Yangxin Huang - RankMe

22 papers Journal 21Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Bayesian weighted composite quantile regression in varying-coefficient partially linear mixed-effects model with ordinal longitudinal data. Comput. Stat. Xiaofan Wang, Jiaqing Chen, Jinjing Wang, Yibo Long, Feng Gu, Yangxin Huang
2026	J	`jnl`	Co-Activation Pattern Analysis Based on Hidden Semi-Markov Model for Brain Spatiotemporal Dynamics. IEEE Trans. Medical Imaging Zihao Yuan, Jiaqing Chen, Han Qiu, Houxiang Wang, Yangxin Huang, Fuchun Lin
2026	J	`jnl`	Generalized linear mixed-effects joint model for longitudinal and bivariate survival data. Comput. Stat. Data Anal. Jiming Chen, Yangxin Huang, Niansheng Tang
2025	J	`jnl`	Adjustment of selection bias for clinical trials: a simulation study. Commun. Stat. Simul. Comput. Yuanyuan Lu, Henian Chen, Wei Wang, Yangxin Huang, Feng Cheng, Ellen Daley
2025	J	`jnl`	Understanding Viewers' Attitudes Toward Virtual Streamers: A Systematic Review. IEEE Access Yangxin Huang, Tianran Wang
2024	J	`jnl`	Adaptive sufficient sparse clustering by controlling false discovery. Stat. Comput. Zihao Yuan, Jiaqing Chen, Han Qiu, Houxiang Wang, Yangxin Huang
2024	J	`jnl`	NHSMM-MAR-sdNC: A novel data-driven computational framework for state-dependent effective connectivity analysis. Medical Image Anal. Houxiang Wang, Jiaqing Chen, Zihao Yuan, Yangxin Huang, Fuchun Lin
2023	J	`jnl`	Empirical Bayes Decision for a Generalized Exponential Distribution with Contaminated Data. Symmetry Han Qiu, Jiaqing Chen, Zihao Yuan, Yangxin Huang
2023	J	`jnl`	Quantile-Adaptive Sufficient Variable Screening by Controlling False Discovery. Entropy Zihao Yuan, Jiaqing Chen, Han Qiu, Yangxin Huang
2022	—	`conf`	Attentional Generative Multimodal Network for Neonatal Postoperative Pain Estimation. MICCAI (3) Md Sirajus Salekin, Ghada Zamzmi, Dmitry B. Goldgof, Peter R. Mouton, Kanwaljeet J. S. Anand, Terri Ashmeade, Stephanie Prescott, Yangxin Huang, Yu Sun
2022	J	`jnl`	Bayesian Joint Modeling of Multivariate Longitudinal and Survival Data With an Application to Diabetes Study. Frontiers Big Data Yangxin Huang, Jiaqing Chen, Lan Xu, Nian-Sheng Tang
2022	J	`jnl`	Double Penalized Expectile Regression for Linear Mixed Effects Model. Symmetry Sihan Gao, Jiaqing Chen, Zihao Yuan, Jie Liu, Yangxin Huang
2022	J	`jnl`	Editorial: Bayesian Inference and AI. Frontiers Big Data Niansheng Tang, Catherine Liu, Jian Qing Shi, Yangxin Huang
2022	J	`jnl`	The Estimation of Bent Line Expectile Regression Model Based on a Smoothing Technique. Symmetry Jie Liu, Jiaqing Chen, Yangxin Huang
2017	J	`jnl`	Bayesian inference on partially linear mixed-effects joint models for longitudinal data with multiple features. Comput. Stat. Yangxin Huang, Tao Lu
2016	J	`jnl`	Finite mixture of nonlinear mixed-effects joint models in the presence of missing and mismeasured covariate, with application to AIDS studies. Comput. Stat. Data Anal. Xiaosun Lu, Yangxin Huang, Yiliang Zhu
2016	J	`jnl`	Mixed-effects Models with Skewed Distributions for Time-varying Decay Rate in HIV Dynamics. Commun. Stat. Simul. Comput. Chunning Yan, Ren Chen, Yangxin Huang
2014	J	`jnl`	Jointly modeling time-to-event and longitudinal data: a Bayesian approach. Stat. Methods Appl. Yangxin Huang, X. Joan Hu, Getachew Dagne
2013	J	`jnl`	Comparison of Mixed-Effects Models for Skew-Normal Responses with an Application to AIDS Data: A Bayesian Approach. Commun. Stat. Simul. Comput. Yangxin Huang, Getachew Dagne
2010	J	`jnl`	vFitness: a web-based computing tool for improving estimation of BMC Bioinform. Jingming Ma, Carrie Dykes, Tao Wu, Yangxin Huang, Lisa M. Demeter, Hulin Wu
2008	J	`jnl`	Long-term HIV dynamic models incorporating drug adherence and resistance to treatment for prediction of virological responses. Comput. Stat. Data Anal. Yangxin Huang
2005	J	`jnl`	On a family of interval estimators of effective doses. Comput. Stat. Data Anal. Yangxin Huang

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.