Saber Malekmohammadi

18 papers A* 2A 1B 1Journal 13Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Differentially Private Clustered Federated Learning. Trans. Mach. Learn. Res. Saber Malekmohammadi, Afaf Taïk, Golnoosh Farnadi
2025	J	`jnl`	Sharpness-Aware Parameter Selection for Machine Unlearning. CoRR Saber Malekmohammadi, Hong-Kyu Lee, Li Xiong
2024	J	`jnl`	Mitigating Disparate Impact of Differential Privacy in Federated Learning through Robust Clustering. CoRR Saber Malekmohammadi, Afaf Taïk, Golnoosh Farnadi
2024	A*	`conf`	Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning. ICML Saber Malekmohammadi, Yaoliang Yu, Yang Cao
2024	J	`jnl`	Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning. CoRR Saber Malekmohammadi, Yaoliang Yu, Yang Cao
2024	J	`jnl`	On the Implicit Relation Between Low-Rank Adaptation and Differential Privacy. CoRR Saber Malekmohammadi, Golnoosh Farnadi
2024	J	`jnl`	Semi-Variance Reduction for Fair Federated Learning. CoRR Saber Malekmohammadi
2023	J	`jnl`	Proportional Fairness in Federated Learning. Trans. Mach. Learn. Res. Guojun Zhang, Saber Malekmohammadi, Xi Chen, Yaoliang Yu
2022	J	`jnl`	Equality Is Not Equity: Proportional Fairness in Federated Learning. CoRR Guojun Zhang, Saber Malekmohammadi, Xi Chen, Yaoliang Yu
2021	J	`jnl`	An Operator Splitting View of Federated Learning. CoRR Saber Malekmohammadi, Kiarash Shaloudegi, Zeou Hu, Yaoliang Yu
2021	A*	`conf`	Graph-SIM: A Graph-based Spatiotemporal Interaction Modelling for Pedestrian Action Prediction. ICRA Tiffany Yau, Saber Malekmohammadi, Amir Rasouli, Peter Lakner, Mohsen Rohani, Jun Luo
2021	—	`conf`	Splitting Algorithms for Federated Learning. PKDD/ECML Workshops (1) Saber Malekmohammadi, Kiarash Shaloudegi, Zeou Hu, Yaoliang Yu
2020	J	`jnl`	Graph-SIM: A Graph-based Spatiotemporal Interaction Modelling for Pedestrian Action Prediction. CoRR Tiffany Yau, Saber Malekmohammadi, Amir Rasouli, Peter Lakner, Mohsen Rohani, Jun Luo
2020	A	`conf`	Non Parametric Graph Learning for Bayesian Graph Neural Networks. UAI Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang, Yishi Xu, Mark Coates
2020	J	`jnl`	Non-Parametric Graph Learning for Bayesian Graph Neural Networks. CoRR Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang, Yishi Xu, Mark Coates
2020	J	`jnl`	PePScenes: A Novel Dataset and Baseline for Pedestrian Action Prediction in 3D. CoRR Amir Rasouli, Tiffany Yau, Peter Lakner, Saber Malekmohammadi, Mohsen Rohani, Jun Luo
2019	B	`conf`	On the Use of Wide Channels in WiFi Networks. LCN Saber Malekmohammadi, Catherine Rosenberg, Razvan Stanica
2019	J	`jnl`	Sparsity Promoting Reconstruction of Delta Modulated Voice Samples by Sequential Adaptive Thresholds. CoRR Mahdi Boloursaz Mashhadi, Saber Malekmohammadi, Farokh Marvasti

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.