Omid Bazgir - RankMe

12 papers Journal 8Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	GRASP: Graph Reasoning Agents for Systems Pharmacology with Human-in-the-Loop. CoRR Omid Bazgir, Vineeth Manthapuri, Ilia Rattsev, Mohammad Jafarnejad
2024	—	`conf`	Area-power and Energy Efficient Substitution box (S-box) in Advanced Encryption Standard (AES). ACM Great Lakes Symposium on VLSI Omid Bazgir, Satwik Gali, Tooraj Nikoubin
2023	J	`jnl`	Integration of Graph Neural Network and Neural-ODEs for Tumor Dynamic Prediction. CoRR Omid Bazgir, Zichen Wang, Marc Hafner, James Lu
2023	—	`conf`	Multitask-Guided Self-Supervised Tabular Learning for Patient-Specific Survival Prediction. MLCB You Wu, Omid Bazgir, Yongju Lee, Tommaso Biancalani, James Lu, Ehsan Hajiramezanali
2021	J	`jnl`	Investigation of REFINED CNN ensemble learning for anti-cancer drug sensitivity prediction. Bioinform. Omid Bazgir, Souparno Ghosh, Ranadip Pal
2020	J	`jnl`	A Novel Data-Driven Magnetic Resonance Spectroscopy Signal Analysis Framework to Quantify Metabolite Concentration. Algorithms Omid Bazgir, Eric A. Walden, Brian Nutter, Sunanda Mitra
2020	J	`jnl`	Investigation of REFINED CNN ensemble learning for anti-cancer drug sensitivity prediction. CoRR Omid Bazgir, Souparno Ghosh, Ranadip Pal
2020	—	`conf`	Kidney segmentation using 3D U-Net localized with Expectation Maximization. SSIAI Omid Bazgir, Kai Barck, Richard A. D. Carano, Robby M. Weimer, Luke Xie
2020	J	`jnl`	Kidney segmentation using 3D U-Net localized with Expectation Maximization. CoRR Omid Bazgir, Kai Barck, Richard A. D. Carano, Robby M. Weimer, Luke Xie
2019	J	`jnl`	Emotion Recognition with Machine Learning Using EEG Signals. CoRR Omid Bazgir, Zeynab Mohammadi, Seyed Amir Hassan Habibi
2019	J	`jnl`	REFINED (REpresentation of Features as Images with NEighborhood Dependencies): A novel feature representation for Convolutional Neural Networks. CoRR Omid Bazgir, Ruibo Zhang, Saugato Rahman Dhruba, Raziur Rahman, Souparno Ghosh, Ranadip Pal
2018	—	`conf`	Fully Automatic Baseline Correction in Magnetic Resonance Spectroscopy. SSIAI Omid Bazgir, Sunanda Mitra, Brian Nutter, Eric A. Walden

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.