Zewen Liu - RankMe

18 papers A* 2Journal 13Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	EpiQAL: Benchmarking Large Language Models in Epidemiological Question Answering for Enhanced Alignment and Reasoning. CoRR Mingyang Wei, Dehai Min, Zewen Liu, Yuzhang Xie, Guanchen Wu, Carl Yang, Max S. Y. Lau, Qi He, Lu Cheng, Wei Jin
2026	J	`jnl`	Exposing Vulnerabilities in Explanation for Time Series Classifiers via Dual-Target Attacks. CoRR Bohan Wang, Zewen Liu, Lu Lin, Hui Liu, Li Xiong, Ming Jin, Wei Jin
2026	—	`conf`	TimeDistill: Efficient Long-Term Time Series Forecasting with MLP via Cross-Architecture Distillation. KDD (1) Juntong Ni, Zewen Liu, Shiyu Wang, Ming Jin, Wei Jin
2025	J	`jnl`	Are We Overlooking the Dimensions? Learning Latent Hierarchical Channel Structure for High-Dimensional Time Series Forecasting. CoRR Juntong Ni, Shiyu Wang, Zewen Liu, Xiaoming Shi, Xinyue Zhong, Zhou Ye, Wei Jin
2025	J	`jnl`	CAPE: Covariate-Adjusted Pre-Training for Epidemic Time Series Forecasting. CoRR Zewen Liu, Juntong Ni, Max S. Y. Lau, Wei Jin
2025	J	`jnl`	Can Large Language Models Adequately Perform Symbolic Reasoning Over Time Series? CoRR Zewen Liu, Juntong Ni, Xianfeng Tang, Max S. Y. Lau, Wenpeng Yin, Wei Jin
2025	A*	`conf`	EARTH: Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph. ICML Guancheng Wan, Zewen Liu, Xiaojun Shan, Max S. Y. Lau, B. Aditya Prakash, Wei Jin
2025	—	`conf`	Efficient Epidemic Intervention Generation: A Graph Adversarial Attack Perspective. WWW (Companion Volume) Yunxiao Li, Mingyang Wei, Zewen Liu, Max S. Y. Lau, Wei Jin
2025	J	`jnl`	Generalist vs Specialist Time Series Foundation Models: Investigating Potential Emergent Behaviors in Assessing Human Health Using PPG Signals. CoRR Saurabh Kataria, Yi Wu, Zhaoliang Chen, Gloria Hyunjung Kwak, Yuhao Xu, Lovely Yeswanth Panchumarthi, Ran Xiao, Jiaying Lu, Ayca Ermis, Anni Zhao, Runze Yan, Alex Federov, Zewen Liu, Xu Wu, Wei Jin, Carl Yang, Jocelyn Grunwell, Stephanie R. Brown, Amit J. Shah, Craig S. Jabaley, Timothy G. Buchman, Sivasubramanium V. Bhavani, Randall J. Lee, Xiao Hu
2025	—	`conf`	Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks. KDD (2) Zewen Liu, Xiaoda Wang, Bohan Wang, Zijie Huang, Carl Yang, Wei Jin
2025	J	`jnl`	Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks. CoRR Zewen Liu, Xiaoda Wang, Bohan Wang, Zijie Huang, Carl Yang, Wei Jin
2025	J	`jnl`	Higher-order Interaction Matters: Dynamic Hypergraph Neural Networks for Epidemic Modeling. CoRR Songyuan Liu, Shengbo Gong, Tianning Feng, Zewen Liu, Max S. Y. Lau, Wei Jin
2025	J	`jnl`	TimeDistill: Efficient Long-Term Time Series Forecasting with MLP via Cross-Architecture Distillation. CoRR Juntong Ni, Zewen Liu, Shiyu Wang, Ming Jin, Wei Jin
2024	A*	`conf`	A Review of Graph Neural Networks in Epidemic Modeling. KDD Zewen Liu, Guancheng Wan, B. Aditya Prakash, Max S. Y. Lau, Wei Jin
2024	J	`jnl`	A Review of Graph Neural Networks in Epidemic Modeling. CoRR Zewen Liu, Guancheng Wan, B. Aditya Prakash, Max S. Y. Lau, Wei Jin
2024	J	`jnl`	EpiLearn: A Python Library for Machine Learning in Epidemic Modeling. CoRR Zewen Liu, Yunxiao Li, Mingyang Wei, Guancheng Wan, Max S. Y. Lau, Wei Jin
2024	J	`jnl`	Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph. CoRR Guancheng Wan, Zewen Liu, Max S. Y. Lau, B. Aditya Prakash, Wei Jin
2024	J	`jnl`	Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness. CoRR Kai Guo, Zewen Liu, Zhikai Chen, Hongzhi Wen, Wei Jin, Jiliang Tang, Yi Chang

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.