Quentin Guimard

13 papers A* 1A 4B 1Journal 4Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	SEM: Sparse Embedding Modulation for Post-Hoc Debiasing of Vision-Language Models. CoRR Quentin Guimard, Federico Bartsch, Simone Caldarella, Rahaf Aljundi, Elisa Ricci, Massimiliano Mancini
2025	A*	`conf`	Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers. CVPR Quentin Guimard, Moreno D'Incà, Massimiliano Mancini, Elisa Ricci
2025	J	`jnl`	Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers. CoRR Quentin Guimard, Moreno D'Incà, Massimiliano Mancini, Elisa Ricci
2024	J	`jnl`	Deep Variational Learning for 360° Adaptive Streaming. ACM Trans. Multim. Comput. Commun. Appl. Quentin Guimard, Lucile Sassatelli, Francesco Marchetti, Federico Becattini, Lorenzo Seidenari, Alberto Del Bimbo
2023	—	`—`	Deep learning for adaptive 360° video streaming in virtual reality. (Deep learning pour le streaming adaptatif de vidéos à 360° en réalité virtuelle). Quentin Guimard
2023	—	`conf`	PEM360: A dataset of 360° videos with continuous Physiological measurements, subjective Emotional ratings and Motion traces. IMX Workshops Florent Robert, Quentin Guimard, Lucile Sassatelli, Hui-Yin Wu, Marco Winckler, Auriane Gros
2023	A	`conf`	SMART360: Simulating Motion prediction and Adaptive bitRate sTrategies for 360° video streaming. MMSys Quentin Guimard, Lucile Sassatelli
2022	A	`conf`	Deep variational learning for multiple trajectory prediction of 360° head movements. MMSys Quentin Guimard, Lucile Sassatelli, Francesco Marchetti, Federico Becattini, Lorenzo Seidenari, Alberto Del Bimbo
2022	—	`conf`	Effects of emotions on head motion predictability in 360° videos. MMVE@MMSys Quentin Guimard, Lucile Sassatelli
2022	A	`conf`	Machine learning-based strategies for streaming and experiencing 3DoF virtual reality: research proposal. MMSys Quentin Guimard, Lucile Sassatelli
2022	B	`conf`	On The Link Between Emotion, Attention And Content In Virtual Immersive Environments. ICIP Quentin Guimard, Florent Robert, Camille Bauce, Aldric Ducreux, Lucile Sassatelli, Hui-Yin Wu, Marco Winckler, Auriane Gros
2022	A	`conf`	PEM360: a dataset of 360° videos with continuous physiological measurements, subjective emotional ratings and motion traces. MMSys Quentin Guimard, Florent Robert, Camille Bauce, Aldric Ducreux, Lucile Sassatelli, Hui-Yin Wu, Marco Winckler, Auriane Gros
2021	J	`jnl`	Early Detection of Security-Relevant Bug Reports using Machine Learning: How Far Are We? CoRR Arthur D. Sawadogo, Quentin Guimard, Tegawendé F. Bissyandé, Abdoul Kader Kaboré, Jacques Klein, Naouel Moha

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.