Fajie Wang - RankMe

31 papers Journal 31

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A novel local semi-analytical meshless method for acoustic eigenfrequency and modal analysis. Appl. Math. Lett. Tongtong Sun, Fajie Wang, Xingxing Yue
2026	J	`jnl`	Fundamental solution neural networks for solving inverse Cauchy problems for the Laplace and biharmonic equations. Comput. Math. Appl. Xin Li, Fajie Wang, Renhao Wang, Shengdong Zhao, Daigeng Yang
2025	J	`jnl`	A spatio-temporal radial basis function collocation method based on Hausdorff fractal distance for Hausdorff derivative heat conduction equations in three-dimensional anisotropic materials. Appl. Math. Comput. Jiayu Wang, Lin Qiu, Yingjie Liang, Fajie Wang
2025	J	`jnl`	Adaptive multi-domain physics-informed neural networks for coupled thermo-mechanical analysis of thermal barrier coatings. Eng. Comput. Gefei Li, Lin Qiu, Fajie Wang, Wenzhen Qu, Ji Lin, Yan Gu, Qing-Hua Qin
2025	J	`jnl`	Enriched physics-informed neural networks for dynamic Poisson-Nernst-Planck systems. Math. Comput. Simul. Xujia Huang, Fajie Wang, Benrong Zhang, Hanqing Liu
2025	J	`jnl`	Physics-informed radial basis function network based on Hausdorff fractal distance for solving Hausdorff derivative elliptic problems. Comput. Math. Appl. Lin Qiu, Fajie Wang, Yingjie Liang, Qing-Hua Qin
2025	J	`jnl`	Spectral integrated neural networks with large time steps for 2D and 3D transient elastodynamic analysis. Neural Networks Haodong Ma, Wenzhen Qu, Yan Gu, Lin Qiu, Fajie Wang, Shengdong Zhao
2024	J	`jnl`	A novel semi-analytical meshless method for the thickness optimization of porous material distributed on sound barriers. Appl. Math. Lett. Hanqing Liu, Fajie Wang
2024	J	`jnl`	Enriched Physics-informed Neural Networks for Dynamic Poisson-Nernst-Planck Systems. CoRR Xujia Huang, Fajie Wang, Benrong Zhang, Hanqing Liu
2024	J	`jnl`	Spectral integrated neural networks (SINNs) for solving forward and inverse dynamic problems. CoRR Lin Qiu, Fajie Wang, Wenzhen Qu, Yan Gu, Qing-Hua Qin
2024	J	`jnl`	Spectral integrated neural networks (SINNs) for solving forward and inverse dynamic problems. Neural Networks Lin Qiu, Fajie Wang, Wenzhen Qu, Yan Gu, Qing-Hua Qin
2023	J	`jnl`	Adaptive physics-informed neural networks for dynamic thermo-mechanical coupling problems in large-size-ratio functionally graded materials. CoRR Lin Qiu, Yanjie Wang, Tian He, Yan Gu, Fajie Wang
2023	J	`jnl`	Boundary integrated neural networks (BINNs) for acoustic radiation and scattering. CoRR Wenzhen Qu, Yan Gu, Shengdong Zhao, Fajie Wang
2022	J	`jnl`	A semi-analytical and boundary-type meshless method with adjoint variable formulation for acoustic design sensitivity analysis. Appl. Math. Lett. Suifu Cheng, Fajie Wang, Guozheng Wu, Chengxin Zhang
2022	J	`jnl`	Localized singular boundary method for the simulation of large-scale problems of elliptic operators in complex geometries. Comput. Math. Appl. Ji Lin, Lin Qiu, Fajie Wang
2022	J	`jnl`	Singular boundary method for 2D and 3D acoustic design sensitivity analysis. Comput. Math. Appl. Suifu Cheng, Fajie Wang, Po-Wei Li, Wenzhen Qu
2021	J	`jnl`	Local non-singular knot method for large-scale computation of acoustic problems in complicated geometries. Comput. Math. Appl. Xingxing Yue, Fajie Wang, Po-Wei Li, Chia-Ming Fan
2021	J	`jnl`	Localized Chebyshev collocation method for solving elliptic partial differential equations in arbitrary 2D domains. Appl. Math. Comput. Fajie Wang, Qinghai Zhao, Zengtao Chen, Chia-Ming Fan
2020	J	`jnl`	Local knot method for 2D and 3D convection-diffusion-reaction equations in arbitrary domains. Appl. Math. Lett. Fajie Wang, Chao Wang, Zengtao Chen
2020	J	`jnl`	Localized MFS for the inverse Cauchy problems of two-dimensional Laplace and biharmonic equations. Appl. Math. Comput. Fajie Wang, Chia-Ming Fan, Qingsong Hua, Yan Gu
2019	J	`jnl`	A Trefftz/MFS mixed-type method to solve the Cauchy problem of the Laplace equation. Appl. Math. Lett. Chein-Shan Liu, Fajie Wang, Yan Gu
2019	J	`jnl`	A meshless singular boundary method for transient heat conduction problems in layered materials. Comput. Math. Appl. Lin Qiu, Fajie Wang, Ji Lin
2019	J	`jnl`	A novel space-time meshless method for nonhomogeneous convection-diffusion equations with variable coefficients. Appl. Math. Lett. Xingxing Yue, Fajie Wang, Qingsong Hua, Xiangyun Qiu
2019	J	`jnl`	Nonlinear wave inverse source problem solved by a method of m-order homogenization functions. Appl. Math. Lett. Chein-Shan Liu, Lin Qiu, Fajie Wang
2018	J	`jnl`	A meshless method for solving the nonlinear inverse Cauchy problem of elliptic type equation in a doubly-connected domain. Comput. Math. Appl. Chein-Shan Liu, Fajie Wang
2018	J	`jnl`	A simple empirical formula of origin intensity factor in singular boundary method for two-dimensional Hausdorff derivative Laplace equations with Dirichlet boundary. Comput. Math. Appl. Fajie Wang, Wen Chen, Qingsong Hua
2018	J	`jnl`	An energy method of fundamental solutions for solving the inverse Cauchy problems of the Laplace equation. Comput. Math. Appl. Chein-Shan Liu, Fajie Wang
2018	J	`jnl`	Boundary function method for inverse geometry problem in two-dimensional anisotropic heat conduction equation. Appl. Math. Lett. Fajie Wang, Qingsong Hua, Chein-Shan Liu
2018	J	`jnl`	Optimal sources in the MFS by minimizing a new merit function: Energy gap functional. Appl. Math. Lett. Fajie Wang, Chein-Shan Liu, Wenzhen Qu
2018	J	`jnl`	Trefftz energy method for solving the Cauchy problem of the Laplace equation. Appl. Math. Lett. Chein-Shan Liu, Fajie Wang, Yan Gu
2017	J	`jnl`	Three-dimensional thermal stress analysis using the indirect BEM in conjunction with the radial integration method. Adv. Eng. Softw. Wenzhen Qu, Yaoming Zhang, Yan Gu, Fajie Wang

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.