Fangfang Tang - RankMe

15 papers A* 1Misc 1Journal 8Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	HiFi-Mamba: Dual-Stream ?-Laplacian Enhanced Mamba for High-Fidelity MRI Reconstruction. AAAI Hongli Chen, Pengcheng Fang, Yuxia Chen, Yingxuan Ren, Jing Hao, Fangfang Tang, Xiaohao Cai, Shanshan Shan, Feng Liu
2025	J	`jnl`	HiFi-Mamba: Dual-Stream W-Laplacian Enhanced Mamba for High-Fidelity MRI Reconstruction. CoRR Hongli Chen, Pengcheng Fang, Yuxia Chen, Yingxuan Ren, Jing Hao, Fangfang Tang, Xiaohao Cai, Shanshan Shan, Feng Liu
2025	J	`jnl`	HiFi-MambaV2: Hierarchical Shared-Routed MoE for High-Fidelity MRI Reconstruction. CoRR Pengcheng Fang, Hongli Chen, Guangzhen Yao, Jian Shi, Fangfang Tang, Xiaohao Cai, Shanshan Shan, Feng Liu
2025	J	`jnl`	Machine Well Screening Method Based on POI Data and DBSCAN Clustering Algorithm. IEEE Geosci. Remote. Sens. Lett. Xing Gan, Haiyan Fan, Moyuan Yang, Fangfang Tang, Honglu Liu, Zhijun Ma
2023	—	`conf`	AF automatic classification based on different time-delay values of the recurrence plot. EMBC Hua Zhang, Chengyu Liu, Fangfang Tang, Mingyan Li, Ling Xia, Stuart Crozier, Wenlong Xu, Feng Liu
2023	—	`conf`	An Improved Anchor-Free Nodule Detection System Using Feature Pyramid Network. EMBC Wenjia Song, Fangfang Tang, Henry Marshall, Kwun M. Fong, Feng Liu
2021	—	`conf`	Can3d: Fast 3d Knee Mri Segmentation Via Compact Context Aggregation. ISBI Wei Dai, Boyeong Woo, Siyu Liu, Matthew Marques, Fangfang Tang, Stuart Crozier, Craig Engstrom, Shekhar Chandra
2021	J	`jnl`	Deep Simultaneous Optimisation of Sampling and Reconstruction for Multi-contrast MRI. CoRR Xinwen Liu, Jing Wang, Fangfang Tang, Shekhar S. Chandra, Feng Liu, Stuart Crozier
2019	J	`jnl`	Gradient Field Deviation (GFD) Correction Using a Hybrid-Norm Approach With Wavelet Sub-Band Dependent Regularization: Implementation for Radial MRI at 9.4 T. IEEE Trans. Biomed. Eng. Shanshan Shan, Mingyan Li, Fangfang Tang, Huan Ma, Feng Liu, Stuart Crozier
2019	J	`jnl`	Numerical Design of High-Efficiency Whole-Body Gradient Coils With a Hybrid Cylindrical-Planar Structure. IEEE Trans. Biomed. Eng. Chaoqun Niu, Qiuliang Wang, Yang Hu, Yaohui Wang, Fangfang Tang, Feng Liu, Stuart Crozier
2017	J	`jnl`	Mitigation of Intra-coil Eddy Currents in Split Gradient Coils in a Hybrid MRI-LINAC System. IEEE Trans. Biomed. Eng. Fangfang Tang, Fabio Freschi, Maurizio Repetto, Yu Li, Feng Liu, Stuart Crozier
2016	—	`—`	Gradient coil design and intra-coil eddy currents in MRI systems Fangfang Tang
2012	J	`jnl`	Semi-Supervised Learning: Exploiting Unlabeled Data with Symmetrical Distribution and High confidence. Int. J. Pattern Recognit. Artif. Intell. Yihao Zhang, Junhao Wen, Fangfang Tang, Zhuo Jiang
2011	Misc	`conf`	A Stochastic-Petri-Net-Based Model for Ontology-Based Service Compositions. TASE Yunni Xia, Gang Dai, Fangfang Tang, Qingsheng Zhu
2011	—	`conf`	An Approach of Authentication Base on Modified Digital Identity Metasystem in Service-Oriented Architecture. WISM (1) Peng Li, Junhao Wen, Junping Dong, Fangfang Tang

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.