, León, Spain, June 14–17, 2023, Proceedings, Springer Nature Switzerland, Cham, 2023, pp. 191–202.

Evaluation of Spiking Neural Nets-Based Image Classification Using the Runtime Simulator RAVSim
S. Sanaullah, S. Koravuna, U. Rückert, T. Jungeblut, International Journal of Neural Systems (2023).

Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications
S. Sanaullah, S. Koravuna, U. Rückert, T. Jungeblut, Frontiers in Computational Neuroscience 17 (2023).

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

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.

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.