| 2026 | DATE | QSLM: A Performance- and Memory-aware Quantization Framework with Tiered Search Strategy for Spike-driven Language Models. | Rachmad Vidya Wicaksana Putra, Pasindu Wickramasinghe, Muhammad Shafique |
| 2026 | DATE | Focus Session: Hardware and Software Techniques for Accelerating Multimodal Foundation Models. | Muhammad Shafique, Abdul Basit, Muhammad Abdullah Hanif, Alberto Marchisio, Rachmad Vidya Wicaksana Putra, Minghao Shao |
| 2025 | DAC | Replay4NCL: An Efficient Memory Replay-based Methodology for Neuromorphic Continual Learning in Embedded AI Systems. | Mishal Fatima Minhas, Rachmad Vidya Wicaksana Putra, Falah Awwad, Osman Hasan, Muhammad Shafique |
| 2025 | IJCNN | QSViT: A Methodology for Quantizing Spiking Vision Transformers. | Rachmad Vidya Wicaksana Putra, Saad Iftikhar, Muhammad Shafique |
| 2025 | IJCNN | Enabling Efficient Processing of Spiking Neural Networks with On-Chip Learning on Commodity Neuromorphic Processors for Edge AI Systems. | Rachmad Vidya Wicaksana Putra, Pasindu Wickramasinghe, Muhammad Shafique |
| 2024 | ICARCV | FastSpiker: Enabling Fast Training for Spiking Neural Networks on Event-based Data Through Learning Rate Enhancements for Autonomous Embedded Systems. | Iqra Bano, Rachmad Vidya Wicaksana Putra, Alberto Marchisio, Muhammad Shafique |
| 2024 | ICARCV | A Methodology to Study the Impact of Spiking Neural Network Parameters Considering Event-Based Automotive Data. | Iqra Bano, Rachmad Vidya Wicaksana Putra, Alberto Marchisio, Muhammad Shafique |
| 2024 | ICARCV | Embodied Neuromorphic Artificial Intelligence for Robotics: Perspectives, Challenges, and Research Development Stack. | Rachmad Vidya Wicaksana Putra, Alberto Marchisio, Fakhreddine Zayer, Jorge Dias, Muhammad Shafique |
| 2023 | IROS | TopSpark: A Timestep Optimization Methodology for Energy-Efficient Spiking Neural Networks on Autonomous Mobile Agents. | Rachmad Vidya Wicaksana Putra, Muhammad Shafique |
| 2022 | DAC | SoftSNN: low-cost fault tolerance for spiking neural network accelerators under soft errors. | Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique |
| 2022 | IJCNN | lpSpikeCon: Enabling Low-Precision Spiking Neural Network Processing for Efficient Unsupervised Continual Learning on Autonomous Agents. | Rachmad Vidya Wicaksana Putra, Muhammad Shafique |
| 2021 | DAC | SpikeDyn: A Framework for Energy-Efficient Spiking Neural Networks with Continual and Unsupervised Learning Capabilities in Dynamic Environments. | Rachmad Vidya Wicaksana Putra, Muhammad Shafique |
| 2021 | DAC | SparkXD: A Framework for Resilient and Energy-Efficient Spiking Neural Network Inference using Approximate DRAM. | Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique |
| 2021 | ICCAD | Towards Energy-Efficient and Secure Edge AI: A Cross-Layer Framework ICCAD Special Session Paper. | Muhammad Shafique, Alberto Marchisio, Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif |
| 2021 | ICCAD | ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories. | Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique |
| 2021 | IJCNN | Q-SpiNN: A Framework for Quantizing Spiking Neural Networks. | Rachmad Vidya Wicaksana Putra, Muhammad Shafique |
| 2020 | DAC | DRMap: A Generic DRAM Data Mapping Policy for Energy-Efficient Processing of Convolutional Neural Networks. | Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique |
| 2018 | IOLTS | Robust Machine Learning Systems: Reliability and Security for Deep Neural Networks. | Muhammad Abdullah Hanif, Faiq Khalid, Rachmad Vidya Wicaksana Putra, Semeen Rehman, Muhammad Shafique |