Yang Yang - RankMe

19 papers A* 1B 1Misc 1Journal 14Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	Misc	`conf`	Microtitre Plate Image Augmentation with Generative Adversarial Networks. ICASSP Ru Li, Tingting Chai, Samaneh Kouchaki, David A. Clifton, Yang Yang
2024	—	`conf`	A Comparison of Representation Learning Methods for Medical Concepts in EHR Databases. BCB Zhangdaihong Liu, Xuan Wu, Yang Yang, David A. Clifton
2024	J	`jnl`	DuKA: A Dual-Keyless-Attention Model for Multi-Modality EHR Data Fusion and Organ Failure Prediction. IEEE Trans. Biomed. Eng. Zhangdaihong Liu, Xuan Wu, Yang Yang, David A. Clifton
2023	J	`jnl`	A medical multimodal large language model for future pandemics. npj Digit. Medicine Fenglin Liu, Tingting Zhu, Xian Wu, Bang Yang, Chenyu You, Chenyang Wang, Lei Lu, Zhangdaihong Liu, Yefeng Zheng, Xu Sun, Yang Yang, Lei A. Clifton, David A. Clifton
2023	J	`jnl`	An adversarial training framework for mitigating algorithmic biases in clinical machine learning. npj Digit. Medicine Jenny Yang, Andrew A. S. Soltan, David W. Eyre, Yang Yang, David A. Clifton
2023	J	`jnl`	Patient Clustering for Vital Organ Failure Using ICD Code With Graph Attention. IEEE Trans. Biomed. Eng. Zhangdaihong Liu, Ying Hu, Xuan Wu, Gert Mertes, Yang Yang, David A. Clifton
2023	J	`jnl`	Privacy-Aware Early Detection of COVID-19 Through Adversarial Training. IEEE J. Biomed. Health Informatics Omid Rohanian, Samaneh Kouchaki, Andrew A. S. Soltan, Jenny Yang, Morteza Rohanian, Yang Yang, David A. Clifton
2022	J	`jnl`	A Deep Learning Approach for the Assessment of Signal Quality of Non-Invasive Foetal Electrocardiography. Sensors Gert Mertes, Yuan Long, Zhangdaihong Liu, Yuhui Li, Yang Yang, David A. Clifton
2022	J	`jnl`	Privacy-aware Early Detection of COVID-19 through Adversarial Training. CoRR Omid Rohanian, Samaneh Kouchaki, Andrew A. S. Soltan, Jenny Yang, Morteza Rohanian, Yang Yang, David A. Clifton
2022	A*	`conf`	Retrieve, Reason, and Refine: Generating Accurate and Faithful Patient Instructions. NeurIPS Fenglin Liu, Bang Yang, Chenyu You, Xian Wu, Shen Ge, Zhangdaihong Liu, Xu Sun, Yang Yang, David A. Clifton
2022	J	`jnl`	Retrieve, Reason, and Refine: Generating Accurate and Faithful Patient Instructions. CoRR Fenglin Liu, Bang Yang, Chenyu You, Xian Wu, Shen Ge, Zhangdaihong Liu, Xu Sun, Yang Yang, David A. Clifton
2021	J	`jnl`	An end-to-end heterogeneous graph attention network for Mycobacterium tuberculosis drug-resistance prediction. Briefings Bioinform. Yang Yang, Timothy M. Walker, Samaneh Kouchaki, Chenyang Wang, Timothy E. A Peto, Derrick W. Crook, David A. Clifton
2019	J	`jnl`	Application of machine learning techniques to tuberculosis drug resistance analysis. Bioinform. Samaneh Kouchaki, Yang Yang, Timothy M. Walker, A. Sarah Walker, Daniel J. Wilson, Timothy E. A Peto, Derrick W. Crook, CRyPTIC Consortium, David A. Clifton
2019	J	`jnl`	DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis. Bioinform. Yang Yang, Timothy M. Walker, A. Sarah Walker, Daniel J. Wilson, Timothy E. A Peto, Derrick W. Crook, Farah Shamout, CRyPTIC Consortium, Tingting Zhu, David A. Clifton
2019	J	`jnl`	Patient-Specific Physiological Monitoring and Prediction Using Structured Gaussian Processes. IEEE Access Tingting Zhu, Glen Wright Colopy, Glenn H. MacEwen, Katherine E. Niehaus, Yang Yang, Chris W. Pugh, David A. Clifton
2018	B	`conf`	Does Higher Order LSTM Have Better Accuracy for Segmenting and Labeling Sequence Data? COLING Yi Zhang, Xu Sun, Shuming Ma, Yang Yang, Xuancheng Ren
2018	J	`jnl`	Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data. Bioinform. Yang Yang, Katherine E. Niehaus, Timothy M. Walker, Zamin Iqbal, A. Sarah Walker, Daniel J. Wilson, Tim E. A. Peto, Derrick W. Crook, E. Grace Smith, Tingting Zhu, David A. Clifton
2017	J	`jnl`	Does Higher Order LSTM Have Better Accuracy in Chunking and Named Entity Recognition? CoRR Yi Zhang, Xu Sun, Yang Yang
2016	—	`conf`	Risk prediction for cardiovascular disease using ECG data in the China kadoorie biobank. EMBC Yanting Shen, Yang Yang, Sarah Parish, Zhengming Chen, Robert Clarke, David A. Clifton

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.