Rachmad Vidya Wicaksana Putra

67 papers A* 5A 3B 4C 4Journal 39Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	QSLM: A Performance- and Memory-aware Quantization Framework with Tiered Search Strategy for Spike-driven Language Models. CoRR Rachmad Vidya Wicaksana Putra, Pasindu Wickramasinghe, Muhammad Shafique
2026	J	`jnl`	SpikeNAS: A Fast Memory-Aware Neural Architecture Search Framework for Spiking Neural Network-Based Embedded AI Systems. IEEE Trans. Artif. Intell. Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2025	J	`jnl`	Continual Learning With Neuromorphic Computing: Foundations, Methods, and Emerging Applications. IEEE Access Mishal Fatima Minhas, Rachmad Vidya Wicaksana Putra, Falah Awwad, Osman Hasan, Muhammad Shafique
2025	B	`conf`	Enabling Efficient Processing of Spiking Neural Networks with On-Chip Learning on Commodity Neuromorphic Processors for Edge AI Systems. IJCNN Rachmad Vidya Wicaksana Putra, Pasindu Wickramasinghe, Muhammad Shafique
2025	J	`jnl`	Enabling Efficient Processing of Spiking Neural Networks with On-Chip Learning on Commodity Neuromorphic Processors for Edge AI Systems. CoRR Rachmad Vidya Wicaksana Putra, Pasindu Wickramasinghe, Muhammad Shafique
2025	B	`conf`	QSViT: A Methodology for Quantizing Spiking Vision Transformers. IJCNN Rachmad Vidya Wicaksana Putra, Saad Iftikhar, Muhammad Shafique
2025	J	`jnl`	QSViT: A Methodology for Quantizing Spiking Vision Transformers. CoRR Rachmad Vidya Wicaksana Putra, Saad Iftikhar, Muhammad Shafique
2025	A*	`conf`	Replay4NCL: An Efficient Memory Replay-based Methodology for Neuromorphic Continual Learning in Embedded AI Systems. DAC Mishal Fatima Minhas, Rachmad Vidya Wicaksana Putra, Falah Awwad, Osman Hasan, Muhammad Shafique
2025	J	`jnl`	Replay4NCL: An Efficient Memory Replay-based Methodology for Neuromorphic Continual Learning in Embedded AI Systems. CoRR Mishal Fatima Minhas, Rachmad Vidya Wicaksana Putra, Falah Awwad, Osman Hasan, Muhammad Shafique
2025	J	`jnl`	SpiKernel: A Kernel Size Exploration Methodology for Improving Accuracy of the Embedded Spiking Neural Network Systems. IEEE Embed. Syst. Lett. Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2025	J	`jnl`	SpikeVox: Towards Energy-Efficient Speech Therapy Framework with Spike-driven Generative Language Models. CoRR Rachmad Vidya Wicaksana Putra, Aadithyan Rajesh Nair, Muhammad Shafique
2025	J	`jnl`	SwitchMT: An Adaptive Context Switching Methodology for Scalable Multi-Task Learning in Intelligent Autonomous Agents. CoRR Avaneesh Devkota, Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2024	J	`jnl`	A Methodology for Improving Accuracy of Embedded Spiking Neural Networks through Kernel Size Scaling. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2024	C	`conf`	A Methodology to Study the Impact of Spiking Neural Network Parameters Considering Event-Based Automotive Data. ICARCV Iqra Bano, Rachmad Vidya Wicaksana Putra, Alberto Marchisio, Muhammad Shafique
2024	J	`jnl`	A Methodology to Study the Impact of Spiking Neural Network Parameters considering Event-Based Automotive Data. CoRR Iqra Bano, Rachmad Vidya Wicaksana Putra, Alberto Marchisio, Muhammad Shafique
2024	—	`ch.`	An Off-Chip Memory Access Optimization for Embedded Deep Learning Systems. Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing: Hardware Architectures Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2024	J	`jnl`	Continual Learning with Neuromorphic Computing: Theories, Methods, and Applications. CoRR Mishal Fatima Minhas, Rachmad Vidya Wicaksana Putra, Falah Awwad, Osman Hasan, Muhammad Shafique
2024	C	`conf`	Embodied Neuromorphic Artificial Intelligence for Robotics: Perspectives, Challenges, and Research Development Stack. ICARCV Rachmad Vidya Wicaksana Putra, Alberto Marchisio, Fakhreddine Zayer, Jorge Dias, Muhammad Shafique
2024	J	`jnl`	Embodied Neuromorphic Artificial Intelligence for Robotics: Perspectives, Challenges, and Research Development Stack. CoRR Rachmad Vidya Wicaksana Putra, Alberto Marchisio, Fakhreddine Zayer, Jorge Dias, Muhammad Shafique
2024	C	`conf`	FastSpiker: Enabling Fast Training for Spiking Neural Networks on Event-based Data Through Learning Rate Enhancements for Autonomous Embedded Systems. ICARCV Iqra Bano, Rachmad Vidya Wicaksana Putra, Alberto Marchisio, Muhammad Shafique
