Sabyasachi Sahoo

13 papers A* 3A 1Journal 9

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	A Layer Selection Approach to Test Time Adaptation. AAAI Sabyasachi Sahoo, Mostafa ElAraby, Jonas Ngnawé, Yann Batiste Pequignot, Frédéric Precioso, Christian Gagné
2025	J	`jnl`	GROOD: GRadient-Aware Out-of-Distribution Detection. Trans. Mach. Learn. Res. Mostafa ElAraby, Sabyasachi Sahoo, Yann Pequignot, Paul Novello, Liam Paull
2025	J	`jnl`	Robust Fine-Tuning from Non-Robust Pretrained Models: Mitigating Suboptimal Transfer With Adversarial Scheduling. CoRR Jonas Ngnawé, Maxime Heuillet, Sabyasachi Sahoo, Yann Pequignot, Ola Ahmad, Audrey Durand, Frédéric Precioso, Christian Gagné
2024	A*	`conf`	Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers. NeurIPS Jonas Ngnawé, Sabyasachi Sahoo, Yann Pequignot, Frédéric Precioso, Christian Gagné
2024	J	`jnl`	Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers. CoRR Jonas Ngnawé, Sabyasachi Sahoo, Yann Pequignot, Frédéric Precioso, Christian Gagné
2024	J	`jnl`	Hessian Aware Low-Rank Perturbation for Order-Robust Continual Learning. IEEE Trans. Knowl. Data Eng. Jiaqi Li, Yuanhao Lai, Rui Wang, Changjian Shui, Sabyasachi Sahoo, Charles X. Ling, Shichun Yang, Boyu Wang, Christian Gagné, Fan Zhou
2024	J	`jnl`	Layerwise Early Stopping for Test Time Adaptation. CoRR Sabyasachi Sahoo, Mostafa ElAraby, Jonas Ngnawé, Yann Pequignot, Frédéric Precioso, Christian Gagné
2023	A	`conf`	Differentiable SLAM Helps Deep Learning-based LiDAR Perception Tasks. BMVC Prashant Kumar, Dheeraj Vattikonda, Vedang Bhupesh Shenvi Nadkarni, Erqun Dong, Sabyasachi Sahoo
2023	J	`jnl`	Differentiable SLAM Helps Deep Learning-based LiDAR Perception Tasks. CoRR Prashant Kumar, Dheeraj Vattikonda, Vedang Bhupesh Shenvi Nadkarni, Erqun Dong, Sabyasachi Sahoo
2023	J	`jnl`	GROOD: GRadient-aware Out-Of-Distribution detection in interpolated manifolds. CoRR Mostafa ElAraby, Sabyasachi Sahoo, Yann Pequignot, Paul Novello, Liam Paull
2023	J	`jnl`	Hessian Aware Low-Rank Weight Perturbation for Continual Learning. CoRR Jiaqi Li, Rui Wang, Yuanhao Lai, Changjian Shui, Sabyasachi Sahoo, Charles X. Ling, Shichun Yang, Boyu Wang, Christian Gagné, Fan Zhou
2021	J	`jnl`	DSLR: Dynamic to Static LiDAR Scan Reconstruction Using Adversarially Trained Autoencoder. CoRR Prashant Kumar, Sabyasachi Sahoo, Vanshil Shah, Vineetha Kondameedi, Abhinav Jain, Akshaj Verma, Chiranjib Bhattacharyya, Vinay Viswanathan
2021	A*	`conf`	Dynamic to Static Lidar Scan Reconstruction Using Adversarially Trained Auto Encoder. AAAI Prashant Kumar, Sabyasachi Sahoo, Vanshil Shah, Vineetha Kondameedi, Abhinav Jain, Akshaj Verma, Chiranjib Bhattacharyya, Vinay Vishwanath

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.