Yang Liu - RankMe

29 papers A* 2A 1Journal 18Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Plane Geometry Problem Solving with Multi-modal Reasoning: A Survey. EACL (Findings) Seunghyuk Cho, Zhenyue Qin, Yang Liu, Youngbin Choi, Seungbeom Lee, Dongwoo Kim
2026	J	`jnl`	VOLMO: Versatile and Open Large Models for Ophthalmology. CoRR Zhenyue Qin, Younjoon Chung, Elijah Lee, Wanyue Feng, Xuguang Ai, Serina S. Applebaum, Minjie Zou, Yang Liu, Pan Xiao, Mac Singer, Amisha D. Dave, Aidan Gilson, Tiarnan D. L. Keenan, Emily Y. Chew, Zhiyong Lu, Yih-Chung Tham, Ron Adelman, Luciano V. Del Priore, Qingyu Chen
2025	—	`conf`	GeoDANO: Geometric VLM with Domain Agnostic Vision Encoder. EMNLP (Findings) Seunghyuk Cho, Zhenyue Qin, Yang Liu, Youngbin Choi, Seungbeom Lee, Dongwoo Kim
2025	A	`conf`	HandCraft: Anatomically Correct Restoration of Malformed Hands in Diffusion Generated Images. WACV Zhenyue Qin, Yiqun Zhang, Yang Liu, Dylan Campbell
2025	J	`jnl`	LMOD+: A Comprehensive Multimodal Dataset and Benchmark for Developing and Evaluating Multimodal Large Language Models in Ophthalmology. CoRR Zhenyue Qin, Yang Liu, Yu Yin, Jinyu Ding, Haoran Zhang, Anran Li, Dylan Campbell, Xuansheng Wu, Ke Zou, Tiarnan D. L. Keenan, Emily Y. Chew, Zhiyong Lu, Yih-Chung Tham, Ninghao Liu, Xiuzhen Zhang, Qingyu Chen
2025	J	`jnl`	Plane Geometry Problem Solving with Multi-modal Reasoning: A Survey. CoRR Seunghyuk Cho, Zhenyue Qin, Yang Liu, Youngbin Choi, Seungbeom Lee, Dongwoo Kim
2025	J	`jnl`	Position-Sensing Graph Neural Networks: Proactively Learning Nodes Relative Positions. IEEE Trans. Neural Networks Learn. Syst. Yiqun Zhang, Zhenyue Qin, Saeed Anwar, Dongwoo Kim, Yang Liu, Pan Ji, Tom Gedeon
2024	J	`jnl`	Fusing Higher-Order Features in Graph Neural Networks for Skeleton-Based Action Recognition. IEEE Trans. Neural Networks Learn. Syst. Zhenyue Qin, Yang Liu, Pan Ji, Dongwoo Kim, Lei Wang, Robert I. McKay, Saeed Anwar, Tom Gedeon
2024	J	`jnl`	HandCraft: Anatomically Correct Restoration of Malformed Hands in Diffusion Generated Images. CoRR Zhenyue Qin, Yiqun Zhang, Yang Liu, Dylan Campbell
2023	A*	`conf`	Anonymization for Skeleton Action Recognition. AAAI Saemi Moon, Myeonghyeon Kim, Zhenyue Qin, Yang Liu, Dongwoo Kim
2023	J	`jnl`	Detecting and Restoring Non-Standard Hands in Stable Diffusion Generated Images. CoRR Yiqun Zhang, Zhenyue Qin, Yang Liu, Dylan Campbell
2022	J	`jnl`	ANUBIS: Skeleton Action Recognition Dataset, Review, and Benchmark. CoRR Zhenyue Qin, Yang Liu, Madhawa Perera, Tom Gedeon, Pan Ji, Dongwoo Kim, Saeed Anwar
2022	—	`conf`	DRT: A Lightweight Single Image Deraining Recursive Transformer. CVPR Workshops Yuanchu Liang, Saeed Anwar, Yang Liu
2022	J	`jnl`	DRT: A Lightweight Single Image Deraining Recursive Transformer. CoRR Yuanchu Liang, Saeed Anwar, Yang Liu
2022	J	`jnl`	Disentangling Noise from Images: A Flow-Based Image Denoising Neural Network. Sensors Yang Liu, Saeed Anwar, Zhenyue Qin, Pan Ji, Sabrina B. Caldwell, Tom Gedeon
2022	—	`conf`	Strengthening Skeletal Action Recognizers via Leveraging Temporal Patterns. ECCV Workshops (5) Zhenyue Qin, Pan Ji, Dongwoo Kim, Yang Liu, Saeed Anwar, Tom Gedeon
2022	J	`jnl`	Strengthening Skeletal Action Recognizers via Leveraging Temporal Patterns. CoRR Zhenyue Qin, Dongwoo Kim, Yang Liu, Saeed Anwar, Tom Gedeon
2021	J	`jnl`	Anonymization for Skeleton Action Recognition. CoRR Myeonghyeon Kim, Zhenyue Qin, Yang Liu, Dongwoo Kim
2021	—	`conf`	Classification Models for Medical Data with Interpretative Rules. ICONIP (1) Xinyue Xu, Xiang Ding, Zhenyue Qin, Yang Liu
2021	J	`jnl`	Disentangling Noise from Images: A Flow-Based Image Denoising Neural Network. CoRR Yang Liu, Saeed Anwar, Zhenyue Qin, Pan Ji, Sabrina B. Caldwell, Tom Gedeon
2021	A*	`conf`	Invertible Denoising Network: A Light Solution for Real Noise Removal. CVPR Yang Liu, Zhenyue Qin, Saeed Anwar, Pan Ji, Dongwoo Kim, Sabrina B. Caldwell, Tom Gedeon
2021	J	`jnl`	Invertible Denoising Network: A Light Solution for Real Noise Removal. CoRR Yang Liu, Zhenyue Qin, Saeed Anwar, Pan Ji, Dongwoo Kim, Sabrina B. Caldwell, Tom Gedeon
2021	J	`jnl`	Leveraging Third-Order Features in Skeleton-Based Action Recognition. CoRR Zhenyue Qin, Yang Liu, Pan Ji, Dongwoo Kim, Lei Wang, Bob McKay, Saeed Anwar, Tom Gedeon
2021	J	`jnl`	Position-Sensing Graph Neural Networks: Proactively Learning Nodes Relative Positions. CoRR Zhenyue Qin, Saeed Anwar, Dongwoo Kim, Yang Liu, Pan Ji, Tom Gedeon
2021	—	`conf`	Skeletons on the Stairs: Are They Deceptive? ICONIP (6) Yiran Li, Yang Liu, Zhenyue Qin, Xuanying Zhu, Sabrina B. Caldwell, Tom Gedeon
2020	J	`jnl`	Are Deep Neural Architectures Losing Information? Invertibility Is Indispensable. CoRR Yang Liu, Zhenyue Qin, Saeed Anwar, Sabrina B. Caldwell, Tom Gedeon
2020	—	`conf`	Are Deep Neural Architectures Losing Information? Invertibility is Indispensable. ICONIP (3) Yang Liu, Zhenyue Qin, Saeed Anwar, Sabrina B. Caldwell, Tom Gedeon
2020	J	`jnl`	Emotion Recognition Through Observer's Physiological Signals. CoRR Yang Liu, Tom Gedeon, Sabrina B. Caldwell, Shouxu Lin, Zi Jin
2020	—	`conf`	GradNet Image Denoising. CVPR Workshops Yang Liu, Saeed Anwar, Liang Zheng, Qi Tian

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.