Qiang Wu - RankMe

15 papers A* 4Journal 10Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Hardware-Software Co-design for 3D-DRAM-based LLM Serving Accelerator. CoRR Cong Li, Yihan Yin, Chenhao Xue, Zhao Wang, Fujun Bai, Yixin Guo, Xiping Jiang, Qiang Wu, Yuan Xie, Guangyu Sun
2026	A*	`conf`	OTARo: Once Tuning for All Precisions Toward Robust On-Device LLMs. AAAI Shaoyuan Chen, Zhixuan Chen, Dawei Yang, Zhihang Yuan, Qiang Wu
2026	A*	`conf`	VAEVQ: Enhancing Discrete Visual Tokenization Through Variational Modeling. AAAI Sicheng Yang, Xing Hu, Qiang Wu, Dawei Yang
2025	A*	`conf`	AIM: Software and Hardware Co-design for Architecture-level IR-drop Mitigation in High-performance PIM. ISCA Yuanpeng Zhang, Xing Hu, Xi Chen, Zhihang Yuan, Cong Li, Jingchen Zhu, Zhao Wang, Chenguang Zhang, Xin Si, Wei Gao, Qiang Wu, Runsheng Wang, Guangyu Sun
2025	J	`jnl`	AIM: Software and Hardware Co-design for Architecture-level IR-drop Mitigation in High-performance PIM. CoRR Yuanpeng Zhang, Xing Hu, Xi Chen, Zhihang Yuan, Cong Li, Jingchen Zhu, Zhao Wang, Chenguang Zhang, Xin Si, Wei Gao, Qiang Wu, Runsheng Wang, Guangyu Sun
2025	A*	`conf`	H ISCA Cong Li, Yihan Yin, Xintong Wu, Jingchen Zhu, Zhutianya Gao, Dimin Niu, Qiang Wu, Xin Si, Yuan Xie, Chen Zhang, Guangyu Sun
2025	J	`jnl`	OTARo: Once Tuning for All Precisions toward Robust On-Device LLMs. CoRR Shaoyuan Chen, Zhixuan Chen, Dawei Yang, Zhihang Yuan, Qiang Wu
2025	J	`jnl`	RSAVQ: Riemannian Sensitivity-Aware Vector Quantization for Large Language Models. CoRR Zukang Xu, Xing Hu, Qiang Wu, Dawei Yang
2025	J	`jnl`	VAEVQ: Enhancing Discrete Visual Tokenization through Variational Modeling. CoRR Sicheng Yang, Xing Hu, Qiang Wu, Dawei Yang
2023	J	`jnl`	ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models. CoRR Zhihang Yuan, Yuzhang Shang, Yue Song, Qiang Wu, Yan Yan, Guangyu Sun
2023	J	`jnl`	Benchmarking the Reliability of Post-training Quantization: a Particular Focus on Worst-case Performance. CoRR Zhihang Yuan, Jiawei Liu, Jiaxiang Wu, Dawei Yang, Qiang Wu, Guangyu Sun, Wenyu Liu, Xinggang Wang, Bingzhe Wu
2023	J	`jnl`	PB-LLM: Partially Binarized Large Language Models. CoRR Yuzhang Shang, Zhihang Yuan, Qiang Wu, Zhen Dong
2023	J	`jnl`	RPTQ: Reorder-based Post-training Quantization for Large Language Models. CoRR Zhihang Yuan, Lin Niu, Jiawei Liu, Wenyu Liu, Xinggang Wang, Yuzhang Shang, Guangyu Sun, Qiang Wu, Jiaxiang Wu, Bingzhe Wu
2022	—	`conf`	PTQ4ViT: Post-training Quantization for Vision Transformers with Twin Uniform Quantization. ECCV (12) Zhihang Yuan, Chenhao Xue, Yiqi Chen, Qiang Wu, Guangyu Sun
2021	J	`jnl`	PTQ4ViT: Post-Training Quantization Framework for Vision Transformers. CoRR Zhihang Yuan, Chenhao Xue, Yiqi Chen, Qiang Wu, Guangyu Sun

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.