Ramchandran Muthukumar

11 papers A* 3Journal 8

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Disentangling Safe and Unsafe Corruptions via Anisotropy and Locality. CoRR Ramchandran Muthukumar, Ambar Pal, Jeremias Sulam, René Vidal
2025	A*	`conf`	Disentangling Safe and Unsafe Image Corruptions via Anisotropy and Locality. CVPR Ramchandran Muthukumar, Ambar Pal, Jeremias Sulam, René Vidal
2023	J	`jnl`	Adversarial Robustness of Sparse Local Lipschitz Predictors. SIAM J. Math. Data Sci. Ramchandran Muthukumar, Jeremias Sulam
2023	A*	`conf`	Sparsity-aware generalization theory for deep neural networks. COLT Ramchandran Muthukumar, Jeremias Sulam
2023	J	`jnl`	Sparsity-aware generalization theory for deep neural networks. CoRR Ramchandran Muthukumar, Jeremias Sulam
2022	J	`jnl`	Adversarial robustness of sparse local Lipschitz predictors. CoRR Ramchandran Muthukumar, Jeremias Sulam
2021	J	`jnl`	Randomized Sketching Algorithms for Low-Memory Dynamic Optimization. SIAM J. Optim. Ramchandran Muthukumar, Drew P. Kouri, Madeleine Udell
2020	J	`jnl`	A Study of Neural Training with Non-Gradient and Noise Assisted Gradient Methods. CoRR Anirbit Mukherjee, Ramchandran Muthukumar
2020	A*	`conf`	Adversarial Robustness of Supervised Sparse Coding. NeurIPS Jeremias Sulam, Ramchandran Muthukumar, Raman Arora
2020	J	`jnl`	Adversarial Robustness of Supervised Sparse Coding. CoRR Jeremias Sulam, Ramchandran Muthukumar, Raman Arora
2020	J	`jnl`	Guarantees on learning depth-2 neural networks under a data-poisoning attack. CoRR Anirbit Mukherjee, Ramchandran Muthukumar

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.