Eisa Mahmoudi - RankMe

18 papers Journal 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A new class of median estimators using auxiliary information under PPS sampling: theoretical properties and empirical evaluation. Comput. Stat. Salman Shah, Eisa Mahmoudi, Moiz Qureshi, Hasnain Iftikhar, Paulo Canas Rodrigues, Ronny Ivan Gonzales Medina, Javier Linkolk López-Gonzales
2026	J	`jnl`	An Efficient Horvitz-Thompson-Type Estimator for Two Sensitive Means Using a Three-Stage Quantitative Randomized Response Under Complex Sampling. Axioms Hamed Salemian, Eisa Mahmoudi, Osama Abdulaziz Alamri
2025	J	`jnl`	A Novel Family of CDF Estimators Under PPS Sampling: Computational, Theoretical, and Applied Perspectives. Axioms Salman Shah, Eisa Mahmoudi, Hasnain Iftikhar, Paulo Canas Rodrigues, Ronny Ivan Gonzales Medina, Javier Linkolk López-Gonzales
2022	J	`jnl`	A new family of heavy tailed distributions with an application to the heavy tailed insurance loss data. Commun. Stat. Simul. Comput. Zubair Ahmad, Eisa Mahmoudi, Sanku Dey
2022	J	`jnl`	Copula-Based Reliability for Weighted-$k$-Out-of-$n$ Systems Having Randomly Chosen Components of $m$ Different Types. IEEE Trans. Reliab. Eisa Mahmoudi, Rahmat Sadat Meshkat, Hamzeh Torabi
2022	J	`jnl`	Modelling insurance losses using a new beta power transformed family of distributions. Commun. Stat. Simul. Comput. Zubair Ahmad, Eisa Mahmoudi, Morad Alizadeh
2021	J	`jnl`	A New Class of Heavy-Tailed Distributions: Modeling and Simulating Actuarial Measures. Complex. Jin Zhao, Zubair Ahmad, Eisa Mahmoudi, Eslam H. Hafez, Marwa Mostafa Mohie El-Din
2021	J	`jnl`	The Arcsine-X Family of Distributions with Applications to Financial Sciences. Comput. Syst. Sci. Eng. Yen Liang Tung, Zubair Ahmad, Eisa Mahmoudi
2020	J	`jnl`	A Flexible Reduced Logarithmic-X Family of Distributions with Biomedical Analysis. Comput. Math. Methods Medicine Yinglin Liu, Muhammad Ilyas, Saima K. Khosa, Eisa Mahmoudi, Zubair Ahmad, Dost Muhammad Khan, G. G. Hamedani
2020	J	`jnl`	On Modeling the Earthquake Insurance Data via a New Member of the T-X Family. Comput. Intell. Neurosci. Zubair Ahmad, Eisa Mahmoudi, Omid Kharazmi
2020	J	`jnl`	Sequential fixed-accuracy confidence intervals for the stress-strength reliability parameter for the exponential distribution: two-stage sampling procedure. Comput. Stat. Ashkan Khalifeh, Eisa Mahmoudi, Ajit Chaturvedi
2018	J	`jnl`	Estimation of parameters for the Marshall-Olkin generalized exponential distribution based on complete data. Math. Comput. Simul. Hamzeh Torabi, F. L. Bagheri, Eisa Mahmoudi
2017	J	`jnl`	A New Bivariate Distribution Obtained by Compounding the Bivariate Normal and Geometric Distributions. J. Stat. Theory Appl. Eisa Mahmoudi, Hamid Mahmoodian
2017	J	`jnl`	The compound class of linear failure rate-power series distributions: Model, properties, and applications. Commun. Stat. Simul. Comput. Eisa Mahmoudi, Ali Akbar Jafari
2013	J	`jnl`	Exponentiated Weibull-Poisson distribution: Model, properties and applications. Math. Comput. Simul. Eisa Mahmoudi, Afsaneh Sepahdar
2012	J	`jnl`	Generalized exponential-power series distributions. Comput. Stat. Data Anal. Eisa Mahmoudi, Ali Akbar Jafari
2011	J	`jnl`	An admissible minimax estimator of a lower-bounded scale parameter under squared-log error loss function. Kybernetika Eisa Mahmoudi, Hojatollah Zakerzadeh
2011	J	`jnl`	The beta generalized Pareto distribution with application to lifetime data. Math. Comput. Simul. Eisa Mahmoudi

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.