Qi Qi - RankMe

19 papers B 1C 3Journal 6Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	BioGuard: Malicious sample free defense method for biometric classifiers against model extraction attacks. Comput. Secur. Ziting Ren, Yucong Duan, Qi Qi
2024	J	`jnl`	DCWPSO: particle swarm optimization with dynamic inertia weight updating and enhanced learning strategies. PeerJ Comput. Sci. Yibo Han, Meiting Lin, Ni Li, Qi Qi, Jinqing Li, Qingxin Liu
2024	C	`conf`	Robust modeling of the multi-depot vehicle routing problem under uncertain demands. CSCWD Jinqing Li, Qi Qi, Ni Li, Yibo Han
2023	J	`jnl`	A chimp-inspired remora optimization algorithm for multilevel thresholding image segmentation using cross entropy. Artif. Intell. Rev. Qingxin Liu, Ni Li, Heming Jia, Qi Qi, Laith Abualigah
2023	C	`conf`	Federated Opposite Learning Based Arithmetic Optimization Algorithm for Image Segmentation Using Multilevel Thresholding. CSCWD Qingxin Liu, Qi Qi, Ni Li
2022	—	`conf`	SLEO: An efficient Equilibrium Optimizer for numerical optimization. SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta Qingxin Liu, Qi Qi, Ni Li
2021	—	`conf`	An Improved Slime Mould Algorithm with Quasi Reflection-based Learning for Global Optimization Problems. HPCC/DSS/SmartCity/DependSys Qingxin Liu, Qi Qi, Heming Jia, Ni Li
2021	—	`conf`	Organs-At-Risk Segmentation in Medical Imaging Based on the U-Net with Residual and Attention Mechanisms. HPCC/DSS/SmartCity/DependSys Xiao-Wei Lin, Ni Li, Qi Qi
2021	J	`jnl`	Using API Call Sequences for IoT Malware Classification Based on Convolutional Neural Networks. Int. J. Softw. Eng. Knowl. Eng. Qian-Guang Lin, Ni Li, Qi Qi, Jia-Bin Hu
2020	—	`conf`	A Semi-supervised Learning Approach for High Dimensional Android Malware Classification. CSS Qiao Shang, Ni Li, Qi Qi, Xiao-Wei Lin
2020	—	`conf`	Classification of IoT Malware based on Convolutional Neural Network. ICSS Qian-Guang Lin, Ni Li, Qi Qi, Jia-Bin Hu
2017	—	`conf`	Exploration of Heuristic-Based Feature Selection on Classification Problems. PAAP Qi Qi, Ni Li, Weimin Li
2017	C	`conf`	Health service provision based on typed resources of data, information and knowledge. Healthcom Lixu Shao, Yucong Duan, Donghai Zhu, Jinbing Li, Hui Zhou, Qi Qi
2016	—	`conf`	Estimating End-to-End Available Bandwidth for Cyber-Physical Applications in Hybrid Networks. WICON Hui Zhou, Chunyang Ye, Yucong Duan, Qi Qi, Yu Zhang
2011	J	`jnl`	Comparison of Probabilistic Chain Graphical Model-Based and Gaussian Process-Based Observation Selections for Wireless Sensor Scheduling. Int. J. Distributed Sens. Networks Qi Qi, Yi Shang
2010	B	`conf`	An improved algorithm for optimal subset selection in chain graphical models. IEEE Congress on Evolutionary Computation Qi Qi, Yi Shang, Hongchi Shi
2009	J	`jnl`	Wireless sensor networks in intelligent transportation systems. Wirel. Commun. Mob. Comput. Malik Ayed Tubaishat, Peng Zhuang, Qi Qi, Yi Shang
2008	—	`conf`	Model-Based Traffic Prediction Using Sensor Networks. CCNC Peng Zhuang, Qi Qi, Yi Shang, Hongchi Shi
2008	—	`conf`	Wireless Sensor-Based Traffic Light Control. CCNC Malik Ayed Tubaishat, Qi Qi, Yi Shang, Hongchi Shi

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.