2024	J	`jnl`	FastSpiker: Enabling Fast Training for Spiking Neural Networks on Event-based Data through Learning Rate Enhancements for Autonomous Embedded Systems. CoRR Iqra Bano, Rachmad Vidya Wicaksana Putra, Alberto Marchisio, Muhammad Shafique
2024	J	`jnl`	HASNAS: A Hardware-Aware Spiking Neural Architecture Search Framework for Neuromorphic Compute-in-Memory Systems. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2024	J	`jnl`	MTSpark: Enabling Multi-Task Learning with Spiking Neural Networks for Generalist Agents. CoRR Avaneesh Devkota, Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2024	—	`ch.`	Massively Parallel Neural Processing Array (MPNA): A CNN Accelerator for Embedded Systems. Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing: Hardware Architectures Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2024	J	`jnl`	PENDRAM: Enabling High-Performance and Energy-Efficient Processing of Deep Neural Networks through a Generalized DRAM Data Mapping Policy. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2024	J	`jnl`	SNN4Agents: A Framework for Developing Energy-Efficient Embodied Spiking Neural Networks for Autonomous Agents. CoRR Rachmad Vidya Wicaksana Putra, Alberto Marchisio, Muhammad Shafique
2024	J	`jnl`	SNN4Agents: a framework for developing energy-efficient embodied spiking neural networks for autonomous agents. Frontiers Robotics AI Rachmad Vidya Wicaksana Putra, Alberto Marchisio, Muhammad Shafique
2024	J	`jnl`	SpikeNAS: A Fast Memory-Aware Neural Architecture Search Framework for Spiking Neural Network Systems. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2023	J	`jnl`	EnforceSNN: Enabling Resilient and Energy-Efficient Spiking Neural Network Inference considering Approximate DRAMs for Embedded Systems. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2023	—	`conf`	Mantis: Enabling Energy-Efficient Autonomous Mobile Agents with Spiking Neural Networks. ICARA Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2023	J	`jnl`	RescueSNN: Enabling Reliable Executions on Spiking Neural Network Accelerators under Permanent Faults. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2023	A	`conf`	TopSpark: A Timestep Optimization Methodology for Energy-Efficient Spiking Neural Networks on Autonomous Mobile Agents. IROS Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2023	J	`jnl`	TopSpark: A Timestep Optimization Methodology for Energy-Efficient Spiking Neural Networks on Autonomous Mobile Agents. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2022	J	`jnl`	Mantis: Enabling Energy-Efficient Autonomous Mobile Agents with Spiking Neural Networks. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2022	J	`jnl`	SoftSNN: Low-Cost Fault Tolerance for Spiking Neural Network Accelerators under Soft Errors. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2022	A*	`conf`	SoftSNN: low-cost fault tolerance for spiking neural network accelerators under soft errors. DAC Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2022	B	`conf`	lpSpikeCon: Enabling Low-Precision Spiking Neural Network Processing for Efficient Unsupervised Continual Learning on Autonomous Agents. IJCNN Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2022	J	`jnl`	lpSpikeCon: Enabling Low-Precision Spiking Neural Network Processing for Efficient Unsupervised Continual Learning on Autonomous Agents. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2022	J	`jnl`	tinySNN: Towards Memory- and Energy-Efficient Spiking Neural Networks. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2021	B	`conf`	Q-SpiNN: A Framework for Quantizing Spiking Neural Networks. IJCNN Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2021	J	`jnl`	Q-SpiNN: A Framework for Quantizing Spiking Neural Networks. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2021	J	`jnl`	ROMANet: Fine-Grained Reuse-Driven Off-Chip Memory Access Management and Data Organization for Deep Neural Network Accelerators. IEEE Trans. Very Large Scale Integr. Syst. Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2021	A	`conf`	ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories. ICCAD Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2021	J	`jnl`	ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2021	A*	`conf`	SparkXD: A Framework for Resilient and Energy-Efficient Spiking Neural Network Inference using Approximate DRAM. DAC Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2021	J	`jnl`	SparkXD: A Framework for Resilient and Energy-Efficient Spiking Neural Network Inference using Approximate DRAM. