Lalla Mouatadid

25 papers A 2B 1C 1Journal 14Unranked 6

Year	Rank	Type	Title / Venue / Authors
2024	A	`conf`	DECDM: Document Enhancement using Cycle-Consistent Diffusion Models. WACV Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das, Kumar Sricharan
2024	—	`conf`	RE²: Region-Aware Relation Extraction from Visually Rich Documents. NAACL-HLT Pritika Ramu, Sijia Wang, Lalla Mouatadid, Joy Rimchala, Lifu Huang
2024	—	`conf`	SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models. EACL (1) Xiang Gao, Jiaxin Zhang, Lalla Mouatadid, Kamalika Das
2024	J	`jnl`	SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models. CoRR Xiang Gao, Jiaxin Zhang, Lalla Mouatadid, Kamalika Das
2024	J	`jnl`	\(\boldsymbol{(\alpha, \beta )}\)-Modules in Graphs. SIAM J. Discret. Math. Michel Habib, Lalla Mouatadid, Éric Sopena, Mengchuan Zou
2023	J	`jnl`	A Scalable Technique for Weak-Supervised Learning with Domain Constraints. CoRR Sudhir Agarwal, Anu Sreepathy, Lalla Mouatadid
2023	J	`jnl`	A new graph parameter to measure linearity. J. Graph Theory Pierre Charbit, Michel Habib, Lalla Mouatadid, Reza Naserasr
2023	J	`jnl`	DECDM: Document Enhancement using Cycle-Consistent Diffusion Models. CoRR Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das, Kumar Sricharan
2023	J	`jnl`	RE CoRR Pritika Ramu, Sijia Wang, Lalla Mouatadid, Joy Rimchala, Lifu Huang
2022	J	`jnl`	A general algorithmic scheme for combinatorial decompositions with application to modular decompositions of hypergraphs. Theor. Comput. Sci. Michel Habib, Fabien de Montgolfier, Lalla Mouatadid, Mengchuan Zou
2022	—	`conf`	Actionable Recommendations for Small Businesses With Hybrid AI. AAAI Spring Symposium: MAKE Sudhir Agarwal, Lalla Mouatadid, Anu Sreepathy, Kevin Furbish, Morgen Kimbrell, Mike Gabriel
2022	A	`conf`	Mining Frequent Patterns on Knowledge Graphs. WSDM Lalla Mouatadid
2021	J	`jnl`	(α, β)-Modules in Graphs. CoRR Michel Habib, Lalla Mouatadid, Éric Sopena, Mengchuan Zou
2020	—	`conf`	Approximating Modular Decomposition Is Hard. CALDAM Michel Habib, Lalla Mouatadid, Mengchuan Zou
2020	J	`jnl`	Maximum Induced Matching Algorithms via Vertex Ordering Characterizations. Algorithmica Michel Habib, Lalla Mouatadid
2019	C	`conf`	A General Algorithmic Scheme for Modular Decompositions of Hypergraphs and Applications. IWOCA Michel Habib, Fabien de Montgolfier, Lalla Mouatadid, Mengchuan Zou
2018	—	`—`	Efficient Algorithms on Cocomparability Graphs via Vertex Orderings. Lalla Mouatadid
2017	—	`conf`	A New Graph Parameter to Measure Linearity. COCOA (2) Pierre Charbit, Michel Habib, Lalla Mouatadid, Reza Naserasr
2017	B	`conf`	Maximum Induced Matching Algorithms via Vertex Ordering Characterizations. ISAAC Michel Habib, Lalla Mouatadid
2017	J	`jnl`	Maximum Induced Matching Algorithms via Vertex Ordering Characterizations. CoRR Michel Habib, Lalla Mouatadid
2017	J	`jnl`	Towards A Unified View of Linear Structure on Graph Classes. CoRR Pierre Charbit, Michel Habib, Lalla Mouatadid, Reza Naserasr
2016	J	`jnl`	A linear time algorithm to compute a maximum weighted independent set on cocomparability graphs. Inf. Process. Lett. Ekkehard Köhler, Lalla Mouatadid
2015	J	`jnl`	Path Graphs, Clique Trees, and Flowers. CoRR Lalla Mouatadid, Robert Robere
2014	—	`conf`	Linear Time LexDFS on Cocomparability Graphs. SWAT Ekkehard Köhler, Lalla Mouatadid
2014	J	`jnl`	Linear Time LexDFS on Cocomparability Graphs. CoRR Ekkehard Köhler, Lalla Mouatadid

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.