Zehao Dong - RankMe

17 papers A* 3A 1C 1Journal 11Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	DoseGNN: Improving the Performance of Deep Learning Models in Adaptive Dose-Volume Histogram Prediction through Graph Neural Networks. CoRR Zehao Dong, Yixin Chen, Tianyu Zhao
2024	J	`jnl`	Highly Accurate Disease Diagnosis and Highly Reproducible Biomarker Identification with PathFormer. CoRR Zehao Dong, Qihang Zhao, Philip R. O. Payne, Michael A. Province, Carlos Cruchaga, Muhan Zhang, Tianyu Zhao, Yixin Chen, Fuhai Li
2024	J	`jnl`	Large-Language-Model Empowered Dose Volume Histogram Prediction for Intensity Modulated Radiotherapy. CoRR Zehao Dong, Yixin Chen, Hiram Gay, Yao Hao, Geoffrey D. Hugo, Pamela Samson, Tianyu Zhao
2024	A*	`conf`	Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability. ICLR Zehao Dong, Muhan Zhang, Philip R. O. Payne, Michael A. Province, Carlos Cruchaga, Tianyu Zhao, Fuhai Li, Yixin Chen
2024	J	`jnl`	SPGNN: Recognizing Salient Subgraph Patterns via Enhanced Graph Convolution and Pooling. CoRR Zehao Dong, Muhan Zhang, Yixin Chen
2023	A*	`conf`	CktGNN: Circuit Graph Neural Network for Electronic Design Automation. ICLR Zehao Dong, Weidong Cao, Muhan Zhang, Dacheng Tao, Yixin Chen, Xuan Zhang
2023	J	`jnl`	CktGNN: Circuit Graph Neural Network for Electronic Design Automation. CoRR Zehao Dong, Weidong Cao, Muhan Zhang, Dacheng Tao, Yixin Chen, Xuan Zhang
2023	—	`conf`	FRVidSwin:A Novel Video Captioning Model with Automatical Removal of Redundant Frames. ICIC (5) Zehao Dong, Yuehui Chen, Yi Cao, Yaou Zhao
2023	C	`conf`	GNNHLS: Evaluating Graph Neural Network Inference via High-Level Synthesis. ICCD Chenfeng Zhao, Zehao Dong, Yixin Chen, Xuan Zhang, Roger D. Chamberlain
2023	J	`jnl`	GNNHLS: Evaluating Graph Neural Network Inference via High-Level Synthesis. CoRR Chenfeng Zhao, Zehao Dong, Yixin Chen, Xuan Zhang, Roger D. Chamberlain
2023	J	`jnl`	Time Associated Meta Learning for Clinical Prediction. CoRR Hao Liu, Muhan Zhang, Zehao Dong, Lecheng Kong, Yixin Chen, Bradley A. Fritz, Dacheng Tao, Christopher Ryan King
2023	J	`jnl`	Universal Normalization Enhanced Graph Representation Learning for Gene Network Prediction. CoRR Zehao Dong, Muhan Zhang, Qihang Zhao, Philip R. O. Payne, Michael A. Province, Carlos Cruchaga, Tianyu Zhao, Yixin Chen, Fuhai Li
2022	J	`jnl`	Interpreting mechanism of Synergism of drug combinations using attention based hierarchical graph pooling. CoRR Zehao Dong, Yixin Chen, Philip R. O. Payne, Fuhai Li
2022	A*	`conf`	PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs. ICML Zehao Dong, Muhan Zhang, Fuhai Li, Yixin Chen
2022	J	`jnl`	PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs. CoRR Zehao Dong, Muhan Zhang, Fuhai Li, Yixin Chen
2021	A	`conf`	Efficient Nonmyopic Online Allocation of Scarce Reusable Resources. AAMAS Zehao Dong, Sanmay Das, Patrick J. Fowler, Chien-Ju Ho
2021	J	`jnl`	Interpretable Drug Synergy Prediction with Graph Neural Networks for Human-AI Collaboration in Healthcare. CoRR Zehao Dong, Heming Zhang, Yixin Chen, Fuhai Li

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.