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2021	A*	`conf`	SpikeDyn: A Framework for Energy-Efficient Spiking Neural Networks with Continual and Unsupervised Learning Capabilities in Dynamic Environments. DAC Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2021	J	`jnl`	SpikeDyn: A Framework for Energy-Efficient Spiking Neural Networks with Continual and Unsupervised Learning Capabilities in Dynamic Environments. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2021	A	`conf`	Towards Energy-Efficient and Secure Edge AI: A Cross-Layer Framework ICCAD Special Session Paper. ICCAD Muhammad Shafique, Alberto Marchisio, Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif
2021	J	`jnl`	Towards Energy-Efficient and Secure Edge AI: A Cross-Layer Framework. CoRR Muhammad Shafique, Alberto Marchisio, Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif
2020	J	`jnl`	APNAS: Accuracy-and-Performance-Aware Neural Architecture Search for Neural Hardware Accelerators. IEEE Access Paniti Achararit, Muhammad Abdullah Hanif, Rachmad Vidya Wicaksana Putra, Muhammad Shafique, Yuko Hara-Azumi
2020	A*	`conf`	DRMap: A Generic DRAM Data Mapping Policy for Energy-Efficient Processing of Convolutional Neural Networks. DAC Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2020	J	`jnl`	DRMap: A Generic DRAM Data Mapping Policy for Energy-Efficient Processing of Convolutional Neural Networks. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2020	J	`jnl`	FSpiNN: An Optimization Framework for Memory- and Energy-Efficient Spiking Neural Networks. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2020	J	`jnl`	FSpiNN: An Optimization Framework for Memory-Efficient and Energy-Efficient Spiking Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Rachmad Vidya Wicaksana Putra, Muhammad Shafique
2019	J	`jnl`	ROMANet: Fine-Grained Reuse-Driven Data Organization and Off-Chip Memory Access Management for Deep Neural Network Accelerators. CoRR Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2018	—	`conf`	HW/SW co-design and co-optimizations for deep learning. INTESA@ESWEEK Alberto Marchisio, Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2018	J	`jnl`	MPNA: A Massively-Parallel Neural Array Accelerator with Dataflow Optimization for Convolutional Neural Networks. CoRR Muhammad Abdullah Hanif, Rachmad Vidya Wicaksana Putra, Muhammad Tanvir, Rehan Hafiz, Semeen Rehman, Muhammad Shafique
2018	C	`conf`	Robust Machine Learning Systems: Reliability and Security for Deep Neural Networks. IOLTS Muhammad Abdullah Hanif, Faiq Khalid, Rachmad Vidya Wicaksana Putra, Semeen Rehman, Muhammad Shafique
2016	—	`conf`	An architecture design of SAD based template matching for fast queue counter in FPGA. ISPACS Trio Adiono, Mahendra Drajat Adhinata, Novi Prihatiningrum, Ricky Disastra, Rachmad Vidya Wicaksana Putra, Amy Hamidah Salman
2016	—	`conf`	Analog filters design in VLC analog front-end receiver for reducing indoor ambient light noise. APCCAS Trio Adiono, Angga Pradana, Rachmad Vidya Wicaksana Putra, Syifaul Fuada
2016	—	`conf`	Kurtosis and energy based spectrum detection for SDR based RF monitoring system. ISPACS Prasetiyo, Rachmad Vidya Wicaksana Putra, Trio Adiono, Amy Hamidah Salman
2016	—	`conf`	Live demonstration: MINDS - Meshed and internet networked devices system for smart home: Track selection: Embedded systems. APCCAS Trio Adiono, Maulana Yusuf Fathany, Rachmad Vidya Wicaksana Putra, Khilda Afifah, Muhammad Husni Santriaji, Braham Lawas Lawu, Syifaul Fuada
2016	—	`conf`	Parallel morphological template matching design for efficient human detection application. ISPACS Trio Adiono, Radhian Ferel Armansyah, Fadhli Dzil Ikram, Swizya Satira Nolika, Rachmad Vidya Wicaksana Putra, Amy Hamidah Salman
2015	—	`conf`	Optimized hardware algorithm for integer cube root calculation and its efficient architecture. ISPACS Rachmad Vidya Wicaksana Putra, Trio Adiono
2014	—	`conf`	A register-free and homogenous architecture for square root algorithm. IC3INA Rachmad Vidya Wicaksana Putra, Trio Adiono
2011	—	`conf`	The efficient mCBE algorithm and quantization numbers for multiplierless and low complexity DCT/IDCT Image Compression Architecture. ICEEI Rachmad Vidya Wicaksana Putra, Rella Mareta, Nurfitri Anbarsanti, Trio Adiono

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.