Baiming Chen - RankMe

20 papers A* 2A 2B 1Journal 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	PAIR-Former: Budgeted Relational MIL for miRNA Target Prediction. CoRR Jiaqi Yin, Baiming Chen, Jia Fei, Mingjun Yang
2026	J	`jnl`	Parasite: planting durable backdoors against continual federated model fusion via discriminative feature pushing-pulling. Inf. Fusion Tong Chen, Bowen Du, Jiejie Zhao, Jiakai Wang, Haiquan Wang, Yuxi Li, Baiming Chen, Weifeng Lv
2022	J	`jnl`	Adversarial Evaluation of Autonomous Vehicles in Lane-Change Scenarios. IEEE Trans. Intell. Transp. Syst. Baiming Chen, Xiang Chen, Qiong Wu, Liang Li
2021	A*	`conf`	Context-Aware Safe Reinforcement Learning for Non-Stationary Environments. ICRA Baiming Chen, Zuxin Liu, Jiacheng Zhu, Mengdi Xu, Wenhao Ding, Liang Li, Ding Zhao
2021	J	`jnl`	Context-Aware Safe Reinforcement Learning for Non-Stationary Environments. CoRR Baiming Chen, Zuxin Liu, Jiacheng Zhu, Mengdi Xu, Wenhao Ding, Ding Zhao
2021	J	`jnl`	Delay-aware model-based reinforcement learning for continuous control. Neurocomputing Baiming Chen, Mengdi Xu, Liang Li, Ding Zhao
2021	J	`jnl`	Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation. IEEE Robotics Autom. Lett. Wenhao Ding, Baiming Chen, Bo Li, Kim Ji Eun, Ding Zhao
2020	J	`jnl`	Adversarial Evaluation of Autonomous Vehicles in Lane-Change Scenarios. CoRR Baiming Chen, Liang Li
2020	J	`jnl`	Delay-Aware Model-Based Reinforcement Learning for Continuous Control. CoRR Baiming Chen, Mengdi Xu, Liang Li, Ding Zhao
2020	J	`jnl`	Delay-Aware Multi-Agent Reinforcement Learning. CoRR Baiming Chen, Mengdi Xu, Zuxin Liu, Liang Li, Ding Zhao
2020	A	`conf`	Learning to Collide: An Adaptive Safety-Critical Scenarios Generating Method. IROS Wenhao Ding, Baiming Chen, Minjun Xu, Ding Zhao
2020	A	`conf`	MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments. IROS Zuxin Liu, Baiming Chen, Hongyi Zhou, Guru Koushik, Martial Hebert, Ding Zhao
2020	J	`jnl`	MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments. CoRR Zuxin Liu, Baiming Chen, Hongyi Zhou, Guru Koushik, Martial Hebert, Ding Zhao
2020	J	`jnl`	Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation. CoRR Wenhao Ding, Baiming Chen, Bo Li, Kim Ji Eun, Ding Zhao
2020	J	`jnl`	Safe Model-based Reinforcement Learning with Robust Cross-Entropy Method. CoRR Zuxin Liu, Hongyi Zhou, Baiming Chen, Sicheng Zhong, Martial Hebert, Ding Zhao
2020	A*	`conf`	Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes. NeurIPS Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao
2020	J	`jnl`	Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes. CoRR Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao
2018	J	`jnl`	Hierarchical Lateral Control Scheme for Autonomous Vehicle with Uneven Time Delays Induced by Vision Sensors. Sensors Qi Liu, Yahui Liu, Congzhi Liu, Baiming Chen, Wenhao Zhang, Liang Li, Xuewu Ji
2017	J	`jnl`	Evaluation of Automated Vehicles Encountering Pedestrians at Unsignalized Crossings. CoRR Baiming Chen, Ding Zhao, Huei Peng
2017	B	`conf`	Evaluation of automated vehicles encountering pedestrians at unsignalized crossings. Intelligent Vehicles Symposium Baiming Chen, Ding Zhao, Huei Peng

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.