Umair Mohammad

16 papers B 1Journal 7Unranked 8

Year	Rank	Type	Title / Venue / Authors
2024	B	`conf`	Lightweight Transformer exhibits comparable performance to LLMs for Seizure Prediction: A case for light-weight models for EEG data. IEEE Big Data Paras Parani, Umair Mohammad, Fahad Saeed
2024	—	`conf`	Robustness of ML-Based Seizure Prediction Using Noisy EEG Data From Limited Channels. DCOSS-IoT Umair Mohammad, Fahad Saeed
2023	J	`jnl`	Dynamic Task Allocation for Mobile Edge Learning. IEEE Trans. Mob. Comput. Umair Mohammad, Sameh Sorour, Mohamed Hefeida
2023	J	`jnl`	Energy Aware Task Allocation for Semi-Asynchronous Mobile Edge Learning. IEEE Trans. Green Commun. Netw. Umair Mohammad, Sameh Sorour, Mohamed Hefeida
2023	—	`conf`	Energy Efficient AI/ML based Continuous Monitoring at the Edge: ECG and EEG Case Study. BIBM Umair Mohammad, Fahad Saeed
2022	—	`conf`	SPERTL: Epileptic Seizure Prediction using EEG with ResNets and Transfer Learning. BHI Umair Mohammad, Fahad Saeed
2021	—	`conf`	Optimal Task Allocation for Mobile Edge Learning with Global Training Time Constraints. CCNC Umair Mohammad, Sameh Sorour, Mohamed Hefeida
2021	—	`conf`	Search feasibility in distributed MS-proteomics big data. BCB Umair Mohammad, Fahad Saeed
2021	—	`conf`	Simulation Testbed for Evaluating Distributed Querying and Searching of Mass Spectrometry Big Data in a Network-based Infrastructure. BigDataService Umair Mohammad, Fahad Saeed
2020	J	`jnl`	Optimal Task Allocation for Mobile Edge Learning with Global Training Time Constraints. CoRR Umair Mohammad, Sameh Sorour, Mohamed Hefeida
2020	J	`jnl`	Returning the Favor: What Wireless Networking Can Offer to AI and Edge Learning. CoRR Sameh Sorour, Umair Mohammad, Amr Abutuleb, Hossam S. Hassanein
2020	J	`jnl`	Task Allocation for Asynchronous Mobile Edge Learning with Delay and Energy Constraints. CoRR Umair Mohammad, Sameh Sorour, Mohamed Hefeida
2020	—	`conf`	Task Allocation for Mobile Federated and Offloaded Learning with Energy and Delay Constraints. ICC Workshops Umair Mohammad, Sameh Sorour, Mohamed Hefeida
2019	J	`jnl`	Adaptive Task Allocation for Asynchronous Federated Mobile Edge Learning. CoRR Umair Mohammad, Sameh Sorour
2019	—	`conf`	Adaptive Task Allocation for Mobile Edge Learning. WCNC Workshops Umair Mohammad, Sameh Sorour
2018	J	`jnl`	Adaptive Task Allocation for Mobile Edge Learning. CoRR Umair Mohammad, Sameh Sorour

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.