Ta-Wei Yang - RankMe

13 papers Journal 9Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Intelligent Reflecting Surface-Assisted Millimeter Wave Communications: Cross Attention-Aided Variational Autoencoder-Based Precoding Design. IEEE Trans. Cogn. Commun. Netw. Meng-Hsun Wu, Hong-Yunn Chen, Ta-Wei Yang, Chih-Chuan Hsu, Chih-Wei Huang, Cheng-Fu Chou
2024	J	`jnl`	A Hybrid Approach for Binary Classification of Imbalanced Data. Int. J. Comput. Intell. Appl. Hsinhan Tsai, Ta-Wei Yang, Wai-Man Wong, Han-Yi Kao, Cheng-Fu Chou
2024	J	`jnl`	A Novel Method for Audiogram Digitization in Audiological Reports. IEEE Access Ta-Wei Yang, Chen-Yu Yang, Yen-Hui Lee, Pey-Yu Chen, Pei-Hsuan Lin, Wei-Cheng Wu, Chen-Chi Wu, Cheng-Fu Chou
2024	J	`jnl`	Machine learning-based longitudinal prediction for GJB2-related sensorineural hearing loss. Comput. Biol. Medicine Pey-Yu Chen, Ta-Wei Yang, Yi-Shan Tseng, Cheng-Yu Tsai, Chiung-Szu Yeh, Yen-Hui Lee, Pei-Hsuan Lin, Ting-Chun Lin, Yu-Jen Wu, Ting-Hua Yang, Yu-Ting Chiang, Jacob Shujui Hsu, Chuan-Jen Hsu, Pei-Lung Chen, Cheng-Fu Chou, Chen-Chi Wu
2024	J	`jnl`	Multimodal Attention Network for Dementia Prediction. IEEE J. Biomed. Health Informatics Hsinhan Tsai, Ta-Wei Yang, Kai-Hao Ou, Tung-Hung Su, Che Lin, Cheng-Fu Chou
2023	J	`jnl`	Attention-Aided Autoencoder-Based Channel Prediction for Intelligent Reflecting Surface-Assisted Millimeter-Wave Communications. IEEE Trans. Green Commun. Netw. Hong-Yunn Chen, Meng-Hsun Wu, Ta-Wei Yang, Chih-Wei Huang, Cheng-Fu Chou
2023	J	`jnl`	Intelligent Reflecting Surface Enhanced Wireless Communications With MultiHead-Attention Sparse Autoencoder-Based Channel Prediction. IEEE Commun. Lett. Hong-Yunn Chen, Meng-Hsun Wu, Ta-Wei Yang, Jia-Wei Liao, Chih-Wei Huang, Cheng-Fu Chou
2022	J	`jnl`	A Hybrid Approach for Binary Classification of Imbalanced Data. CoRR Hsin-Han Tsai, Ta-Wei Yang, Wai-Man Wong, Cheng-Fu Chou
2022	—	`conf`	On LSTM Autoencoder-Based Hybrid Precoding for Reconfigurable Intelligent Surface-Aided Multiuser Millimeter-Wave Massive MIMO 6G Systems. VTC Spring Yi-Hsien Lu, Kai-Hao Ou, Hong-Yunn Chen, Meng-Hsun Wu, Ta-Wei Yang, Hsin-Han Tsai, Cheng-Fu Chou
2021	—	`conf`	A Systematic Resource Management for VR Streaming on MECs. WOCC Yu-Syuan Jheng, Min-Li Wu, Ta-Wei Yang, Cheng-Fu Chou, Ing-Chau Chang
2021	—	`conf`	Wi-Fi DSAR: Wi-Fi based Indoor Localization using Denoising Supervised Autoencoder. WOCC Yun-Hao Wang, Ta-Wei Yang, Cheng-Fu Chou, Ing-Chau Chang
2020	J	`jnl`	Achieving M2M-device authentication through heterogeneous information bound with USIM card. Future Gener. Comput. Syst. Ta-Wei Yang, Yu-Han Ho, Cheng-Fu Chou
2020	—	`conf`	Using Coalitional Game for Bandwidth-aware Fast Failover in Distributed SDN Environment. CCNC Jia-Wei Li, Chun-Chien Teng, Ta-Wei Yang, Cheng-Fu Chou

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.