Yaniv Sadeh - RankMe

18 papers A* 3A 2B 1Journal 11Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond Vizing Chains: Improved Recourse in Dynamic Edge Coloring. CoRR Yaniv Sadeh, Haim Kaplan
2025	J	`jnl`	Search Trees on Trees via LP. CoRR Yaniv Sadeh, Haim Kaplan, Uri Zwick
2024	A*	`conf`	Caching Connections in Matchings. ICALP Yaniv Sadeh, Haim Kaplan
2023	J	`jnl`	Caching Connections in Matchings. CoRR Yaniv Sadeh, Haim Kaplan
2023	A	`conf`	Dynamic Binary Search Trees: Improved Lower Bounds for the Greedy-Future Algorithm. STACS Yaniv Sadeh, Haim Kaplan
2023	J	`jnl`	Dynamic Binary Search Trees: Improved Lower Bounds for the Greedy-Future Algorithm. CoRR Yaniv Sadeh, Haim Kaplan
2023	J	`jnl`	Load Balancing With Minimal Deviation in Switch Memories. IEEE Trans. Netw. Serv. Manag. Yaniv Sadeh, Ori Rottenstreich, Haim Kaplan
2022	J	`jnl`	Codes for Load Balancing in TCAMs: Size Analysis. CoRR Yaniv Sadeh, Ori Rottenstreich, Haim Kaplan
2022	B	`conf`	Coding Size of Traffic Partition in Switch Memories. ISIT Yaniv Sadeh, Ori Rottenstreich, Haim Kaplan
2022	A*	`conf`	Minimal Total Deviation in TCAM Load Balancing. INFOCOM Yaniv Sadeh, Ori Rottenstreich, Haim Kaplan
2022	J	`jnl`	On Ranges and Partitions in Optimal TCAMs. CoRR Yaniv Sadeh
2022	J	`jnl`	Optimal Weighted Load Balancing in TCAMs. IEEE/ACM Trans. Netw. Yaniv Sadeh, Ori Rottenstreich, Haim Kaplan
2021	—	`conf`	How Much TCAM do we Need for Splitting Traffic? SOSR Yaniv Sadeh, Ori Rottenstreich, Haim Kaplan
2021	J	`jnl`	Optimal Weighted Load Balancing in TCAMs. CoRR Yaniv Sadeh, Ori Rottenstreich, Haim Kaplan
2020	J	`jnl`	Optimal Representations of a Traffic Distribution in Switch Memories. IEEE/ACM Trans. Netw. Yaniv Sadeh, Ori Rottenstreich, Arye Barkan, Yossi Kanizo, Haim Kaplan
2020	A	`conf`	Optimal approximations for traffic distribution in bounded switch memories. CoNEXT Yaniv Sadeh, Ori Rottenstreich, Haim Kaplan
2019	A*	`conf`	Optimal Representations of a Traffic Distribution in Switch Memories. INFOCOM Yaniv Sadeh, Ori Rottenstreich, Arye Barkan, Yossi Kanizo, Haim Kaplan
2016	J	`jnl`	The Emergence of Synaesthesia in a Neuronal Network Model via Changes in Perceptual Sensitivity and Plasticity. PLoS Comput. Biol. Oren Shriki, Yaniv Sadeh, Jamie Ward

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.