Tao Li

21 papers A* 1Journal 14Unranked 6
YearRankTypeTitle / Venue / Authors
2026 J jnl
In-P
IEEE Trans. Aerosp. Electron. Syst.
Tao Li, Tong Hua, Jie Yin, Xusheng Yang, Wen-An Zhang, Ling Pei, Wenxian Yu, Trieu-Kien Truong
2025 — conf
A Deep Learning Positioning Framework Fusing Pseudorange, Carrier Phase, and Doppler Observations.
UPINLBS
Huarui Zhang, Songpengcheng Xia, Tao Li, Jiamin Wang, Ling Pei, Wen-An Zhang, Wenxian Yu
2025 J jnl
DLBAcalib: Robust Extrinsic Calibration for Non-Overlapping LiDARs Based on Dual LBA.
CoRR
Han Ye, Yuqiang Jin, Jinyuan Liu, Tao Li, Wen-An Zhang, Minglei Fu
2025 J jnl
In-P
IEEE Trans. Intell. Transp. Syst.
Tao Li, Tong Hua, Minglei Fu, Wen-An Zhang, Ling Pei, Wenxian Yu, Trieu-Kien Truong
2025 J jnl
SVA: A Street-View-Aided GNSS Positioning Framework With 2DSDM and Likelihood Road for NLOS/Multipath Mitigation.
IEEE Robotics Autom. Lett.
Mingxiang Gu, Tao Li, Guoqing Liu, Zongwei Liu, Chaoran Xiong, Chao Wang, Rui Duan, Fanchen Meng, Yan Xiang, Ling Pei
2024 J jnl
Sky-GVINS: a sky-segmentation aided GNSS-Visual-Inertial system for robust navigation in urban canyons.
Geo spatial Inf. Sci.
Jie Yin, Tao Li, Hao Yin, Wenxian Yu, Danping Zou
2023 J jnl
P
IEEE Trans. Instrum. Meas.
Tao Li, Ling Pei, Yan Xiang, Xingxing Zuo, Wenxian Yu, Trieu-Kien Truong
2023 A* conf
PIEKF-VIWO: Visual-Inertial-Wheel Odometry using Partial Invariant Extended Kalman Filter.
ICRA
Tong Hua, Tao Li, Ling Pei
2023 J jnl
PIEKF-VIWO: Visual-Inertial-Wheel Odometry using Partial Invariant Extended Kalman Filter.
CoRR
Tong Hua, Tao Li, Ling Pei
2023 — conf
PLV-IEKF: Consistent Visual-Inertial Odometry using Points, Lines, and Vanishing Points.
ROBIO
Tong Hua, Tao Li, Liang Pang, Guoqing Liu, Wencheng Xuanyuan, Chang Shu, Ling Pei
2023 J jnl
PLV-IEKF: Consistent Visual-Inertial Odometry using Points, Lines, and Vanishing Points.
CoRR
Tong Hua, Tao Li, Liang Pang, Guoqing Liu, Wencheng Xuanyuan, Chang Shu, Ling Pei
2022 J jnl
M2DGR: A Multi-Sensor and Multi-Scenario SLAM Dataset for Ground Robots.
IEEE Robotics Autom. Lett.
Jie Yin, Ang Li, Tao Li, Wenxian Yu, Danping Zou
2022 J jnl
P$^{3}$-VINS: Tightly-Coupled PPP/INS/Visual SLAM Based on Optimization Approach.
IEEE Robotics Autom. Lett.
Tao Li, Ling Pei, Yan Xiang, Wenxian Yu, Trieu-Kien Truong
2020 — conf
A Deep Learning Method for Complex Human Activity Recognition Using Virtual Wearable Sensors.
SpatialDI
Fanyi Xiao, Ling Pei, Lei Chu, Danping Zou, Wenxian Yu, Yifan Zhu, Tao Li
2020 J jnl
A Deep Learning Method for Complex Human Activity Recognition Using Virtual Wearable Sensors.
CoRR
Fanyi Xiao, Ling Pei, Lei Chu, Danping Zou, Wenxian Yu, Yifan Zhu, Tao Li
2020 — conf
A Geometric Consistency Model of Virtual Camera for Vision-Based SLAM Simulation.
SpatialDI
Yifan Zhu, Ling Pei, Danping Zou, Wenxian Yu, Tao Li, Qi Wu, Songpengcheng Xia
2020 J jnl
Attention-SLAM: A Visual Monocular SLAM Learning from Human Gaze.
CoRR
Jinquan Li, Ling Pei, Danping Zou, Songpengcheng Xia, Qi Wu, Tao Li, Zhen Sun, Wenxian Yu
2020 — conf
CPI: LiDAR-Camera Extrinsic Calibration Based on Feature Points with Reflection Intensity.
SpatialDI
Lihao Tao, Ling Pei, Tao Li, Danping Zou, Qi Wu, Songpengcheng Xia
2020 J jnl
IVPR: An Instant Visual Place Recognition Approach Based on Structural Lines in Manhattan World.
IEEE Trans. Instrum. Meas.
Ling Pei, Kun Liu, Danping Zou, Tao Li, Qi Wu, Yifan Zhu, You Li, Zhe He, Yuwei Chen, Daniele Sartori
2020 J jnl
P3-LOAM: PPP/LiDAR Loosely Coupled SLAM with Accurate Covariance Estimation and Robust RAIM in Urban Canyon Environment.
CoRR
Tao Li, Ling Pei, Yan Xiang, Qi Wu, Songpengcheng Xia, Lihao Tao, Wenxian Yu
2019 — conf
Image Aided Point-wise Autonomous Annotation for LiDAR Data.
CSAI
Yexuan Li, Ling Pei, Danping Zou, Yifan Zhu, Xiao Liang, Tao Li

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.