Yanchuan Chang

23 papers A* 3B 3Journal 14Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	DualCast: A Model to Disentangle Aperiodic Events from Traffic Series. IJCAI Xinyu Su, Feng Liu, Yanchuan Chang, Egemen Tanin, Majid Sarvi, Jianzhong Qi
2025	—	`conf`	FlexiReg: Flexible Urban Region Representation Learning. KDD (2) Fengze Sun, Yanchuan Chang, Egemen Tanin, Shanika Karunasekera, Jianzhong Qi
2025	J	`jnl`	From Reasoning to Generalization: Knowledge-Augmented LLMs for ARC Benchmark. CoRR Chao Lei, Nir Lipovetzky, Krista A. Ehinger, Yanchuan Chang
2025	J	`jnl`	K Nearest Neighbor-Guided Trajectory Similarity Learning. CoRR Yanchuan Chang, Xu Cai, Christian S. Jensen, Jianzhong Qi
2025	—	`conf`	Planning-Driven Programming: A Large Language Model Programming Workflow. ACL (1) Chao Lei, Yanchuan Chang, Nir Lipovetzky, Krista A. Ehinger
2025	J	`jnl`	Urban Region Representation Learning: A Flexible Approach. CoRR Fengze Sun, Yanchuan Chang, Egemen Tanin, Shanika Karunasekera, Jianzhong Qi
2024	J	`jnl`	Deep Learning for Trajectory Data Management and Mining: A Survey and Beyond. CoRR Wei Chen, Yuxuan Liang, Yuanshao Zhu, Yanchuan Chang, Kang Luo, Haomin Wen, Lei Li, Yanwei Yu, Qingsong Wen, Chao Chen, Kai Zheng, Yunjun Gao, Xiaofang Zhou, Yu Zheng
2024	J	`jnl`	DualCast: Disentangling Aperiodic Events from Traffic Series with a Dual-Branch Model. CoRR Xinyu Su, Feng Liu, Yanchuan Chang, Egemen Tanin, Majid Sarvi, Jianzhong Qi
2024	J	`jnl`	Planning-Driven Programming: A Large Language Model Programming Workflow. CoRR Chao Lei, Yanchuan Chang, Nir Lipovetzky, Krista A. Ehinger
2024	B	`conf`	Spatial-temporal Forecasting for Regions without Observations. EDBT Xinyu Su, Jianzhong Qi, Egemen Tanin, Yanchuan Chang, Majid Sarvi
2024	J	`jnl`	Spatial-temporal Forecasting for Regions without Observations. CoRR Xinyu Su, Jianzhong Qi, Egemen Tanin, Yanchuan Chang, Majid Sarvi
2024	J	`jnl`	Trajectory Similarity Measurement: An Efficiency Perspective. Proc. VLDB Endow. Yanchuan Chang, Egemen Tanin, Gao Cong, Christian S. Jensen, Jianzhong Qi
2024	A*	`conf`	Urban Region Representation Learning with Attentive Fusion. ICDE Fengze Sun, Jianzhong Qi, Yanchuan Chang, Xiaoliang Fan, Shanika Karunasekera, Egemen Tanin
2023	A*	`conf`	Contrastive Trajectory Similarity Learning with Dual-Feature Attention. ICDE Yanchuan Chang, Jianzhong Qi, Yuxuan Liang, Egemen Tanin
2023	—	`—`	Effective, Efficient, and Generalizable Algorithms for Trajectory Similarity Queries. Yanchuan Chang
2023	B	`conf`	Spatial Structure-Aware Road Network Embedding via Graph Contrastive Learning. EDBT Yanchuan Chang, Egemen Tanin, Xin Cao, Jianzhong Qi
2023	J	`jnl`	Trajectory Similarity Measurement: An Efficiency Perspective. CoRR Yanchuan Chang, Egemen Tanin, Gao Cong, Christian S. Jensen, Jianzhong Qi
2023	J	`jnl`	Urban Region Representation Learning with Attentive Fusion. CoRR Fengze Sun, Jianzhong Qi, Yanchuan Chang, Xiaoliang Fan, Shanika Karunasekera, Egemen Tanin
2022	J	`jnl`	Contrastive Trajectory Similarity Learning with Dual-Feature Attention. CoRR Yanchuan Chang, Jianzhong Qi, Yuxuan Liang, Egemen Tanin
2021	B	`conf`	Sub-trajectory Similarity Join with Obfuscation. SSDBM Yanchuan Chang, Jianzhong Qi, Egemen Tanin, Xingjun Ma, Hanan Samet
2021	J	`jnl`	Sub-trajectory Similarity Join with Obfuscation. CoRR Yanchuan Chang, Jianzhong Qi, Egemen Tanin, Xingjun Ma, Hanan Samet
2020	J	`jnl`	Packing R-trees with Space-filling Curves: Theoretical Optimality, Empirical Efficiency, and Bulk-loading Parallelizability. ACM Trans. Database Syst. Jianzhong Qi, Yufei Tao, Yanchuan Chang, Rui Zhang
2018	J	`jnl`	Theoretically Optimal and Empirically Efficient R-trees with Strong Parallelizability. Proc. VLDB Endow. Jianzhong Qi, Yufei Tao, Yanchuan Chang, Rui Zhang

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.