Yangxintong Lyu

16 papers B 3C 2Misc 1Journal 9Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	FP8ApproxLib: An FPGA-based approximate multiplier library for 8-bit floating point. J. Syst. Archit. Ruiqi Chen, Yangxintong Lyu, Han Bao, Shidi Tang, Jindong Li, Yanxiang Zhu, Ming Ling, Bruno da Silva
2025	Misc	`conf`	FPGA-Based Approximate Multiplier for FP8. FCCM Ruiqi Chen, Yangxintong Lyu, Han Bao, Jiayu Liu, Yanxiang Zhu, Shidi Tang, Ming Ling, Bruno da Silva
2025	J	`jnl`	HybridTrack: A Hybrid Approach for Robust Multi-Object Tracking. CoRR Leandro Di Bella, Yangxintong Lyu, Bruno Cornelis, Adrian Munteanu
2025	J	`jnl`	HybridTrack: A Hybrid Approach for Robust Multi-Object Tracking. IEEE Robotics Autom. Lett. Leandro Di Bella, Yangxintong Lyu, Bruno Cornelis, Adrian Munteanu
2024	J	`jnl`	A Power-Efficient Hardware Implementation of L-Mul. CoRR Ruiqi Chen, Yangxintong Lyu, Han Bao, Bruno da Silva
2024	J	`jnl`	DeepKalPose: An Enhanced Deep-Learning Kalman Filter for Temporally Consistent Monocular Vehicle Pose Estimation. CoRR Leandro Di Bella, Yangxintong Lyu, Adrian Munteanu
2024	C	`conf`	LAM3D: Leveraging Attention for Monocular 3D Object Detection. MMSP Diana-Alexandra Sas, Leandro Di Bella, Yangxintong Lyu, Florin Oniga, Adrian Munteanu
2024	J	`jnl`	LAM3D: Leveraging Attention for Monocular 3D Object Detection. CoRR Diana-Alexandra Sas, Leandro Di Bella, Yangxintong Lyu, Florin Oniga, Adrian Munteanu
2024	B	`conf`	MonoKalman: Monocular Vehicle Pose Estimation with Kalman Filter-based temporal consistency. MDM Leandro Di Bella, Yangxintong Lyu, Bruno Cornelis, Adrian Munteanu
2024	B	`conf`	STRADA: Spatial-Temporal Dashboard for traffic forecasting. MDM Seyed Mohamad Moghadas, Yangxintong Lyu, Bruno Cornelis, Adrian Munteanu
2024	J	`jnl`	W6DNet: Weakly Supervised Domain Adaptation for Monocular Vehicle 6-D Pose Estimation With 3-D Priors and Synthetic Data. IEEE Trans. Instrum. Meas. Yangxintong Lyu, Remco Royen, Adrian Munteanu
2023	—	`conf`	Mono6D++: Learning Point Cloud Visibility for 3D Prior-based Vehicle 6D Pose Estimation. EUVIP Yangxintong Lyu, Olivier Ducastel, Remco Royen, Adrian Munteanu
2023	C	`conf`	Occlusion-Aware 3D Priors for Deep Learning-Based Applications. MMSP Olivier Ducastel, Yangxintong Lyu, Leon Denis, Adrian Munteanu
2022	J	`jnl`	Framework for Vehicle Make and Model Recognition - A New Large-Scale Dataset and an Efficient Two-Branch-Two-Stage Deep Learning Architecture. Sensors Yangxintong Lyu, Ionut Schiopu, Bruno Cornelis, Adrian Munteanu
2022	B	`conf`	MONO6D: Monocular Vehicle 6D Pose Estimation with 3D Priors. ICIP Yangxintong Lyu, Remco Royen, Adrian Munteanu
2019	J	`jnl`	Consistent video projection on curved displays. Signal Process. Image Commun. Yangxintong Lyu, Shao-Ping Lu, Quentin Bolsee, Adrian Munteanu

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.