Samuel W. K. Wong

15 papers A 2Journal 13

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Classifying Metamorphic versus Single-Fold Proteins with Statistical Learning and AlphaFold2. CoRR Yongkai Chen, Samuel W. K. Wong, S. C. Kou
2025	J	`jnl`	FECT: Factuality Evaluation of Interpretive AI-Generated Claims in Contact Center Conversation Transcripts. CoRR Hagyeong Shin, Binoy Robin Dalal, Iwona Bialynicka-Birula, Navjot Matharu, Ryan Muir, Xingwei Yang, Samuel W. K. Wong
2025	J	`jnl`	Particle Gibbs for likelihood-free inference of stochastic volatility models. Stat. Comput. Zhaoran Hou, Samuel W. K. Wong
2024	J	`jnl`	A Bayesian Collocation Integral Method for Parameter Estimation in Ordinary Differential Equations. J. Comput. Graph. Stat. Mingwei Xu, Samuel W. K. Wong, Peijun Sang
2024	J	`jnl`	magi: A Package for Inference of Dynamic Systems from Noisy and Sparse Data via Manifold-Constrained Gaussian Processes. J. Stat. Softw. Samuel W. K. Wong, Shihao Yang, S. C. Kou
2021	J	`jnl`	BAMBI: An R Package for Fitting Bivariate Angular Mixture Models. J. Stat. Softw. Saptarshi Chakraborty, Samuel W. K. Wong
2021	A	`conf`	Ellipse Detection and Localization with Applications to Knots in Sawn Lumber Images. WACV Shenyi Pan, Shuxian Fan, Samuel W. K. Wong, James V. Zidek, Helge Rhodin
2020	J	`jnl`	A comparison study on nonlinear dimension reduction methods with kernel variations: Visualization, optimization and classification. Intell. Data Anal. Katherine C. Kempfert, Yishi Wang, Cuixian Chen, Samuel W. K. Wong
2020	J	`jnl`	Ellipse Detection and Localization with Applications to Knots in Sawn Lumber Images. CoRR Shenyi Pan, Shuxian Fan, Samuel W. K. Wong, James V. Zidek, Helge Rhodin
2019	J	`jnl`	A Comparison Study on Nonlinear Dimension Reduction Methods with Kernel Variations: Visualization, Optimization and Classification. CoRR Katherine C. Kempfert, Yishi Wang, Cuixian Chen, Samuel W. K. Wong
2019	J	`jnl`	Bayesian Analysis of Accumulated Damage Models in Lumber Reliability. Technometrics Chun-Hao Yang, James V. Zidek, Samuel W. K. Wong
2019	J	`jnl`	The Duration of Load Effect in Lumber as Stochastic Degradation. IEEE Trans. Reliab. Samuel W. K. Wong, James V. Zidek
2017	A	`conf`	Sequential Graph Matching with Sequential Monte Carlo. AISTATS Seong-Hwan Jun, Samuel W. K. Wong, James V. Zidek, Alexandre Bouchard-Côté
2016	J	`jnl`	Quantifying Uncertainty in Lumber Grading and Strength Prediction: A Bayesian Approach. Technometrics Samuel W. K. Wong, Conroy Lum, Lang Wu, James V. Zidek
2015	J	`jnl`	Conformational sampling and structure prediction of multiple interacting loops in soluble and Bioinform. Ke Tang, Samuel W. K. Wong, Jun S. Liu, Jinfeng Zhang, Jie Liang

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.