Rajarshi Guhaniyogi

16 papers Journal 15Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Mapping Drivers of Greenness: Spatial Variable Selection for MODIS Vegetation Indices. CoRR Qishi Zhan, Cheng-Han Yu, Yuchi Chen, Zhikang Dong, Rajarshi Guhaniyogi
2025	J	`jnl`	Bayesian Data Sketching for Varying Coefficient Regression Models. CoRR Rajarshi Guhaniyogi, Laura Baracaldo, Sudipto Banerjee
2025	J	`jnl`	Bayesian Data Sketching for Varying Coefficient Regression Models. J. Mach. Learn. Res. Rajarshi Guhaniyogi, Laura Baracaldo, Sudipto Banerjee
2025	J	`jnl`	Sketching in High-Dimensional Regression With Big Data Using Gaussian Scale Mixture Priors. J. Mach. Learn. Res. Rajarshi Guhaniyogi, Aaron Wolfe Scheffler
2024	J	`jnl`	Covariate-Dependent Clustering of Undirected Networks with Brain-Imaging Data. Technometrics Sharmistha Guha, Rajarshi Guhaniyogi
2024	J	`jnl`	InVA: Integrative Variational Autoencoder for Harmonization of Multi-modal Neuroimaging Data. CoRR Bowen Lei, Rajarshi Guhaniyogi, Krishnendu Chandra, Aaron W. Scheffler, Bani K. Mallick
2022	J	`jnl`	Bayesian Dynamic Feature Partitioning in High-Dimensional Regression With Big Data. Technometrics Rene Gutierrez, Rajarshi Guhaniyogi
2022	J	`jnl`	Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior. J. Mach. Learn. Res. Rajarshi Guhaniyogi, Cheng Li, Terrance D. Savitsky, Sanvesh Srivastava
2021	J	`jnl`	Bayesian Generalized Sparse Symmetric Tensor-on-Vector Regression. Technometrics Sharmistha Guha, Rajarshi Guhaniyogi
2020	—	`conf`	High Dimensional Bayesian Regularization in Regressions Involving Symmetric Tensors. IPMU (3) Rajarshi Guhaniyogi
2018	J	`jnl`	Meta-Kriging: Scalable Bayesian Modeling and Inference for Massive Spatial Datasets. Technometrics Rajarshi Guhaniyogi, Sudipto Banerjee
2017	J	`jnl`	Bayesian Tensor Regression. J. Mach. Learn. Res. Rajarshi Guhaniyogi, Shaan Qamar, David B. Dunson
2017	J	`jnl`	Convergence rate of Bayesian supervised tensor modeling with multiway shrinkage priors. J. Multivar. Anal. Rajarshi Guhaniyogi
2016	J	`jnl`	Compressed Gaussian Process for Manifold Regression. J. Mach. Learn. Res. Rajarshi Guhaniyogi, David B. Dunson
2014	J	`jnl`	Bayesian Conditional Density Filtering for Big Data. CoRR Rajarshi Guhaniyogi, Shaan Qamar, David B. Dunson
2013	J	`jnl`	Bayesian Compressed Regression CoRR Rajarshi Guhaniyogi, David B. Dunson

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.