Gengyu Wang - RankMe

16 papers B 1Journal 7Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Fast Algorithms for Group Markov Centrality Optimization. KDD (1) Gengyu Wang, Haisong Xia, Runze Zhang, Zhongzhi Zhang
2025	—	`conf`	Efficient Algorithms for Relevant Quantities of Friedkin-Johnsen Opinion Dynamics Model. KDD (2) Gengyu Wang, Runze Zhang, Zhongzhi Zhang
2025	J	`jnl`	Efficient Algorithms for Relevant Quantities of Friedkin-Johnsen Opinion Dynamics Model. CoRR Gengyu Wang, Runze Zhang, Zhongzhi Zhang
2025	J	`jnl`	Opinion Maximization in Social Networks by Modifying Internal Opinions. CoRR Gengyu Wang, Runze Zhang, Zhongzhi Zhang
2024	J	`jnl`	Practical token pruning for foundation models in few-shot conversational virtual assistant systems. CoRR Haode Qi, Cheng Qian, Jian Ni, Pratyush Singh, Reza Fazeli, Gengyu Wang, Zhongzheng Shu, Eric Wayne, Juergen Bross
2023	—	`conf`	Check-COVID: Fact-Checking COVID-19 News Claims with Scientific Evidence. ACL (Findings) Gengyu Wang, Kate Harwood, Lawrence Chillrud, Amith Ananthram, Melanie Subbiah, Kathleen R. McKeown
2023	J	`jnl`	Check-COVID: Fact-Checking COVID-19 News Claims with Scientific Evidence. CoRR Gengyu Wang, Kate Harwood, Lawrence Chillrud, Amith Ananthram, Melanie Subbiah, Kathleen R. McKeown
2023	J	`jnl`	Distinguish Sense from Nonsense: Out-of-Scope Detection for Virtual Assistants. CoRR Cheng Qian, Haode Qi, Gengyu Wang, Ladislav Kunc, Saloni Potdar
2023	—	`conf`	IdealGPT: Iteratively Decomposing Vision and Language Reasoning via Large Language Models. EMNLP (Findings) Haoxuan You, Rui Sun, Zhecan Wang, Long Chen, Gengyu Wang, Hammad A. Ayyubi, Kai-Wei Chang, Shih-Fu Chang
2023	J	`jnl`	IdealGPT: Iteratively Decomposing Vision and Language Reasoning via Large Language Models. CoRR Haoxuan You, Rui Sun, Zhecan Wang, Long Chen, Gengyu Wang, Hammad A. Ayyubi, Kai-Wei Chang, Shih-Fu Chang
2022	—	`conf`	Distinguish Sense from Nonsense: Out-of-Scope Detection for Virtual Assistants. EMNLP (Industry Track) Cheng Qian, Haode Qi, Gengyu Wang, Ladislav Kunc, Saloni Potdar
2021	—	`conf`	Evidence based Automatic Fact-Checking for Climate Change Misinformation. ICWSM Workshops Gengyu Wang, Lawrence Chillrud, Kathleen R. McKeown
2021	—	`conf`	Semantic Categorization of Social Knowledge for Commonsense Question Answering. SustaiNLP@EMNLP Gengyu Wang, Xiaochen Hou, Diyi Yang, Kathleen R. McKeown, Jing Huang
2021	J	`jnl`	Semantic Categorization of Social Knowledge for Commonsense Question Answering. CoRR Gengyu Wang, Xiaochen Hou, Diyi Yang, Kathleen R. McKeown, Jing Huang
2019	—	`conf`	Soft Representation Learning for Sparse Transfer. ACL (1) Haeju Park, Jinyoung Yeo, Gengyu Wang, Seung-won Hwang
2018	B	`conf`	Visual Choice of Plausible Alternatives: An Evaluation of Image-based Commonsense Causal Reasoning. LREC Jinyoung Yeo, Gyeongbok Lee, Gengyu Wang, Seungtaek Choi, Hyunsouk Cho, Reinald Kim Amplayo, Seung-won Hwang

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.